2012 ANNUAL RESEARCH REPORT

INTRODUCTION

Welcome, this report marks the 44th year of continuous crop research sponsored by California processing tomato growers. This report details research funded by the contributing growers of the California Tomato Research Institute, Inc.

It is our goal to provide useful timely information, geared to assisting growers in both daily production decisions and long term crop improvement. The Institute Board of Directors continues to support a broad range of projects, addressing both current problems and long range concerns. This Annual Research Report is sent to member growers and their associates. Since the Board of Directors does not wish to exclude anyone, including potential members, a limited number of copies are available to non- members by request by email to [email protected]

2012 BOARD OF DIRECTORS

CALIFORNIA TOMATO RESEARCH INSTITUTE, INC.

Rick Blankenship Chairman Huron

Mark Cooley Vice Chair Dixon

Dino Del Carlo Sect/Treasurer Stockton Bryan Barrios Zamora Darryl Bettencourt Corcoran Daniel Burns Dos Palos Frank Coelho Five Points Brett Ferguson Lemoore Scott Houlding Cantua Creek Cannon Michael Los Banos Scott Park Meridian Ray Perez Crows Landing Kent Stenderup Arvin Tony Turkovich Winters

California Tomato Research Institute ~ 2012 Annual Report Page i 2012 ANNUAL RESEARCH REPORT

Table of Contents

Introduction i

Board of Directors i

Projects Funded in 2012 ii

Members of the California Tomato Research Institute iv-v

Top 50 California Processing Tomato Varieties in 2012 vi

Research Project Reports by Category

Agronomic Projects

Drip Irrigated Double-Row Tomatoes on 80-inch Beds Scott Stoddard 1

Precision Tomato Production Systems for Increased Competitiveness and Resource Use Efficiency Jeff Mitchell 11

Breeding, Genetics & Variety Development Projects

UCCE Statewide Processing Tomato Variety Evaluation Trials, 2012 Brenna Aegerter 17

C.M. Rick Tomato Genetics Resource Center Roger T. Chetelat 33

Disease Management Projects

Tomato Powdery Mildew Control Brenna Aegerter 45

Development and Application of Degree Day Model and Risk Index to Predict Development of Thrips and Tomato Spotted Wilt Virus (TSWV) and Implement an IPM Strategy in California Processing Tomato Fields Robert L. Gilbertson 55

Development of a Virus Integrated Pest Management Strategy for Processing Tomatoes in California’s Central Valley William Wintermantel 73

Movement of Fusarium Oxysporum Via Equipment Gene Miyao 81

Evaluation of Fungicides, Bio-Pesticides and Soil Amendments for the Control of Southern Blight in Processing Tomatoes Joe Nunez 83

Influence of Drip Irrigation on Tomato Root Health Mike Davis 93

Breeding for Resistance to Bacterial Speck and Monitoring California Pseudomonas syringae Strains Gitta Coaker 101

Management of Root-Knot Nematodes with Novel Nematicides J. Ole Becker 109

Assessing the Potential of Nematode-Resistant Wheat Varieties for Control of Root-Knot Nematode on Tomato Valerie Williamson 113

Protection of Tomato Root Health by Bacteria from the Genus Collimonas Johan Leveau 117

Evaluation of Environmental Influence on Tomato Plant Health via Soil Transfer From Five Points to Yolo Gene Miyao 125

Field evaluation of root knot nematode resistant wheat as a cover crop ahead of tomato production Gene Miyao 129

Weed Management Projects

Within-row Weed Control System for Transplanted Processing Tomatoes David C. Slaughter 133

Field Bindweed Management in Drip Irrigated and Furrow Irrigated Processing Tomatoes W. Thomas Lanini 143 Members of the California Tomato

Kidwell Farms Tanaka Farms Inc. John Dondero Farm Sacramento Davis Woodland Linden Valley K.L.M. Ranches, Inc. Ronald Timothy Farming Fantozzi Farms Amistad Ranches Elk Grove Dixon Patterson Walnut Grove La Grande Farms Inc. TOMCO G.G. Orchards George Aoki Farms. Inc. Williams Woodland Linden Woodland Los Rios Farms Triad Farms Jerry Goubert Farms K & D Aoki Davis Davis Westley Woodland William Maupin Farms Two M Enterprises Holdener Ranches Barrios Farms Inc. Williams Dixon Stockton Yolo Mayflower Farms, Inc. Van Ruiten Bros. K and H Farms Steve Barsoom Arbuckle Robbins Tracy Walnut Grove J.H. Meek and Sons Vann Bros. Farms Lassen Farms Dan Best Ranch, Inc. Woodland Williams Stockton Woodland Joe Muller & Sons Viguie Farming J. Lombardi Farms Jim Borchard Woodland Winters Stockton Woodland Mumma Brothers Wallace Brothers F A Maggiore & Sons Bullero Farms Arbuckle Meridian Brentwood Woodland Myers Seed Joe Yeung Farms Rich Marchini Farms Bullseye Farms Colusa West Sacramento Stockton Woodland Nakahara Farms Jon Maring Farming Clarksburg Westley Button and Turkovich, LLC San Joaquin / Winters C&M Ochoa Mizuno Farms Inc. Stanislaus Casa Lupe Farms, Inc. Woodland Tracy Colusa Ornbaun Farms Alvarez Farms Inc. L & R Mussi Farms Tracy Chan Farms Arbuckle Stockton Courtland P & C Farming Arnaudo Bros Inc. Ronald Nunn Farms Tracy Dettling Farms Williams Brentwood Woodland Scott Park Farming Steve Arnaudo & Sons Patterson Westside Farms Tracy Dougherty Bros. Meridian Patterson Robbins Quad H Ranch, Inc. Bayes Ranch Pereira Farms Patterson E and H Farms Robbins Tracy Dixon Sam Reynolds Farm Matthew R Boulware Perez Farms - Crows Landing Salida E and J Farms, Inc. Williams Crows Landing Woodland Richter Bros. Inc. Cerri and Son Perez Farms - Westley Stockton Emerald Farms Knights Lndng Westley Maxwell River Vista Farms Cerutti Bros. George Perry & Sons, Inc. Newman F & F Company Colusa Manteca Walnut Grove Gene Robben Farms Cox and Perez Hal Robertson Farms Westley Fong Farms, Inc Dixon Tracy Woodland Roma Farms Cox Farms B & D Sanguinetti Farms Patterson R.C. Gill and Son Robbins Ripon Dixon Rominger Brothers Farms Del Carlo Farms R & J Sanguinetti Ranch Stockton Harlan & Dumars, Inc. Winters Linden Woodland D.A. Rominger & Sons Del Mar Farms Simoni & Massoni Farms Patterson T.A. Hatanaka Farms Winters Byron Woodland Schreiner Farms Inc. Del Terra Farms, LLC T & M Farms Tracy Hunn, Merwin and Merwin, Inc. Woodland Westley Clarksburg T & P Farms Delucchi Farms Toso Brothers Stockton J & P Farms Arbuckle Stockton Esparto California Tomato Research Institute ~ 2012 Annual Report Page iv Research Institute for 2012

Trinta Brothers W. C. Davis Farms Ralph Palazzo & Co., Inc. Kings / Patterson Firebaugh Los Banos Kern Victoria Island Farms William Deidrich Farms Perez Ranches Holt Firebaugh Firebaugh J.G. Boswell Company Bakersfield Yamamoto Farms J. Diedrich Farms Polder Bros. Farms Westley Firebaugh Lemoore Cauzza Ag Partners Buttonwillow Y and L Farms Dresick Farms, Inc. Pucheu Bros. Ranch Westley Huron Tranquility Dalena Farms, Inc. Madera D & B Yrigoyen Errotabere Ranches Red Rock Ranch, Inc Lathrop Riverdale Five Points Esajian Farming Co. Lemoore Ferguson Farming Company Refco Farms Lemoore Spreckles F & F West Merced, Lemoore Five Points Ranch, Inc. San Andreas Farms Fresno & Five Points Brentwood Fabbri Farms Bakersfield Coastal Fortune Farming Company Sano Farms, Inc. Valleys Fresno Firebaugh Freitas Ranch Hanford A-Bar Ag Enterprises Fundus Farms R.A. Sano Farms, Inc. Opal Fry and Son Los Banos Mendota Firebaugh Bakersfield Abbate Farms G & H Farms Scoto Brothers Farming, Inc. Grimmway Farms Merced Five Points Merced Bakersfield Anderson Farms, LLC Graham Farming J.O. Seasholtz Farms Gary Icardo Farms Huron Kerman Fresno Bakersfield B & T Farms Greenfields Turf, Inc. SJR Farming Island Farms LLC Gilroy Greenfield Los Banos Visalia Beene Farms Hammonds Ranch Solo Mio Farms Jerry Slough Farming Co. Helm Firebaugh Lemoore Buttonwillow J. F. Bennett Ranch Harris Farms Inc. Teicheira Farms Jones Farms Firebaugh Coalinga Los Banos Stratford Bob Filice Farms Houlding Farms Inc. Terra Linda Farms Materra Farming Company, LLC Gilroy Fresno Riverdale Bakersfield Borba Farms, Inc. Gary Hughes Farms Terrranova Ranch, Inc. Newton Farms Riverdale Kerman Helm Stratford Bowles Farming Company Lucero Farms Allen Thomsen Farming Sheely Farms Los Banos Los Banos Firebaugh Lemoore Britz Inc. D. & V. McCurdy Farms Vaquero Farms Stenderup Ag Partners Fresno Firebaugh Stockton Bakersfield Cantua Farms Robert McDonald Farms Ventura Farms, Inc. Stone Land Co. Fresno Los Banos Gustine Stratford Casaca Vineyards McKeen Farms, Inc. Westside Harvesting SVI Farming Five Points Riverdale Cantua Creek Hanford Clark Bros. Farming Motte Ranches, Inc. Will-Shar Farms Donald Valpredo Farms Clovis San Joaquin Merced Bakersfield Coelho South Nickel Family LLC Worth Farms WAY Farms Five Points Dos Palos Coalinga Bakersfield Coelho West Obata Farms Regents of Univ. CA WREC Westlake Farms Five Points Gilroy Five Points Stratford Daddyís Pride Farming Mick Oliveira Farms Hanford El Centro OPC Farms, Inc. N.F. Davis Drier & Elevator Firebaugh San Joaquin California Tomato Research Institute ~ 2012 Annual ReporT Page v 2012 California Top 50 Varieties

PTAB ID Variety Name Share Loads Mold Green MOT Color LU Solids pH 366 SUN 6366 16.3% 79,887 1.0 1.2 0.6 24.6 1.6 5.52 4.40 85 HEINZ 8504 13.3% 65,082 1.0 1.9 0.8 24.2 0.8 5.03 4.30 102 AB 2 5.3% 26,122 1.7 1.1 0.5 24.5 1.6 5.50 4.32 560 HEINZ 5608 5.3% 25,713 1.8 1.4 0.7 23.2 1.0 4.87 4.39 241 HEINZ 2401 5.0% 24,361 1.1 1.7 0.7 24.1 0.8 4.91 4.30 978 HEINZ 9780 3.6% 17,390 1.4 1.8 0.9 24.1 1.2 5.22 4.34 433 HEINZ 3402 3.4% 16,460 1.0 2.2 1.5 23.6 0.6 4.96 4.43 558 HEINZ 5508 3.1% 15,325 0.8 1.7 0.8 23.7 0.4 4.71 4.32 187 CAMPBELL CXD 187 2.9% 14,402 0.6 2.0 0.7 25.2 2.4 4.74 4.40 663 HEINZ 9663 2.9% 14,068 2.6 2.3 1.1 23.1 1.5 4.89 4.36 477 HEINZ 4707 2.8% 13,467 1.1 2.0 0.9 25.0 0.5 4.86 4.36 15 HEINZ 1015 2.0% 9,666 0.3 1.7 0.6 23.8 0.6 5.22 4.43 444 SEMINIS APT 410 1.9% 9,218 0.7 1.2 0.4 24.8 2.5 5.18 4.41 502 WOOD BRIDGE BQ 205 1.7% 8,473 1.0 1.4 0.6 24.9 1.4 5.53 4.34 368 SUN 6368 1.7% 8,150 1.6 0.6 0.5 24.8 0.8 5.11 4.34 255 CAMPBELL CXD 255 1.7% 8,144 1.3 0.7 0.4 26.3 0.9 5.11 4.34 194 UNITED GENETICS UG 19406 1.4% 6,833 1.0 1.2 0.5 23.8 0.8 5.60 4.29 3 AB 3 1.3% 6,362 1.9 0.9 0.4 24.5 1.7 5.54 4.37 849 SEMINIS HYPEEL 849 1.3% 6,307 1.6 0.5 0.4 24.8 0.5 5.01 4.35 639 NUNHEMS 6394 1.2% 5,862 2.1 0.9 0.8 23.0 3.0 5.39 4.48 206 WOOD BRIDGE BQ 206 1.2% 5,670 1.2 0.7 0.5 25.1 1.5 5.32 4.32 361 WOOD BRIDGE BQ 163 1.2% 5,641 1.2 1.2 0.5 24.5 2.5 5.51 4.38 800 HEINZ 8004 1.0% 5,001 0.9 1.4 0.4 24.5 1.2 5.35 4.43 373 VDB U 373 1.0% 4,847 1.1 1.4 0.6 25.3 2.5 4.81 4.40 491 HEINZ 9491 0.9% 4,602 1.1 2.3 0.3 24.8 2.2 4.74 4.35 261 HEINZ 2601 0.9% 4,498 1.2 0.8 0.4 25.1 1.6 5.02 4.45 656 PX 650 0.9% 4,227 1.5 0.6 0.3 25.6 1.3 5.18 4.43 180 UNITED GENETICS 18806 0.9% 4,180 1.8 1.0 0.3 25.3 1.7 5.07 4.42 701 HEINZ 5701 0.7% 3,572 1.4 1.9 1.2 24.8 0.7 4.75 4.34 602 PX 002 0.7% 3,523 1.2 1.5 0.6 24.3 1.5 4.98 4.39 672 BOS 67212 0.7% 3,400 1.3 1.0 0.4 24.3 1.8 5.25 4.44 509 BOS 66509 0.7% 3,265 1.3 2.0 0.7 25.2 2.9 5.08 4.44 397 NUNHEMS 6397 0.7% 3,212 0.7 1.6 0.6 24.6 0.7 5.30 4.41 665 HEINZ 9665 0.6% 3,094 1.4 0.8 0.4 23.6 0.5 4.91 4.31 503 HEINZ 5003 0.6% 2,893 0.6 2.7 1.3 24.6 1.5 5.23 4.38 190 UNITED GENETICS 19006 0.6% 2,730 1.4 0.9 0.6 23.5 0.9 5.52 4.31 82 CXD 282 0.5% 2,430 2.2 2.4 0.9 25.5 1.0 5.16 4.36 193 UNITED GENETICS 19306 0.5% 2,374 1.4 0.8 0.3 23.2 0.4 5.43 4.35 789 HM 7883 0.5% 2,341 0.8 0.4 0.3 23.9 0.5 4.88 4.40 586 NUNHEMS 6385 0.5% 2,329 2.1 1.6 0.8 23.6 1.1 4.71 4.38 108 SEMINIS HYPEEL 108 0.5% 2,220 1.4 0.7 0.3 25.3 1.9 5.32 4.46 990 HARRIS MORAN 9905 0.4% 2,197 1.0 0.6 0.3 24.6 0.3 4.96 4.46 910 CAMPBELL CXD 109 SHASTA 0.4% 2,100 0.5 1.1 0.5 26.2 2.1 5.54 4.30 111 DE RUITER DRI 0311 0.4% 2,010 1.5 1.3 0.5 22.7 1.5 5.79 4.34 494 HEINZ 9494 0.4% 1,964 1.4 2.6 1.3 24.9 0.9 4.62 4.38 551 BOS HALLEY 3155 0.4% 1,915 1.4 0.6 0.5 24.2 1.7 5.40 4.36 204 WOOD BRIDGE BQ 204 0.4% 1,852 0.2 1.2 0.3 24.9 1.5 5.13 4.40 611 SUN 6117 0.4% 1,778 0.3 1.3 0.3 25.4 2.7 5.34 4.38 44 NUNHEMS 6404 0.3% 1,618 1.4 0.5 0.3 24.0 1.2 5.20 4.39 885 HMX 7885 0.3% 1,412 0.5 0.8 0.2 25.0 0.5 5.06 4.48 100.0% 489,617 Table courtesy of the Processing Tomato Advisory Board More information at www.ptab.org

2012 California Tomato Research Institute Annual Report Page vi Project Title: Drip Irrigated Double - Row Tomatoes on 80-inch Beds (Final)

Project Leader: Scott Stoddard Farm Advisor Merced & Madera Counties 2145 Wardrobe Ave. Merced, CA 95340 Phone: 209-385-7403 Cell: 209-777-SOIL [email protected]

Co-investigators: Thomas A. Turini Vegetable Crops Farm Advisor, Fresno County University of California Cooperative Extension 1720 South Maple Avenue Fresno, CA 93702 Phone: (559) 456-7157 Fax: (559) 456-7575 [email protected]

Summary: This was the fourth year of a study designed to provide information regarding costs of production, yield and quality, and optimal plant population of processing tomatoes under alternative drip/bed configurations. Main plot treatments included 1) standard 60-inch bed with buried drip tape and one row of transplants in the center of the bed; 2) 80-inch bed with one buried drip tape in the center of the bed and two rows of transplants on top of the bed; 3) 80-inch bed with two buried drip lines and two rows of transplants; 4) 80-inch bed with one buried drip line and directed seeded cantaloupes in the center of the bed (fallow-tomatoes-tomatoes-melons rotation treatment). These were the same beds installed in spring of 2009, however new drip tape was installed into all plots. Split-plot treatments were plant spacing: 4000, 6000, 8000, and 10,000 plants per acre. The plots were planted with mechanical trans-planters and the TSWV- resistant cultivar N6385. Yields ranged between 35 – 50 tons/acre depending on treatment, with Brix averaging 4.9%. Despite new drip tape and substantial improvements to the irrigation manifold, deficit irrigation again occurred, especially in treatment 3, which likely reduced yields in this treatment. As in 2011, yields this year were best in the 60-inch bed treatments, a change from the first two years of this project. With the 60” beds, yields peaked between 5000 – 6000 plants per acre, but at 6000 – 7000 plants per acre in the 80-inch bed system. While the impacts of bed configuration (60” vs 80”) have not been consistent in this experiment, in all years higher yield was observed in the 80” beds at slightly greater (about 10 – 15%) plants per acre.

Methods: This trial was located at the University of California West Side Research and Extension Center (WSREC), near Five Points, CA. Soil type is a Panoche clay loam, deep and well drained. Spring soil sampling indicated low levels of N and P, but sufficient K (Table 2). The drip tape was installed into previous formed, clean beds at a depth of about 9” in early March 2012.

California Tomato Research Institute ~ 2012 Annual Report 1

The drip tape used was Netafim, 5/8” 10 mil thickness with 12” emitter spacing. Double-line treatments had 0.16 gph emitters, while the single line treatments used 0.36 gph emitters. The use of different flow rates was to keep the total amount of water applied between treatments about the same. To improve water flow, the manifold used in 2010 was retrofitted with larger, ¾” flow meters and pressure regulators. One flow meter was used for each main plot treatment.

On May 3-4, 2012, processing tomato variety N6385 was transplanted using Holland Transplanters. This variety was chosen because it is TSWV resistant. A randomized complete block split-plot design with four replications was used. Main plot treatments were bed size and drip tape configuration; sub-plot treatments were plant spacing. Each main-plot treatment was 300 ft long by three beds wide, and sub plot treatments were 75 feet long. All plots were irrigated with sprinklers for the first two weeks after transplanting and then irrigated with drip tape for the remainder of the season (May 2 – Aug 28). Treatments compared include the following: 1. Standard. 60” beds with a one drip tape at the center of the bed, single row of transplants. 2. 80” bed with single drip tape at the center of the bed, double row of transplants. 3. 80” bed with two lines of drip tape, double row of transplants. 4. 80” bed, single drip tape. Direct seeded cantaloupes (mixed variety).

Irrigation scheduling was driven by Et. Double row tape (Netafim) had 0.16 gph emitters at 12 in spacing, while the tape installed in a single line per bed had 0.36 gph emitters at 12 in spacing. Water flow was monitored through the use of water meters over the course of the season.

Plant spacing (plants per acre): 1. 4000, actual 4075 2. 6000, actual 5762 3. 8000, actual 7533 4. 10000, actual 9331

Leaf and soil sampling was performed on June 14 and again on July 26. Pest management for weeds, powdery mildew, and leaf miners were performed by the WSREC station per standard management practices. Treflan + Dual Magnum was pre-plant incorporated, followed by an application of Matrix (rimsulfuron) herbicide at 2 oz/A about 1 week after transplanting and incorporated with sprinklers. On July 23, Quadris Top, Warrior, and Radiant were applied for powdery mildew, stunk bugs, and thrips. Bravo and Quadris Top were applied about 1 month before harvest to control black mold.

Fertilizer as UN-32 was applied through the drip line beginning June 13. Four applications of 30 lbs N/A were made, for a total of 120 lbs N/A. Preplant fertilizer was 150 lbs/acre of ammonium phosphate, broadcast in January, and again in April by shanking into the beds about 10 inches deep and 10” off-center.

Harvest was performed on Sept 5 using a Johnson mechanical harvester set on 80” centers. The 60” bed plots were also harvested with this machine.

California Tomato Research Institute ~ 2012 Annual Report 2

Fruit yield was measured using the same weigh wagon utilized for the variety trials. Only the middle bed of each plot was harvested. Samples were taken at this time and submitted for PTAB analyses (Brix, color, pH). Unlike in previous year, fruit samples were not taken to estimate red, green, rot, and sunburn from each plot.

Results: Plant establishment was good this year for all plant spacing but 10,000. This treatment varied considerable from 7800 – 10,700 plants per acre, with more stand problems in the 80” beds. Due to the nature of this trial, beds are transplanted one at a time. In the double-row beds, plants were placed 10 inches off-center.

Leaf samples were taken in mid-season and sent to DANR labs for analysis. Results from 2012 are not yet available, but there were no obvious nutrient problems in any of the plots. Leaf samples from 2010 and 2011 are shown in Table 1 (these were omitted from previous reports because the results were delayed until January). There were no significant differences in nutrient levels between the treatments in 2010, but in 2011 N and K were lower in treatment 3 than any of the others, and suggests that this treatment did not receive equivalent fertilizer . Soil sample results are shown in Table 2. We attempted to ameliorate for the low soil P levels with the application of 300 lbs/A of MAP before transplanting

Yield and PTAB results are shown in Table 3. Significant differences were seen between yield, with the 80-inch bed with 2 drip lines (treatment 3) yielding significantly less than the other two. The standard 60” bed had numerically highest yields at 43.7 tons per acre (Figure 2). This also occurred in 2011, after the first two years of this trial showing better yields from the 80” beds. Plant spacing did not have a significant impact on yield in 2012, but lowest overall yields were at 10,000 plants per acre. The 80”-bed treatments were characterized by far greater yield variability, and very weak correlation (R2 = 0.09 – 0.31) between plant spacing and yield (Figure 3). While yield was reduced in the 80” bed treatments, soluble solids were significantly increased over that of the standard 60” bed. This suggests increased water stress for all 80” bed treatments, but especially treatment #3. Indeed, end of the season water use, as measured with the in-line flow meters, was not the same for all the treatments in this project (Table 4).

Preferential water flow and the change in plot area likely explain the water difference between the treatments. The 60” bed system used the same tape (0.36 gph) as treatments #2 and 4, but because each plot consisted of 3 beds, the 60” bed treatment occupied 25% less area. Since the 80” bed system with two drip lines used low-flow tape (0.16 gph), the total flow was 12% less than the high flow tape in the other treatments.

In two of four years for this project, the 80” bed configuration had reduced yield as compared to the standard 60” bed, but better Brix and pH. Averaged across all years, the 80-inch system had greater yields of 103 – 123% (Table 5). Similar in all years, however, is that yields in the 80” system peaked at slightly higher plant populations, about 10 – 15% more than the 60” bed system (Figure 3). These values were used to develop an economic analysis shown in Table 6. Based on this, the rotation treatment is the most profitable in the year when tomatoes are grown, but this does not take into consideration the expense of rotating to other crops.

California Tomato Research Institute ~ 2012 Annual Report 3

The results from 2012 again suggest that water may again have been a limiting factor in this trial, and is not being distributed evenly throughout the treatments. This is also impacting nutrient uptake, which is reflected in the leaf analysis. Unfortunately, this makes it difficult to make any firm conclusions about the potential yield benefits of the 80” system. Switching to 80” beds may initially seem to reduce production costs, but our experience has shown that this system may slow both transplanting and harvest speeds, nullifying cost savings from reduced drip tape. The reason to switch may be mainly due to convenience of not having to make wheel spacing adjustments for processing tomato growers who currently grow other crops that utilize 40” or 80” spacing.

California Tomato Research Institute ~ 2012 Annual Report 4

California Tomato Research Institute ~ 2012 Annual Report 5

California Tomato Research Institute ~ 2012 Annual Report 6

California Tomato Research Institute ~ 2012 Annual Report 7

Figure 1. Processing tomato yields for the main effects of bed/drip line configuration and plant spacing, WSREC 2012.

Figure 2. Processing tomato regression curve showing yield response to plant population for the 80” and 60” beds in 2012. The standard 60” beds displayed a nice response to plant population with reasonably good fit (R2 = 0.62), however, the 80” beds displayed a lot of variability in the data. As in the previous two years, yields were greater in the 80” beds at slightly higher plant populations as compared to where optimal yield occurred in the 60-inch beds.

California Tomato Research Institute ~ 2012 Annual Report 8

Figure 3. Regression curves for both bed systems used in this trial over 4 years comparing plant stand to yield. The red bar illustrates the zone where yields were maximized. On average this occurred at 6000 – 7000 plants per acre in the 60-inch system, and at 6600 – 7600 plants per acre in the 80-inch treatments.

California Tomato Research Institute ~ 2012 Annual Report 9

California Tomato Research Institute ~ 2012 Annual Report 10

Project Title: Precision Tomato Production Systems for Increased Competitiveness and Resource Use Efficiency

Project Leader: Jeff Mitchell Department of Plant Sciences University of California, Davis 9240 S. Riverbend Avenue, Parlier, CA 93648 Phone: (559) 646-6565 Fax: (559) 646-6593 Mobile: (559) 303-9689 [email protected]

Project Collaborators: Wes Wallender Department of Land, Air and Water Resources University of California, Davis One Shields Avenue, Davis, CA 95616 Phone: (530) 752-0688 Fax: (530) 752-5262 [email protected]

Karen Klonsky Department of Agricultural and Natural Resource Economics University of California, Davis Phone: (530) 752-3563 Fax: (530) 752-5614, [email protected]

Dan Munk Fresno County Cooperative Extension 1720 S. Maple Avenue Fresno, CA 93720 Phone: (559) 456-7561 Fax: (559) 456- 7575 [email protected]

Anil Shrestha Department of Plant Science and Mechanized Agriculture California State University, Fresno 2415 E. San Ramon Avenue M/S AS 72 Fresno, CA 93740-8033 Phone: (559) 278-5784 [email protected]

William Horwath Department of Land, Air and Water Resources University of California, Davis One Shields Avenue Davis, CA 95616 Phone: (530) 754-6029 [email protected]

California Tomato Research Institute ~ 2012 Annual Report 11

Kurt Hembree Fresno County Cooperative Extension 1720 S. Maple Avenue, Fresno, CA 93720 Phone: (559) 456-7285 Fax: (559) 456-7575 [email protected];

Tom Turini Fresno County Cooperative Extension 1720 S. Maple Avenue, Fresno, CA 93720 Phone: (559) 456-7285 Fax: (559) 456-7575

Collaborators: John Diener Red Rock Ranch P.O. Box 97, Five Points, CA 93624 Phone: (559) 288-8540 [email protected]

Scott Schmidt Farming ‘D’ P.O. Box 248, Five Points, CA 93624 Phone: (559) 285-9201 [email protected]

Ron Harben California Association of Resource Conservation Districts 4974 E. Clinton Way, Suite 214, Fresno, CA 93727 Phone: (559) 252-2192 Fax: (559) 252-5483 [email protected]

Brook Gale USDA Natural Resources Conservation Service Fresno Service Center 4625 W. Jennifer Avenue, Suite 125, Fresno, CA 93722 Phone: (559) 276-7494, Ext. 121 Fax: (559) 276-1791, [email protected]

Monte Bottens Bottens Ag Solutions, Inc. 4746 W. Jennifer Avenue, Suite 104, Fresno, CA 93722 Phone: (559) 694-1582 [email protected]

California Tomato Research Institute ~ 2012 Annual Report 12

Objectives: The goals of this proposed project are to:

1. To conduct the full battery of USDA NRCS Soil Quality Test Kit analyses on our existing long-term CT and cover cropped tomato/cotton rotation in Five Points, CA 2. To determine risks to harvest efficiency of crop and cover crop residues and devise engineering means for overcoming them, 3. To evaluate cover crop mixtures suitable for tomato production systems as a means for improving the sustainability of tomato cropping, and 4. To provide information developed in these studies widely to Central Valley tomato producers

Summary Progress Report: We evaluated a number of soil quality indicator properties in a long-standing tomato-cotton rotation study field to determine impacts of different tillage and cover crop management. Soil chemical properties did not change after twelve years, but a number of soil physical properties have changed. We also evaluated potential risks and problems of high surface residue systems with respect to tomato harvest efficiency.

Procedures: CTRI support in 2012 enabled us to conduct a battery of assays of various soil properties following a number of years of cover cropping and no-tillage practices and to also evaluate potential risks of high surface residue techniques for processing tomato harvest efficiency. Field determinations of soil EC, pH, aggregate stability, slaking, and water infiltration were carried out during the 2012 summer in our long-term tomato-cotton rotation study filed in Five Points in accordance with procedures described in the USDA Natural Resources Conservation Service Soil Quality Test Kit Guide (Soil Quality Institute, 2001) (Photo 1).

Photo 1. USDA NRCS Soil Quality Test Kit California Tomato Research Institute ~ 2012 Annual Report 13

These determinations were designed to provide a straightforward, inexpensive, and relatively easy means for assessing soil quality and to enable the ability to make side-by-side comparisons of different soil management systems to determine their relative effects on soil quality, to take measurements on the same field over time to monitor trends in soil quality as affected by soil use and management, to compare problem areas in a field to non-problem areas, and to compare measured values to a reference soil condition or to the natural ecosystem. The kit is based on fundamental laboratory protocols that have been rendered more ‘user friendly’ and easy to use.

Our study field in Five Points was initiated in 1999 and has four tillage and cover crop systems:

a. Standard tillage no cover crop b. Standard tillage with cover crop c. Conservation tillage no cover crop d. Conservation tillage with cover crop

Since the start of the study, these systems have differed significantly in terms of tillage intensity and carbon inputs. Following cotton harvest and ahead of tomato planting, for instance, the only tillage that is done in the CT plots relies on cotton stalk shredding and root pulling. There is zero tillage following tomato harvest ahead of no-till cotton seeding. The long-term goals of this work have been to evaluate the effects of these practices on the soil resource and to determine both the economic and the agronomic values and downsides of these practices.

In 2012, we also made observations and created a video related to harvest efficiency issues related to high surface residue practices.

Each of the soil quality test kit assays were determined on a relatively large number of samples as shown in Table 1.

Table 1.

Soil quality determination # of samples per plot # of samples per field

Water infiltration 2 64 Slaking 4 256 Aggregate stability 4 256 pH 4 256 EC 4 256

Results/Finding: Following twelve years of using different tillage and cover crop management in this tomato/cotton rotation, we detected differences in some, but not all soil properties that we assayed. Soil EC and pH do not appear to have changed as a result of management (Table 2).

California Tomato Research Institute ~ 2012 Annual Report 14

Table 2.

System pH EC (dS/m)

STNO 7.46 + 0.3 1.04 + 0.32 STCC 7.44 + 0.25 0.98 + 0.25 CTNO 7.38 + 0.18 1.0 + 0.4 CTCC 7.45 + 0.33 0.81 + 0.29

In general, rather large differences were detected, however, in a number of soil physical properties (Table 3). These differences may to some extent have been ‘expected’ based on findings from other regions and other cropping systems, but they represent the first time any sort of comprehensive investigations such as this have been conducted in Central San Joaquin Valley tomato field soils.

Table 3.

System Aggregate Slaking* Water Infiltration (time) Stability (%) (Slaking class) (First inch of (Second inch of water) water)

STNO 28.3 + 14.2 3.18 + 0.56 2:02 + 0:44 10:14 + 2:23 STCC 47.0 + 19.1 3.65 + 0.38 0:35 + 0:15 4:54 + 2:08 CTNO 40.4 + 15.7 3.76 + 0.53 1:29 + 1:05 13:41 + 12:13 CTCC 69.9 + 9.5 5.28 + 0.52 0:06 + 0:03 0:53 + 0:43

The one finding that is of particular note is water infiltration. These data indicate rather striking differences in water infiltration (time for one inch of water to infiltrate into the soil, followed by the time for a second inch to infiltrate). However, a perhaps more subtle look at these data suggest that while water infiltration appears to have been impacted by tillage/cover crop treatments for the first inch of applied water, there was actually a delayed rate for the second inch in the CTNO system suggesting perhaps that the density of the soil in this system has become higher and that the soil is now harder in surface layers. We will determine the bulk density in 2013 and see if it is a negative outcome of the CT systems.

These assays now provide a baseline set of values that indicate the range of changes that might be expected in some key soil quality properties following rather different management. The significance of this information can be considered from at least a couple of perspectives. First, these findings suggest that it is possible to impact soil quality properties in a generally positive direction in quantifiable ways with sustained and rather severe management changes. Second, the functional significance of these findings may not be all that clear UNLESS either they result in greater productivity or profitability, OR, a means for more efficient resource conservation, - i.e. increased water holding capacity, reduced soil water evaporation, lower tillage costs, or other so-called ‘ecosystem services.’ We propose to conduct an in-depth investigation of the water holding capacity of these soils in 2013.

California Tomato Research Institute ~ 2012 Annual Report 15

We also wish to point out the CTRI funding of this work in 2012, has allowed us to leverage adjunct funding from the USDA Natural Resources Conservation Service Conservation Innovation Grants Program. Results from this CTRI work have been shared with over 150 attendees of our 2012 Twilight Conservation Agriculture and Precision Irrigation Field Tour and Barbeque that was held in Five Points on September 13.

*Stability Class Criteria for assignment to stability class (for ‘Standard Characterization’)

0 Soil too unstable to sample (falls through sieve) 1 50% of structural integrity lost within 5 seconds of insertion in water 2 50% of structural integrity lost 5 – 30 seconds after insertion 3 50% of structural integrity lost 30 – 300 seconds after insertion or < 10% of soil remains on the sieve after 5 dipping cycles 4 10 – 25% of soil remaining on sieve after 5 dipping cycles 5 25 – 75% of soil remaining on sieve after 5 dipping cycles 6 75 – 100% of soil remaining on sieve after 5 dipping cycles

California Tomato Research Institute ~ 2012 Annual Report 16

Project Title: UCCE Statewide Processing Tomato Variety Evaluation Trials, 2012

Project Leader: Brenna Aegerter, Farm Advisor UCCE San Joaquin County 2101 E. Earhart Ave., Ste 200 Stockton, CA 95206 209-953-6114 [email protected] Cooperating UC Personnel: Diane Barrett, Food Science & Technology CE Specialist, UC Davis Tim Hartz, Vegetable Crops CE Specialist, UC Davis Michelle Le Strange, Farm Advisor, Tulare & Kings Counties Gene Miyao, Farm Advisor, Yolo, Solano, & Sacramento Counties Joe Nunez, Farm Advisor, Kern County Scott Stoddard, Farm Advisor, Merced & Madera Counties Tom Turini, Farm Advisor, Fresno County

Summary: University of California Cooperative Extension farm advisors, in cooperation with commercial growers, conducted two early-maturity and six mid-maturity variety evaluation trials in 2012. Seed companies submitted 15 early lines, and 16 replicated and 15 observational entries for the mid-maturity/full-season trial. A major change for our variety evaluation program was the move this season of both Fresno County trials from a field station to commercial fields. This season’s trials saw wide variations in both yield and soluble solids between locations.

Among the early-maturity lines, top performers were HMX 1893 and N 6397 for yield and SVR 024 9 0541 and HMX 1893 for soluble solids. Among full season varieties in the replicated trials, HM 9905, N 6404 and N 6402 were highest yielding, while BQ 205, DRI 0319, AB 0311, and N 6402 were highest in soluble solids. There were no significant yield differences in the observational full season variety trials, while soluble solids were highest from H 1161 and SVR 024 9 0686. Variety performance varied significantly by trial, highlighting the importance of looking at results from the individual trials to gauge variety performance under different conditions.

Objectives: The major objective of our project is to evaluate pre-commercial and early commercial release processing tomato varieties for fruit yield, soluble solids, color, and pH in replicated field trials conducted at multiple locations statewide. The data are combined from multiple trials to evaluate variety adaptability under a wide range of growing conditions. These tests are designed and conducted with input from seed companies, processors, and other allied industry members and are intended to generate third-party information on varieties to assist in decision-making.

California Tomato Research Institute ~ 2012 Annual Report 17

Procedures: Two early maturity and six mid-maturity/full-season variety evaluation trials were conducted in 2012. Details of the trials are presented in Table 1. Variety selections were made in October of 2011 with input from California tomato processors. Changes and/or additions were made by the seed companies based on seed availability. Table 2 lists the variety entries, their disease resistances and other characteristics as provided by the seed companies.

Test locations were transplanted from early April (Yolo and Fresno) through May 18th (San Joaquin). New varieties are generally evaluated for one of more years in non-replicated observational trials before moving forward for evaluation in the replicated trials. This year all the trials were conducted in commercial production fields with grower cooperators. This was a major change for the trials in Fresno County, as these trials had previously been conducted at UC’s West Side Research and Extension Center.

Each variety was planted in a single-bed plot measuring 50 to 100 feet in length, depending on the trial location. Both double and single row plots were utilized, again depending on location (see Table 1). Experimental design of each trial was a randomized complete block with four replications. The observational trial consisted of single plots of each variety planted adjacent to the replicated trial. The farm advisor organized transplanting at the same time that the rest of the field was planted. All cultural operations, with the exception of planting and harvest, were done by the grower cooperator using the same equipment and techniques as the rest of the field. All locations used transplants and all but two used drip irrigation. A field day or arrangements for interested persons to visit the plots occurred at most locations.

Shortly before or during harvest, fruit samples were collected from each plot and submitted to a grading station run by the Processing Tomato Advisory Board (PTAB) for measurement of raw fruit quality including soluble solids (reported as °Brix, an estimate of the soluble solids percentage using a refractometer), color (LED color), and fruit pH. These samples consisted of ripe fruit picked from the vines or pulled off the harvester. Additionally, fruit samples were analyzed for cooked fruit quality by the lab of Diane Barrett at UC Davis with funding from the California League of Food Processors; results of those analyses are not reported here but are available from Dr. Barrett. For yield data, the tomatoes the plots were harvested with commercial harvest equipment, conveyed to a GT wagon equipped with weigh cells, and weighed before going to the bulk trailers for processing.

Yield and fruit quality data were subjected to analysis of variance using the SAS software package. When data were combined from multiple locations, the block effect was nested within each county. Mean separation tests were performed using Fisher’s protected LSD at the 5% level. Kern County and San Joaquin County trials were missing yield data from one or more plots, therefore least-squares means are reported rather than arithmetic means. The Stanislaus replicated trial data were excluded from the analyses due to poor plant stands resulting from challenging weather conditions after transplanting. The Kern observational trial was excluded from the combined analysis due to a high number of missing plots.

California Tomato Research Institute ~ 2012 Annual Report 18

Results: Early replicated. The combined analysis of two locations of early-maturity varieties revealed that the varieties varied significantly for yield and fruit quality measurements. Because there were such major differences between these two trials, it is suggested that the results of the individual trials (Tables 3b and 3c) should be considered more informative than the combined analysis (Table 3a). The Fresno County trial experienced very good growing conditions with high yields and mean soluble solids of 5.4 °Brix, while the Yolo location suffered from a shortage of water during a critical stage, resulting in low yields and very high soluble solids (mean of 6.8 °Brix). The variety HMX 1893 was the yield leader at the Fresno location, ranked third for yield at the Yolo location, and ranked second for soluble solids at both locations. The variety N 6397 also did well at both locations (ranked fifth for yield and °Brix at Yolo, third for yield and sixth for °Brix at Fresno). Ranking of most other varieties shifted dramatically between the two locations (see Tables 3b and 3c), suggesting that the trial conditions may have played an important role in variety performance.

Mid replicated. Replicated trials of mid-maturity/full-season varieties were conducted at six locations, but results of only five trials are presented due to an issue of poor stand at one location. Results of analyses combining all locations are shown in Table 4a, and individual trials in Tables 4b – e.

Combining all trials together for analysis, the varieties varied significantly for yield and all fruit quality measurements. However, there was also a significant variety by location interaction for yield, Brix and pH, meaning that varieties performed somewhat differently depending on the trial location. Therefore, the reader should use some caution when viewing the combined results (Table 4a), and may find it more informative to look at the results of individual trials (Table 4b to 4e).

Mean yield of the combined trials was 47 tons per acre, with a wide range of trial averages from 32.7 (Fresno) to 63.4 tons per acre (Yolo). Variety HM 9905 ranked first overall with a mean of 53.2 tons per acre; it was the top performer in the Kern, Fresno and San Joaquin county trials. At other locations, first-ranked varieties were UG 19406 (Yolo) and N 6402 (Merced). See Table 4b.

Overall, the soluble solids averaged 5.3 °Brix when data were combined from all trials, but trial averages varied widely from 4.6 to 6.4 °Brix (from Fresno and Merced trials respectively, see Table 4c). Top performers overall were BQ 205, DRI 0319, AB 0311, and N 6402. However, at particular locations, other varieties made it into that top group (for example, AB 2 at Yolo and Fresno, and N 6404 at San Joaquin and Kern). The leaders for Brix-yield (tons per acre x °Brix) were N 6402 and N 6404.

The Merced County trial had the best fruit color overall (average of 20.6). Best fruit color was observed in varieties H 5608, SUN 6366, AB 0311, and N 6402, with LED color measurements averaging 21.2 to 21.7. (Table 4d). Fruit pH of vareities ranged from 4.32 to 4.51 (mean = 4.40, Table 4e), with lowest means for UG 19406, UG 19006, AB 2, and PX 024 8 1245. The Merced trial had the highest average pH, while the Yolo and San Joaquin trials had the lowest pH (4.33).

California Tomato Research Institute ~ 2012 Annual Report 19

Mid observational. Mid-maturity/full-season varieties which are new to our trial program were evaluated in single plots at six locations. Results of analyses combining five of these locations are shown in Table 5a, and individual trial results are in Tables 5b – 5e. While the average yields of varieties ranged from 35 to 50.1 tons per acre, these means were found to be statistically similar; therefore no conclusions can be drawn regarding yield due to the high variability between trial locations (Table 5b). Because these varieties are not replicated within a trial location, we do not know if the variation in performance by location is due to the particular conditions of that location or due to experimental error (random factors not of interest). When all trials were combined for analysis, significant differences were found among varieties for °Brix, color, and pH (Table 5a). Varieties with the highest soluble solids were BQ 268, H 1161, and SVR 024 9 0686 (5.7 to 5.8 °Brix). Those with the best color included C 316, H 1175 and BQ 272 (measurements of 21 to 21.6). Fruit pH was lowest in H 1161 and H 1170 (pH of 4.31 to 4.35).

Acknowledgements: Many thanks to the California Tomato Research Institute and to participating seed companies for their continued support of this project. The cooperation of the Processing Tomato Advisory Board and of the California tomato processors is also greatly appreciated. A special thanks to Gail Nishimoto for her help with the statistical analyses. Thanks to Sam Matoba of the Diane Barrett lab for managing the analysis of cooked fruit quality and dealing with our compressed planting and harvest schedule this season. And lastly, we are indebted to our excellent grower cooperators for their very generous in-kind support. It is their interest in and support of research that makes this project possible.

California Tomato Research Institute ~ 2012 Annual Report 20

Table 1. 2012 UCCE processing tomato variety trial details. Fresno Yolo County Merced Fresno Kern County Yolo County Stanislaus San Joaquin County Early Early County County County County M LeStrange M LeStrange Advisor: G. Miyao S. Stoddard J. Nunez G. Miyao S. Stoddard B. Aegerter & T. Turini & T. Turini Transplant date: 5-Apr 6-Apr 30-Apr 2-May 4-May 9-May 14-May 18-May

Fruit quality 6-Aug (123 2-Aug (118 9-Sep (132 17-Sep (138 6-Sep (125 12-Sep (126 16-Sep (125 28-Sep (133 sampling date: days) days) days) days) days) days) days) days)

15-Aug (132 2-Aug (118 26-Sep (149 18-Sep (139 14-Sep (133 12-Sep (126 26-Sep (135 29-Sep (134 Harvest date: days) days) days) days) days) days) days) days) D.A. Hal A-Bar Ranch, Fanucchi JH Meek & Cooperator and Farming D, Rominger & Harris Farms, Cox & Perez, Robertson s. of Dos Farms, s. Sons, w. of trial location: Five Points Sons, Five Points Westley Farms, s. of Palos Kern Co. Davis Winters Tracy Irrigation: buried drip furrow buried drip buried drip buried drip buried drip furrow buried drip 66” single 80” double row, 17” 60” double 80” double row, 20” 60” single Bed width, plant 60” double 66” double spacing, row, ~8700 row, ~7200 spacing, 60” row, ~7000 density row row ~5600 plants/ac plants/ac ~7840 plant/ac plants/ac plants/ac Field variety H 8504 N 6385 H 4407 H 5508 poor stand good stand, due to high Missing data good stand, near perfect water some CTV & winds at some TSWV due to tree good growth- Notes: growing shortage; TSWV; split planting, data and CTV being in way Vert and conditions very low y ield set at harvest not included of harvester. some TSWV and high Brix in combined analysis

California Tomato Research Institute ~ 2012 Annual Report 21

Table 2. Varieties evaluated in 2012: information provided by seed companies. UC days to Disease processed std fruit UC trial TRIAL VAR COMPANY code maturity Resistance use Brix compared vine size shape years Early APT 410 (STD) Monsanto 732 114 VFFNP Multiuse med chk med 78 g 97 - 08, 11, 12 Replicated BOS602 Orsetti 1005 114 VFFN Multiuse 5.3 APT410 med-lg blocky 11, 12 BQ204 Woodbridge Seeds1008 105 VFFNP dice/paste med H2206 compact 63 g 11, 12 BQ287 Woodbridge Seeds1029 106 VFFNP Multiuse, EFH high H2206 med 75 g 12 H1015 Heinz 1009 114 VFFNP Multiuse, EFH 5.2 APT410 med blocky 11, 12 H2206 (STD) Heinz 951 99 VF Multiuse, EFH 5.11 compact round 07, 08, 11, 12 H3044 Heinz 472 110 VFFN Multiuse 4.82 med blocky 89, 90, 92-98, 11, 12 HMX 1893 Harris Moran 1030 116 VFFN TSW multiuse high med elong. sq 12 K2769 Keithly Williams 1010 VFFNP 11, 12 K2770 Keithly Williams 1011 VFFN TYLCV 11, 12 N6397 Nunhems 1012 116 VFFN Multiuse high APT410 Large round 11, 12 SVR 024 9 0541 Monsanto 1031 114 VFFP APT410 12 SVR 024 9 0599 Monsanto 1032 110 VFF 12 UG 15308 United Genetics 1015 114 VFFNP peel 5.3 APT410 med sq round 11, 12 UG 15908 United Genetics 1016 114 VFFNP TSW peel 5.3 APT410 med sq round 11, 12 Mid AB 0311 Monsanto 1017 118 VFFNP SW intermediate bostwick5.6 AB2/6366 med-lg 11,12 Replicated AB 2 (STD) Monsanto 868 122 VFFP Multiuse 5.3 check med sq standard since '05 BQ 163 Woodbridge Seeds982 118 VFFNP Paste/peel 5.7-5.9 AB2 med blocky 10, 11, 12 BQ 205 Woodbridge Seeds984 120 VFFNP paste/peel 5.7-6.2 6366 lg blocky 10, 11, 12 DRI 0319 Monsanto 1023 125 VFFNP SWintermediate bostwick5.7 AB2/6366 lg 12 H 5508 Heinz Seed 986 128 VFFN SW paste 4.8 H9780 lg blocky 09,10, 11, 12 H 5608 Heinz Seed 987 128 VFFNP SW MultiUse 5 H9780 V. lg blocky 10, 11, 12 H 9780 (STD) Heinz Seed 866 139 VFFNP Multiuse 5.4 H9780 V. lg blocky 02, 03, 05-12 HM9905 Harris Moran 999 125 VFFN Multiuse, EFH med N6368 lg elong. sq 10,11, 12 N 6402 Nunhems 1027 122 VFFN SW solids/multiuse 5.6-5.7 AB2/6366 lg blocky 12 N 6404 Nunhems 1026 125 VFFN SW multiuse 5.3-5.4 H 8504 med-lg blocky 12 PX 024 8 1245 Monsanto 1013 125 VFFNP Multiuse, EFH 5.2 AB2/S6366 med-lg large 11(early), 12 SUN 6366 (STD) Nunhems 919 118 VFFNP Multiuse high AB2/As410 med sq/blocky 04 to 12 UG 19006 United Genetics 1003 125 VFFNP Multiuse, EFH med H8504/H9780 lg sq round 10,11, 12 UG 19306 United Genetics 1004 130 VFFNP Multiuse, EFH med H9557/H9780 lg sq round 10,11, 12 UG19406 United Genetics 991 128 VFFNP Multiuse, EFH high H9780 lg sq round 09 to 12 Mid BQ 268 Woodbridge Seeds1034 118 VFFNP med-hi visc, EFH 5.3-5.5 lg 12 OBSERVED BQ 270 Woodbridge Seeds1035 118 VFFNP med vis, peeler 5.7-5.9 lg 12 BQ 272 Woodbridge Seeds1036 125 VFFNP SW' multi/visc 5.5-5.7 lg 12 BQ 273 Woodbridge Seeds1033 125 VFFNP SW high visc 5.4 med-lg 12 C 316 Harris Moran 1037 124 VFFFNP multiuse high Hypeel 849 med oval 12 H 1161 Heinz Seed 1038 125 VFFNP thin/multiuse 5.8 AB2 lg oval 12 H 1170 Heinz Seed 1039 128 VFFN thick/multiuse, EFH 5.3 H 9780 lg blocky 12 H 1175 Heinz Seed 1040 130 VFFN paste, EFH 4.9 H 9780 V lg blocky 12 HMX1885 Harris Moran 1025 120 VFFNP TSW multiuse med/hi H5608 lg blocky/sq 11, 12 HMX1892 Harris Moran 1041 122 VFFNP Multiuse, EFH high H3402 lg elong. sq 12 HMX1894 Harris Moran 1042 125 VFFNP TSW pear peel, EFH med H2601 lg pear 12 N 6405 Nunhems USA 1046 125 VFFN solids/multiuse 5.6-5.7 AB2/6366/8504 med blocky 12 N 6407 Nunhems USA 1043 130 VFFN SW solids, EFH 5.5-5.6 6368/ 9780 med-lg blocky 12 SVR 024 9 0686 Monsanto 1044 125 not provided AB2/6366 12 UG 18806 United Genetics 1045 125 VFFNP thick, EFH med sq round 12

V = Verticillium Wilt race 1 All descriptions were provided by participating seed companies. FFF = Fusarium Wilt races 1 & 2Check & 3 with seed company to confirm disease resistance. N = Root knot nematode Bsp, P = Bacterial speck race 0 TSWV, SW = Spotted Wilt TYLCV = Tomato Yellow Leaf Curl Virus

California Tomato Research Institute ~ 2012 Annual Report 22

Table 3a. Early maturity processing tomato varieties, combined analysis, two replicated trial locations, 2012.

Soluble solids Variety Yield (tons/ac) (°Brix) Color pH

HMX 1893 46.7 (1) a 6.5 (2) 21.4 (11) 4.35 (1)

N 6397 45.6 (2) a b 6.3 (5) 20.6 (6) 4.52 (14)

H 1015 44.9 (3) a b 6.1 (9) 20.3 (1) 4.49 (10)

UG 15908 44.3 (4) a b 6.0 (11) 21.0 (7) 4.46 (6)

K 2770 43.5 (5) a b c 5.7 (14) 21.4 (11) 4.39 (2)

SVR 024 9 0599 43.4 (6) a b c 6.3 (3) 21.4 (11) 4.44 (3)

BOS 602 42.9 (7) b c 6.0 (10) 20.3 (1) 4.45 (5)

UG 15308 42.7 (8) b c d 6.3 (4) 20.4 (4) 4.52 (14)

BQ 287 42.5 (9) b c d 6.1 (8) 20.3 (1) 4.49 (10)

SVR 024 9 0541 42.2 (10) b c d 6.7 (1) 21.0 (7) 4.49 (10)

APT 410 (STD) 40.4 (11) c d e 5.9 (12) 21.0 (7) 4.47 (9)

H 3044 40.1 (12) c d e 5.4 (15) 20.4 (4) 4.44 (3)

BQ 204 39.3 (13) d e 5.8 (13) 21.5 (14) 4.51 (13)

K 2769 37.4 (14) e 6.2 (6) 21.3 (10) 4.46 (6)

H 2206 (STD) 37.1 (15) e 6.1 (7) 21.6 (15) 4.46 (6)

Mean 42.2 6.1 20.9 4.46

CV= 8.2 5.6 3.5 1.6 LSD @ 0.05= 3.43 0.34 0.73 0.071 # Locations 2 2 2 2

Numbers in parentheses ( x ) represent relative ranking within a column. LSD = Least significant difference at the 95% confidence level. Means followed by the same letter are not significantly different. CV = coefficient of variation (%), a measure of the variability in the experiment.

California Tomato Research Institute ~ 2012 Annual Report 23

Table 3b. Early maturity processing tomato varieties, Fresno County trial, 2012

Soluble solids Variety Yield (tons/ac) (° Brix) LED color pH HMX 1893 71.3 a 5.7 (2) 21.5 (11) 4.30 (1) UG 15908 70.1 a 5.1 (13) 21.8 (14) 4.43 (9) N 6397 69.4 a b 5.5 (6) 21.0 (5) 4.48 (14) H 1015 69.3 a b 5.5 (6) 20.3 (3) 4.44 (11) UG 15308 68.2 a b c 5.4 (8) 21.0 (5) 4.48 (14) K 2770 67.3 a b c d 5.2 (11) 21.3 (10) 4.30 (1) BQ 287 64.5 b c d e 5.7 (2) 20.0 (1) 4.43 (9) SVR 024 9 0541 64.0 b c d e 5.7 (2) 22.0 (15) 4.47 (13) APT 410 (STD) 63.1 c d e 5.1 (13) 21.5 (11) 4.41 (8) SVR 024 9 0599 62.0 d e 5.6 (5) 21.0 (5) 4.40 (5) BOS 602 61.5 e 5.4 (8) 20.0 (1) 4.40 (5) H 3044 60.9 e 4.8 (15) 20.8 (4) 4.38 (3) BQ 204 59.2 e 5.2 (11) 21.0 (5) 4.45 (12) H 2206 (STD) 52.9 f 5.4 (8) 21.5 (11) 4.40 (5) K 2769 52.8 f 5.9 (1) 21.0 (5) 4.38 (3)

Mean 63.8 5.4 21.0 4.41

CV 5.9 6.6 3.5 1.6 LSD @ 0.05= 5.36 0.51 1.04 0.101

Table 3c. Early maturity processing tomato varieties, Yolo County trial, 2012

Soluble Variety Yield (tons/ac) solids (°Brix) LED color pH SVR 024 9 0599 24.8 (1) a 7.1 (4) 21.8 (13) 4.48 (2) BOS 602 24.4 (2) a 6.6 (10) 20.5 (7) 4.50 (5) HMX 1893 22.1 (3) a b 7.3 (2) 21.3 (10) 4.40 (1) K 2769 22.0 (4) a b c 6.6 (10) 21.5 (11) 4.53 (9) N 6397 21.9 (5) a b c 7.0 (5) 20.3 (4) 4.55 (13) H 2206 (STD) 21.3 (6) a b c d 6.9 (6) 21.8 (13) 4.53 (9) BQ 287 20.6 (7) a b c d 6.5 (12) 20.5 (7) 4.54 (11) H 1015 20.4 (8) a b c d 6.8 (7) 20.3 (4) 4.54 (11) SVR 024 9 0541 20.4 (8) a b c d 7.6 (1) 20.0 (2) 4.52 (7) K 2770 19.7 (10) b c d 6.2 (14) 21.5 (11) 4.49 (3) BQ 204 19.4 (11) b c d 6.5 (12) 22.0 (15) 4.56 (15) H 3044 19.4 (11) b c d 6.0 (15) 20.0 (2) 4.51 (6) UG 15908 18.4 (13) b c d 6.8 (7) 20.3 (4) 4.49 (3) APT 410 (STD) 17.6 (14) c d 6.7 (9) 20.5 (7) 4.52 (7) UG 15308 17.1 (15) d 7.2 (3) 19.8 (1) 4.55 (13)

Mean 20.6 6.8 20.8 4.51

CV 15.1 4.8 3.5 1.6 LSD 4.44 0.46 1.05 NS

California Tomato Research Institute ~ 2012 Annual Report 24

Tables 4a - 4e. Processing tomato varieties, combined analysis of five replicated trials, 2012. Soluble plots Yield* solids Variety (#) (tons/acre) (°Brix) Color pH HM 9905 20 53.2 (1) a 5.1 (12) 22.7 (14) 4.50 (15)

N 6404 19 49.7 (2) b 5.5 (5) 22.4 (10) 4.43 (11)

N 6402 19 49.6 (3) b c 5.6 (3) 21.7 (4) 4.47 (14)

H 5508 20 49.5 (4) b c d 4.6 (16) 22.2 (7) 4.37 (6)

UG 19406 20 48.6 (5) b c d e 5.5 (5) 22.3 (9) 4.32 (1)

SUN 6366 (STD) 20 48.2 (6) b c d e f 5.4 (8) 21.6 (2) 4.51 (16)

UG 19306 20 47.9 (7) b c d e f g 5.3 (10) 22.2 (7) 4.37 (6)

H 5608 20 46.2 (8) c d e f g h 4.8 (15) 21.2 (1) 4.44 (13)

PX 024 8 1245 19 46.1 (9) d e f g h 5.0 (14) 23.7 (16) 4.35 (4)

DRI 0319 18 45.7 (10) e f g h i 5.7 (1) 22.4 (10) 4.38 (8)

AB 0311 20 45.1 (11) f g h i 5.6 (3) 21.6 (2) 4.36 (5)

AB 2 (STD) 20 45.0 (12) f g h i 5.4 (8) 22.7 (14) 4.34 (3)

BQ 205 19 44.6 (13) g h i 5.7 (1) 22.5 (12) 4.41 (10)

H 9780 (STD) 20 44.4 (14) h i 5.1 (12) 22.6 (13) 4.40 (9)

BQ 163 19 44.1 (15) h i 5.5 (5) 21.9 (5) 4.43 (11) UG 19006 20 42.5 (16) i 5.3 (10) 21.9 (5) 4.33 (2)

Mean 47.0 5.3 22.2 4.40

CV= 11.7 5.9 4.3 1.4 LSD @ 0.05= 3.43 0.19 0.59 0.037 # Locations 5 5 5 5 LSD @ 0.05 to compare yields of varieties w ith 20 plots w ith each 3.43 other LSD @ 0.05 to compare yields of varieties w ith 19 plots w ith each 3.52 other LSD @ 0.05 to compare yields of varieties w ith 20 plots vs. 3.48 varieties w ith 19 plots LSD @ 0.05 to compare yields of varieties w ith 20 plots vs. 3.53 varieties w ith 18 plots LSD @ 0.05 to compare yields of varieties w ith 19 plots vs. 3.57 varieties w ith 18 plots * For yield, some varieties have one or more missing plots. Least squares means for these varieties are reported rather than arithmetic means. Numbers in parentheses ( x ) represent relative ranking within a column. LSD = Least significant difference at the 95% confidence level. Means followed by the same letter are not significantly different. NS = not significant.

California Tomato Research Institute ~ 2012 Annual Report 25 CV = coefficient of variation (%), a measure of the variability in the experiment. Table 4b. Yield (tons/acre)

plots San Variety (#) Mean of five locations Yolo Joaquin Fresno Kern Merced HM 9905 20 53.2 a 66.6 44.4 41.2 66.0 47.7 N 6404 19 49.7 b 67.7 35.6 34.8 61.4 49.1 N 6402 19 49.6 b c 67.9 35.6 30.1 57.7 56.6 H 5508 20 49.5 b c d 64.1 42.4 34.7 52.7 53.4 UG 19406 20 48.6 b c d e 69.6 44.3 34.9 50.6 43.7 SUN 6366 (STD) 20 48.2 b c d e f 63.2 40.7 30.8 55.5 50.7 UG 19306 20 47.9 b c d e f g 66.9 37.6 31.8 61.3 42.0 H 5608 20 46.2 c d e f g h 60.9 41.7 33.8 49.5 45.1 PX 024 8 1245 19 46.1 d e f g h 54.0 45.3 35.0 44.3 51.9 DRI 0319 18 45.7 e f g h i 63.8 38.0 32.5 52.2 42.0 AB 0311 20 45.1 f g h i 62.6 36.9 29.8 47.1 48.9 AB 2 (STD) 20 45.0 f g h i 67.2 38.0 28.4 45.2 46.0 BQ 205 19 44.6 g h i 65.5 36.1 31.0 43.4 46.9 H 9780 (STD) 20 44.4 h i 53.7 38.0 26.5 57.6 46.0 BQ 163 19 44.1 h i 59.1 34.8 33.9 47.2 45.6 UG 19006 20 42.5 i 61.5 36.4 34.0 35.3 45.3

Mean 47.0 63.4 39.2 32.7 51.7 47.6 CV 11.7 5.9 8.4 10.2 18.5 10.8 LSD 3.43 5.35 4.71 4.74 13.67 7.31

VarXLoc LSD 7.68 to compare variety yields at different locations # Locations 5

LSD @ 0.05 to compare yields of varieties w ith 20 plots w ith each 3.43 other LSD @ 0.05 to compare yields of varieties w ith 19 plots w ith each 3.52 other LSD @ 0.05 to compare yields of varieties w ith 20 plots vs. varieties 3.48 with 19 plots LSD @ 0.05 to compare yields of varieties w ith 20 plots vs. varieties 3.53 with 18 plots LSD @ 0.05 to compare yields of varieties w ith 19 plots vs. varieties 3.57 with 18 plots

* For yield, some varieties have one or more missing plots. Least squares means for these varieties are reported rather than arithmetic means. LSD = Least significant difference at the 95% confidence level. Means followed by the same letter are not significantly different. CV = coefficient of variation (%), a measure of the variability in the experiment.

California Tomato Research Institute ~ 2012 Annual Report 26

Table 4c. Soluble solids (°Brix) San Variety Mean of five locations Yolo Joaquin Fresno Kern Merced BQ 205 5.7 a 5.1 5.2 5.0 6.1 7.3 DRI 0319 5.7 a 5.6 5.2 4.7 6.0 7.0 AB 0311 5.6 a b 5.4 5.2 4.8 5.6 7.2 N 6402 5.6 a b c 4.8 5.3 4.7 6.1 7.0 BQ 163 5.5 b c d 5.0 5.1 4.8 5.9 6.7 N 6404 5.5 b c d e 5.0 5.3 4.3 6.2 6.6 UG 19406 5.5 b c d e 4.9 4.9 4.9 5.7 6.9 AB 2 (STD) 5.4 b c d e 5.2 5.2 5.0 5.6 6.2 SUN 6366 (STD) 5.4 c d e 4.6 5.0 4.9 5.9 6.5 UG 19006 5.3 d e 5.0 4.8 4.6 5.9 6.3 UG 19306 5.3 e f 5.0 5.1 4.6 5.6 6.2 H 9780 (STD) 5.1 f g 5.1 5.0 4.5 5.4 5.6 HM 9905 5.1 g 4.6 4.7 4.7 5.3 6.1 PX 024 8 1245 5.0 g 4.7 4.7 4.6 5.3 5.9 H 5608 4.8 h 4.4 4.2 4.3 5.6 5.6 H 5508 4.6 h 4.3 4.2 3.8 5.4 5.4

MEAN 5.3 4.9 4.9 4.6 5.7 6.4

CV 5.9 4.9 4.8 5.2 7.3 5.9 LSD 0.19 0.34 0.34 0.34 0.59 0.54 VarXLoc LSD 0.44 to compare varieties at different locations

LSD = Least significant difference at the 95% confidence level. Means followed by the same letter are not significantly different. CV = coefficient of variation (%), a measure of the variability in the experiment.

California Tomato Research Institute ~ 2012 Annual Report 27

Table 4d. PTAB (LED) color San Variety Mean of five locations Yolo Joaquin Fresno Kern Merced H 5608 21.2 a 21.5 21.0 21.8 21.5 20.3 SUN 6366 (STD) 21.6 a b 23.3 21.3 21.8 21.5 20.0 AB 0311 21.6 a b c 22.0 21.5 23.0 21.5 20.0 N 6402 21.7 a b c 22.5 21.3 23.8 21.3 19.5 BQ 163 21.9 b c d 23.5 21.0 22.5 22.3 20.0 UG 19006 21.9 b c d e 23.5 20.5 22.5 22.5 20.5 H 5508 22.2 c d e f 23.3 21.5 23.5 21.8 20.8 UG 19306 22.2 c d e f 23.0 21.8 23.3 22.3 20.5 UG 19406 22.3 d e f 23.3 21.8 23.0 22.3 21.0 N 6404 22.4 d e f 23.0 21.3 24.5 22.5 20.5 DRI 0319 22.4 d e f 23.3 21.8 24.0 22.8 20.3 BQ 205 22.5 e f 24.5 21.3 22.8 23.0 20.8 H 9780 (STD) 22.6 f 22.8 21.5 23.8 23.5 21.3 HM 9905 22.7 f 24.3 21.8 23.5 22.8 21.0 AB 2 (STD) 22.7 f 23.8 21.5 23.8 23.3 21.0 PX 024 8 1245 23.7 g 24.3 22.3 25.3 24.8 22.0

Mean 22.2 23.2 21.4 23.3 22.5 20.6 CV 4.3 3.8 3.0 5.6 3.6 4.7 LSD 0.59 1.26 NS 1.86 1.15 NS VarXLoc LSD NS

LSD = Least significant difference at the 95% confidence level. Means followed by the same letter are not significantly different. NS = not significant. CV = coefficient of variation (%), a measure of the variability in the experiment.

California Tomato Research Institute ~ 2012 Annual Report 28

Table 4e. Fruit pH San Variety Mean of five locations Yolo Joaquin Fresno Kern Merced UG 19406 4.32 a 4.21 4.21 4.37 4.34 4.48 UG 19006 4.33 a b 4.25 4.29 4.36 4.32 4.44 AB 2 (STD) 4.34 a b c 4.29 4.26 4.30 4.37 4.46 PX 024 8 1245 4.35 a b c 4.26 4.28 4.40 4.30 4.49 AB 0311 4.36 b c d 4.33 4.30 4.27 4.41 4.51 UG 19306 4.37 c d 4.29 4.27 4.41 4.34 4.54 H 5508 4.37 c d 4.27 4.37 4.34 4.40 4.48 DRI 0319 4.38 d e 4.34 4.29 4.33 4.40 4.58 H 9780 (STD) 4.40 d e f 4.34 4.28 4.41 4.42 4.54 BQ 205 4.41 e f g 4.28 4.30 4.43 4.49 4.57 BQ 163 4.43 f g 4.33 4.39 4.41 4.45 4.56 N 6404 4.43 f g 4.42 4.35 4.35 4.47 4.56 H 5608 4.44 g h 4.43 4.44 4.38 4.39 4.58 N 6402 4.47 h i 4.47 4.43 4.34 4.50 4.63 HM 9905 4.50 i 4.42 4.44 4.46 4.54 4.63 SUN 6366 (STD) 4.51 i 4.44 4.39 4.57 4.52 4.61

MEAN 4.40 4.33 4.33 4.38 4.42 4.54 CV 1.4 1.4 1.2 1.3 1.1 1.7 LSD 0.037 0.086 0.073 0.082 0.071 0.108 VarXLoc LSD 0.083 to compare varieties at different locations

LSD = Least significant difference at the 95% confidence level. Means followed by the same letter are not significantly different. CV = coefficient of variation (%), a measure of the variability in the experiment.

California Tomato Research Institute ~ 2012 Annual Report 29

Tables 5a - 5e. Processing tomato varieties in 2012 observational trials. Observational varieties are planted in only a single plot at each location, data presented are the means of five locations.

Yield Soluble solids Variety tons/acre (°Brix) Color pH HMX 1892 50.1 (1) 4.9 (12) 23.4 (10) 4.36 (3) H 1161 48.2 (2) 5.7 (2) 23.4 (10) 4.31 (1) H 1175 46.2 (3) 5.0 (10) 21.4 (2) 4.47 (13) N 6407 45.7 (4) 5.5 (4) 22.6 (7) 4.40 (8) H 1170 44.9 (5) 5.4 (5) 22.6 (7) 4.35 (2) BQ 272 43.4 (6) 4.9 (12) 21.6 (3) 4.48 (15) HMX 1894 43.0 (7) 4.7 (14) 25.8 (15) 4.46 (12) BQ 273 42.0 (8) 4.6 (15) 22.6 (7) 4.39 (7) BQ 270 41.9 (9) 5.1 (7) 22.0 (4) 4.47 (13) N 6405 41.5 (10) 5.1 (7) 23.8 (12) 4.42 (10) BQ 268 40.6 (11) 5.8 (1) 24.0 (14) 4.36 (3) HMX1885 39.3 (12) 5.1 (7) 22.0 (4) 4.38 (5) UG 18806 37.6 (13) 5.4 (5) 23.8 (12) 4.38 (5) C 316 35.6 (14) 5.0 (10) 21.0 (1) 4.42 (10) SVR 024 9 0686 35.0 (15) 5.7 (2) 22.2 (6) 4.41 (9)

Mean 42.6 5.2 22.8 4.40

CV 19.9 9.4 7.0 1.3 LSD @ 0.05 NS 0.62 2.04 0.074

LSD = Least significant difference at the 95% confidence level. Means followed by the same letter are not significantly different. NS = not significant. CV = coefficient of variation (%), a measure of the variability in the experiment. Numbers in parentheses are the relative ranking of each variety within a column.

California Tomato Research Institute ~ 2012 Annual Report 30

Table 5a to 5d. Individual variables measured in observational varieties, 2012. Note that observational varieties were not replicated within each location, so the statistical analyses were performed only on data combined from different locations. Table 5b. Yield (tons/acre) Mean of five San Variety locations Yolo Joaquin Stanislaus Fresno Merced HMX 1892 50.1 81.9 33.7 37.5 25.8 71.5 H 1161 48.2 70.1 35.8 48.3 33.6 53.2 H 1175 46.2 66.4 35.2 22.4 25.6 81.2 N 6407 45.7 71.5 28.7 36.8 39.7 51.7 H 1170 44.9 61.4 35.2 27.3 30.7 69.8 BQ 272 43.4 66.5 25.6 41.1 28.7 55.2 HMX 1894 43.0 59.0 21.2 32.2 30.4 72.3 BQ 273 42.0 57.0 38.6 42.3 25.6 46.6 BQ 270 41.9 58.9 35.5 35.3 28.1 51.9 N 6405 41.5 66.7 34.6 21.0 33.6 51.7 BQ 268 40.6 64.9 31.9 35.1 21.9 49.2 HMX1885 39.3 64.5 26.0 25.2 14.1 66.7 UG 18806 37.6 66.3 34.8 20.5 23.8 42.6 C 316 35.6 50.8 --- 40.3 23.9 38.0 SVR 024 9 0686 35.0 47.6 32.2 32.4 23.2 39.5

Mean 42.6 63.6 32.1 33.2 27.3 56.1 CV 19.9 LSD @ 0.05 NS NS = not significant.

Table 5c. Soluble solids (°Brix) San Variety Mean of five locations Yolo Joaquin Stanislaus Fresno Merced BQ 268 5.8 a 5.5 5.4 5.7 4.9 7.4 H 1161 5.7 a b 5.1 5.3 5.4 5.4 7.2 SVR 024 9 0686 5.7 a b c 4.9 5.0 6.4 5.5 6.5 N 6407 5.5 a b c d 5.1 5.3 5.8 4.7 6.7 UG 18806 5.4 a b c d e 4.9 5.9 5.2 5.1 6.1 H 1170 5.4 a b c d e 4.6 5.0 5.8 4.9 6.5 BQ 270 5.1 b c d e f 4.9 5.0 5.0 5.0 5.8 N 6405 5.1 b c d e f 4.7 5.3 5.3 5.0 5.3 HMX 1885 5.1 c d e f 4.8 5.3 5.5 4.4 5.3 C 316 5.0 d e f 5.5 4.9 5.1 4.7 4.7 H 1175 5.0 d e f 4.2 4.8 5.0 4.1 6.8 HMX 1892 4.9 d e f 4.8 5.0 4.9 4.8 5.2 BQ 272 4.9 e f 4.2 5.7 4.8 4.5 5.3 HMX 1894 4.7 f 4.4 5.8 4.3 4.1 4.7 BQ 273 4.6 f 4.6 4.8 4.6 4.4 4.5

Mean 5.2 4.8 5.2 5.3 4.8 5.9 CV 9.4 LSD @ 0.05 0.62

California Tomato Research Institute ~ 2012 Annual Report 31 LSD = Least significant difference at the 95% confidence level. Means followed by the same letter are not significantly different. CV = coefficient of variation (%), a measure of the variability in the experiment. Table 5d. Color San Variety Mean of five locations Yolo Joaquin Stanislaus Fresno Merced C 316 21.0 a 21.0 20.0 23.0 20.0 21.0 H 1175 21.4 a b 22.0 20.0 21.0 23.0 21.0 BQ 272 21.6 a b 22.0 20.0 23.0 23.0 20.0 BQ 270 22.0 a b c 23.0 21.0 22.0 23.0 21.0 HMX1885 22.0 a b c 22.0 20.0 21.0 24.0 23.0 SVR 024 9 0686 22.2 a b c 25.0 22.0 23.0 22.0 19.0 N 6407 22.6 a b c 23.0 21.0 25.0 23.0 21.0 H 1170 22.6 a b c 23.0 21.0 23.0 23.0 23.0 BQ 273 22.6 a b c 24.0 20.0 23.0 24.0 22.0 HMX 1892 23.4 b c 23.0 22.0 26.0 22.0 24.0 H 1161 23.4 b c 23.0 22.0 28.0 24.0 20.0 N 6405 23.8 c d 24.0 22.0 27.0 23.0 23.0 UG 18806 23.8 c d 26.0 22.0 27.0 22.0 22.0 BQ 268 24.0 c d 26.0 21.0 27.0 24.0 22.0 HMX 1894 25.8 d 25.0 21.0 32.0 23.0 28.0

Mean 22.8 CV 7.0 LSD @ 0.05 2.04

Table 5e. pH of raw fruit San Variety Mean of five locations Yolo Joaquin Stanislaus Fresno Merced H 1161 4.31 a 4.30 4.21 4.23 4.37 4.42 H 1170 4.35 a b 4.25 4.28 4.22 4.45 4.53 HMX 1892 4.36 a b c 4.35 4.31 4.22 4.37 4.55 BQ 268 4.36 a b c 4.29 4.31 4.23 4.43 4.55 UG 18806 4.38 a b c 4.28 4.28 4.34 4.44 4.54 HMX1885 4.38 a b c 4.40 4.30 4.41 4.27 4.51 BQ 273 4.39 b c d 4.48 4.32 4.20 4.41 4.55 N 6407 4.40 b c d e 4.24 4.40 4.28 4.48 4.60 SVR 024 9 0686 4.41 b c d e f 4.36 4.32 4.25 4.47 4.64 C 316 4.42 b c d e f 4.40 4.43 4.33 4.41 4.52 N 6405 4.42 c d e f 4.42 4.38 4.31 4.47 4.54 HMX 1894 4.46 d e f 4.39 4.42 4.42 4.43 4.63 BQ 270 4.47 d e f 4.44 4.39 4.35 4.59 4.56 H 1175 4.47 e f 4.47 4.37 4.31 4.56 4.63 BQ 272 4.48 f 4.53 4.34 4.41 4.51 4.61

Mean 4.40 CV 1.3 LSD @ 0.05 0.074

LSD = Least significant difference at the 95% confidence level. Means followed by the same letter are not significantly different. CV = coefficient of variation (%), a measure of the variability in the experiment.

California Tomato Research Institute ~ 2012 Annual Report 32 Roger Chetelat, Director/Curator C. M. Rick Phone: (209) 385-7403 Dept. of Plant Sciences University of California T G R C Davis, CA 95616 [email protected] Tomato Genetics Resource Center http://tgrc.ucdavis.edu

ANNUAL PROGRESS REPORT

2012

Figure 1. Inflorescence of S. habrochaites LA1986. The TGRC regenerated this year a number of wild species accessions which had been stored in our seed vault but had never been grown for seed increase. Several new and interesting items were discovered. The image above is of an accession of S. habrochaites collected by Charley Rick and Jon Fobes in 1979 near Casmiche, Rio Moche, Peru. [photo by S. Peacock] California Tomato Research Institute ~ 2012 Annual Report 33 SUMMARY Acquisitions. Six new accessions of cultivated tomato were acquired from Muriel Quinet at the Univ. Catholique de Louvain, in Belgium. These new stocks are double or triple mutant combinations of uniflora (uf), blind (bl), compound inflorescence (s), jointless (j), and self-pruning (sp). These stocks should be useful for genetic studies of meristem, flower and inflorescence development. In addition, we regenerated 34 previously inactive accessions of wild species, most of which had never been grown before, representing a significant expansion of our wild species collection at a time when opportunities for new germplasm collections are limited and many wild tomatoes have disappeared in situ. The current total of number of active accessions is 3,652. Maintenance and Evaluation. A total of 971 cultures were grown for various purposes, of which 270 were for seed increase (136 of which were of wild species) and 204 for germination tests. 63 stocks were grown for progeny tests of selected mutants that are maintained via heterozygotes, such as recessive lethals, nutritional disorders, and male-sterilities. 13 stocks were grown to test for the presence of transgenes (none were found). Other stocks were genotyped to confirm wild species introgressions. Newly regenerated seed lots were split, with one portion stored at 5° C (our working collection, used for filling seed requests), the other at -18° C for extended longevity. Backup seed samples were also submitted to the USDA Natl. Center for Genetic Resources Preservation in Colorado, and to the Svalbard Global Seed Vault. Distribution and Utilization. The TGRC distributed 4,966 seed samples of 1,931 different accessions in response to 273 requests from 200 colleagues in 23 countries. At least 25 purely informational requests were also answered. The overall utilization rate (i.e. number of samples distributed relative to the number of active accessions) exceeded 135%. These statistics show that our collection continues to be intensively used and that demand for our stocks remains high. Information provided by requestors indicates our stocks are used for a wide variety of research and breeding projects. Our annual literature search again uncovered a large number of publications mentioning use of our stocks (see bibliography). Documentation. Our website was updated in various ways to improve usability. Queries of wild species accessions can now be viewed in a datasheet format, in addition to a form view. The underlying data records can be downloaded to a spreadsheet, and groups of related accessions can be plotted on GoogleMaps. In addition, our web- based query pages were rewritten to meet enhanced security standards in our web server environment. We finished digitizing Charley Rick’s field notebooks from his collecting trips to South America. Containing the records of 15 trips to Peru, Ecuador and Chile made between 1948 and 1995, these notebooks are a trove of information about the wild species accessions, including directions to collection sites, general habitat, likely stress tolerances, disease symptoms, morphological traits, genetic variability, degree of cross pollination, and other details. Research. We continue to study the mechanisms of interspecific reproductive barriers that prevent certain crosses between cultivated and wild tomatoes. We discovered that the pollen factor ui6.1 functions in self- as well as interspecific incompatibility. We also advanced breeding lines representing the genome of S. sitiens in cultivated tomato, with the goal of developing a set of introgression lines for this wild species. Molecular marker analysis of early backcross generations (BC2-BC3) indicated that roughly 80% of the S. sitiens genome has been captured so far.

California Tomato Research Institute ~ 2012 Annual Report 34 ACQUISITIONS The TGRC acquired six new accessions, all of cultivated tomato, during 2012. The new stocks were various double and triple mutant stocks of genes affecting shoot growth and inflorescence or flower development. The genes involved and their phenotypes are as follows: uniflora (uf) produces inflorescences with reduced numbers of flowers (usually a single flower); blind (bl) causes shoot growth to terminate after a very limited number of leaves and flower clusters (usually just one) are produced; compound inflorescence (s) produces highly subdivided inflorescences with a greatly increased number of flowers; jointless (j) eliminates the normal pedicel abscission zone (joint) in the flower; and self-pruning (sp) causes determinate growth habit. The two- or three-gene combination stocks were synthesized by Prof. Muriel Quinet at the Univ. Catholique de Louvain, in Belgium. We expect these stocks will be useful for genetic studies of meristem, flower and inflorescence development. More detailed information on these new accessions can be found on our website at http://tgrc.ucdavis.edu/acq.aspx. We made a major effort this year to regenerate a large number of previously inactive wild species accessions. These stocks had not been grown since they were acquired by the TGRC, either because they were judged to be redundant with other accessions from similar geographic regions, or because space and resources at the time were limiting. Many of these had been stored in our seed vault since the 1980’s or earlier. Thus germination rates for some seed lots were low and viable populations were obtained from only 34 accessions. The main motivation for rescuing these old collections from our vault is that obtaining permission to conduct new collections in the native region has become impractical or impossible. Since the 1992 Convention on Biological Diversity, plant collecting activities have been curtailed in many countries. Another consideration is that wild tomato populations are not being protected in situ, and many previous collections have disappeared. For example, during a trip to Peru in 2009 we observed very few wild tomatoes growing in the agricultural valleys. This genetic erosion was especially severe in the northern half of Peru, and at elevations below 1000 m elevation, a zone where S. pimpinellifolium once flourished and exhibited its highest genetic diversity. In light of these trends, there is an urgent need to regenerate the available ex situ collections while they still have adequate seed viability. Among the 34 inactive accessions we grew this year, there were a number of interesting items. S. habrochaites LA1986 produced extremely vigorous plants with unusually large, showy flowers and fruit up to 2.5 cm in diameter (Figures 1, 2). LA1986 represents only our second collection of this species from the upper Rio Moche (the other accessions are from lower elevations). Another S. habrochaites collection, LA2868, represents our first accession from El Oro province in Ecuador. We also revived a collection of S. pennellii (LA1773) from the Rio Casma, one of only a handful from that region of Peru. Flowers of LA1773 have their pedicel joint in the ‘mid’ position, unlike nearly all other accessions of S. pennellii which show a basal articulation. S. chilense LA1931 is a noteworthy new accession from the Rio Acari drainage, an Figure 2. Fruit of S. habrochaites LA1986. area where relatively few wild tomato populations are known. The Acari drainage is the northernmost boundary of the natural geographic range of S. chilense, and populations there are morphologically and genetically distinguishable from populations in the center of the

California Tomato Research Institute ~ 2012 Annual Report 35 distribution. A newly regenerated accession of S. huaylasense, LA1979, provides additional representation ex situ for a species that has a limited geographic distribution with relatively few known populations. Finally, we regenerated a large number of inactive S. pimpinellifolium accessions from northern Peru. Many of these were from previously uncollected locations, and most were the large-flowered, facultatively outcrossing type, and thus likely to be genetically diverse.

Table 1. Number of accessions of each species maintained by the TGRC. Totals include accessions that are temporarily unavailable during seed regeneration. Solanum name Lycopersicon equivalent No. of Accessions S. lycopersicum L. esculentum, including var. cerasiforme 2,652 S. pimpinellifolium L. pimpinellifolium 311 S. cheesmaniae L. cheesmanii 41 S. galapagense L. cheesmanii f. minor 29 S. chmielewskii L. chmielewskii 27 S. neorickii L. parviflorum 52 S. arcanum L. peruvianum, including f. humifusum 47 S. peruvianum L. peruvianum 78 S. huaylasense L. peruvianum 18 S. corneliomulleri L. peruvianum, including f. glandulosum 53 S. chilense L. chilense 114 S. habrochaites L. hirsutum, including f. glabratum 123 S. pennellii L. pennellii, including var. puberulum 52 S. lycopersicoides n/a 24 S. sitiens n/a 13 S. juglandifolium n/a 6 S. ochranthum n/a 9 Interspecific hybrids n/a 2 Total 3,652

Certain obsolete, erroneous, or redundant stocks were de-accessioned and will no longer be maintained. These included stocks that lacked the correct phenotype and could not be rescued from older seed lots. As in previous years, we continue to prune our collection of multiple marker stocks to a more reasonable number, discarding in some cases those genotypes for which each mutation is available in other, more useful or more easily maintained lines. This year we dropped a fairly large group of multiple marker stocks which had been donated by Dr. Aleksandr Kuzemenskiy, but which lacked sufficient documentation. The total number of accessions maintained by the TGRC is now 3,652 (Table 1).

MAINTENANCE Under the guidance of Peter March and Scott Peacock, our crew of undergraduate student assistants again managed large field and greenhouse plantings this year. A total of 971 families were grown for various purposes; 270 of these were for seed increase, including 136 of wild species accessions, most of which required greenhouse culture. The rest were grown for germination tests, evaluation, introgression of the S. sitiens genome, research, or other purposes. 13 stocks were tested for the presence of transgenes, and all tests were negative. Identifying accessions in need of regeneration begins with seed germination testing. Seed lots with a germination rate that fails to meet our threshold of 80% are normally California Tomato Research Institute ~ 2012 Annual Report 36 regenerated in the same year. Other factors, such as available space, age of seed and supply on hand, are also taken into account. Newly acquired accessions are typically regenerated in the first year or so after acquisition because seed supplies are limited and of uncertain viability. This year, 204 seed lots were tested for germination responses. Average germination rates continued to be relatively high (Table 2), indicating conditions in our seed vault are satisfactory. For accessions grown in the field, the usual sequential plantings were made to spread out the work load. Seedlings were transplanted in the field on four separate dates, the first on April 25th, for a total of 34 field rows. Early growth and establishment were favorable, except for a worse than usual incidence of curly top virus (CTV). Conditions in the field were relatively mild and nearly ideal for fruit set, with only a few periods of excessive temperatures, during which manual pollinations were suspended. The male-steriles and other lines with low fruit set were intensively pollinated by the crew, resulting in adequate seed yields in most cases. We grew 3 male-sterile groups this year to produce adequate seed of F2 (ms/+ x self) or BC (ms/ms x ms/+) generations. Many others were grown for progeny testing of male-sterile seed lots produced in previous years. Stocks that failed to produce sufficient seed under field conditions will be repeated in the greenhouse. Table 2. Results of seed germination tests of wild species accessions. Values are based on samples of 50-100 seeds per accession, and represent the % germination after 14 days at 25°C. Seed lots with a low germination rate are defined as those with less than 80% germination. Date of # Tested Avg % # Low # SoSolanum Species Lots Germ. Tested Germ Growna S. cheesmaniae, S. 2001 76 5 2 4 galapagense S. chilense 1997- 90 6 1 5 2001 S. chmielewskii, S. 1991- 99 11 0 6 neorickii 1999 S. habrochaites 1982- 97 50 1 6 2002 S. lycopersicoides - - - - 1 S. pennellii 1997- 93 4 0 6 1999 S. peruvianum clade 1981- 87 78 11 13 2002 S. pimpinellifolium 1997- 95 19 1 9 2002 S. sitiens 1989 98 1 0 0 S. juglandifolium 1 1 1 S. ochranthum 1996- 80 3 0 1 2000 a Includes all accessions grown for seed increase in the 2012 pedigree year, whether for low germ or for other reasons. For various reasons, many of the wild species, mutants and certain other genetic stocks require greenhouse culture. For the mutant stocks, we start the weakest lines first, and finish with lines of normal vigor. We now grow most of the introgression lines in the greenhouse, both to assure adequate seed set (some are partially sterile in the field) and to reduce the risk of

California Tomato Research Institute ~ 2012 Annual Report 37 outcrossing. For the wild species, plantings in the greenhouse are based on daylength response: those with the least sensitivity are planted first; next, those with intermediate reaction; last, the most sensitive (i.e. flower best under short days). Optimal planting dates for each species are listed on our website, at http://tgrc.ucdavis.edu/spprecommed.html. This year we grew a number of S. habrochaites accessions in the field for experimental crosses. These are normally grown for seed multiplication in the greenhouse because they are self-incompatible (obligate outcrossers), and therefore vulnerable to insect cross pollination outdoors. Furthermore, they are daylength sensitive, and do not flower well in the greenhouse during the summer. The material we grew in the field, on the other hand, flowered strongly throughout summer and most set abundant fruit (Figure 3). The accessions from Ecuador did better than ones from southern Peru. Therefore, S. habrochaites could be grown in the field for seed multiplication, provided that isolation cages are used. Figure 3. S. habrochaites growing in the field (L) and S. juglandifolium in the greenhouse (R). [photos J. Petersen, S. Peacock] Our greenhouse plantings were relatively trouble-free this year, except for recurring infestations of thrips. We continue to search for a good method for inducing S. juglandifolium and S. ochranthum to flower and set seed (Figure 3). This year we had some success growing S. juglandifolium plants in very small pots; they quickly became pot bound and growth was limited, but the flowering response was stronger. As in the past, we continue to store samples of all newly regenerated seed lots in our seed vault at 5-7°C; this is our ‘working’ collection, used for filling seed requests. In addition, we package seed samples of each accession in sealed foil pouches for storage at -18°C in order to extend seed longevity and reduce the number of regeneration cycles. As in the past, large samples of newly regenerated seed lots were sent to the USDA-NCGRP in Ft. Collins, Colorado, for long-term backup storage. This year, 70 accessions were sent to NCGRP, and 165 to the Svalbard Global Seed Vault in Norway.

EVALUATION All stocks grown for seed increase or other purposes are systematically examined and observations recorded. Older accessions are checked to ensure that they have the correct phenotypes. New accessions are evaluated in greater detail, with the descriptors depending upon type of accession (wild species, cultivar, mutant, chromosomal stocks, etc.). In the case of new wild species accessions, plantings are reviewed at different growth stages to observe foliage,

California Tomato Research Institute ~ 2012 Annual Report 38 habit, flower morphology, mating system, and fruit morphology. We also record the extent of variation for morphological traits, and in some cases assay genetic variation with markers. Such observations may reveal traits that were not seen at the time of collection, either because plants were not flowering or were in such poor condition that not all traits were evident, or because certain traits were overlooked by the collector. Many genetic stocks, including various sterilities, nutritional, and weak mutants, cannot be maintained in true-breeding condition, hence have to be transmitted from heterozygotes. Progeny tests must therefore be made to verify that individual seed lots segregate for the gene in question. This year we performed progeny tests on 63 seed lots to confirm the segregation of specific markers or to resolve segregation problems. The tested stocks included several male- steriles mutants, thiamineless (tl), and mortalis (mts). We also initiated allele tests of a provisional mutant that exhibits purplish leaves and dark anthers by crossing to two anthocyanin enhancer mutants, Anthocyanin fruit (Aft) and atroviolacium (atv). Stocks grown for observation included the accessions of S. lycopersicum that form part of the SolCAP core collection.

DISTRIBUTION AND UTILIZATION The TGRC again filled a very large number of seed requests this year. A total of 4,966 seed samples representing 1,931 different accessions were sent in response to 273 seed requests from 200 investigators in 23 countries. In addition, at least 25 purely informational requests were answered. Relative to the size of the TGRC collection, the number of seed samples distributed was equivalent to a utilization rate of approx. 136% -- a high level of use for any genebank, and proof that demand for our stocks remains high. The various steps involved in filling seed requests – selecting accessions, packaging seeds, entering the information into our database, providing cultural recommendations, obtaining phytosanitary certificates and import permits, etc – involve a large time commitment. Led by Alison Gerken and Jennifer Petersen, the TGRC crew did a splendid job filling requests promptly and accurately. The online payment system we implemented last year to recover the costs of phytosanitary certificates continues to function well, allowing us to keep up with the rising cost of phytos (USDA-APHIS raised their prices again this year). Many countries are increasing the stringency of their import regulations, and obtaining the necessary phytosanitary certificates and/or import permits is becoming more onerous and time consuming. For instance, Japan now requires an import permit for some tomato species but not for others, so shipments need to be split, with different sets of documents accompanying each group of seed samples. We can no longer ship seed to countries in the E.U. zone unless the requestor provides a letter of authorization with the appropriate phytosanitary exemptions. Information provided by recipients regarding intended uses of our stocks is summarized below (Table 3). Breeding for resistance to various diseases and/or investigations of the molecular biology of host-pathogen interactions were major areas of research interest, as in previous years. In particular, many requests mentioned research or breeding related to begomoviruses, bacterial speck or late blight. Research on responses to abiotic stresses emphasized salinity and low temperature stresses this year. In the area of fruit quality, there seems to be less interest in carotenoids and greater focus on fruit flavor than in the past. There continues to be high demand for studies of rootstocks and grafting. Many requests for genetic research now mention gene expression and/or evolutionary studies. Other research topics accounting for many requests were: interspecific reproductive barriers, flower and inflorescence development, the soil microbial community, wounding responses, and metabolites. We also

California Tomato Research Institute ~ 2012 Annual Report 39 received a large number of requests for educational / instructional uses, and one request for an archeological study. As in the past, we received a large number of requests for unspecified breeding or research purposes, particularly from users in the private sector. There continues to be high demand for introgression lines (ILs) -- stocks containing a defined wild species chromosome segment in the background of cultivated tomato -- as they offer many advantages for breeding and research. A total of 23 requests and 255 seed samples were processed for the S. pennellii ILs, 21 requests and 446 samples for the S. habrochaites ILs, and 13 requests and 149 samples for the S. lycopersicoides ILs. The relatively high demand for the S. habrochaites ILs this year was noteworthy. Table 3. Intended uses of TGRC stocks as reported by requestors. Values represent the total number of requests in each category. Requests addressing multiple topics may be counted more than once. Category # Requests Category # Requests Biotic Stresses Unspecified insects 1 Viruses: Unspecified biotic stresses 7 PepMV 1 TBSV 1 Abiotic Stresses ToMV 3 Drought 6 TSWV and other tospoviruses 2 High temperatures 3 TYLCV and other begomoviruses 6 Low temperatures 7 Viroids 1 P-efficiency 1 Bacteria: Salinity 10 Bacterial canker 1 Shade 1 Bacterial speck 6 Unspecified abiotic stresses 5 Bacterial spot 1 Bacterial wilt 2 Fruit Traits Septoria 1 Anthocyanins and antioxidants 2 Zebra complex 1 Cuticle/wax properties 2 Unspecified bacteria 2 Development and ripening 3 Fungi: Flavor, volatiles 4 Cladosporium 2 Food safety 1 Early blight 2 Nutritional quality 1 Fusarium wilt 1 Postharvest and shelf life 3 Late blight 5 Quality 1 Powdery mildew 1 Size and shape 2 Southern blight 1 Sugars 1 Verticillium wilt 1 Tomatine 1 Unspecified fungi 1 Nematodes: Miscellaneous Breeding Pale cyst nematode 3 Heterosis, yield 1 Root knot nematode 3 Grafting, rootstocks 7 Unspecified nematodes 1 Haploids 1 Unspecified diseases 11 Home garden cultivars 2 Insects: Marker assisted selection 1 Aphids 3 Marker development 2 Bemisia 2 Ornamentals 1 Bollworms 1 Prebreeding 2 Mites 1 Wild species introgressions 1 Thrips 1 Yield 1

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Category # Requests Category # Requests Unspecified breeding uses 26 ABA responses 1 Abscission 4 Genetic Studies Acyl-sugars 4 Association mapping 3 Flower, inflorescence development 5 Biosystematics 2 Flowering time 2 Centromeres 1 Gibberellin responses 1 Diversity studies 3 Hormone responses 1 Double mutants 1 Metabolites, metabolomics 6 Evolution and domestication 4 Mycorrhizae, rhizosphere 5 Functional genomics 4 Photomorphogenesis, photosynthesis 1 Gene cloning 1 Pollination biology 1 Gene expression / transcriptomics 6 Reproductive barriers, mating systems 12 Gene silencing 2 Root biology and architecture 7 Mapping 2 Seed development, germination 1 Phenotyping 1 Trichomes, volatiles, exudates 3 Population genetics 3 Wounding, defense signaling 5 Recombination, segregation 2 Unspecified physiological studies 2 Sequencing 2 SNP genotyping 1 Miscellaneous TILLING 1 Horticultural studies 2 Transformation 1 Archaeological studies 1 Unspecified genetic, genomic studies 5 Instructional uses 7 Unspecified research 23 Physiology & Development Unspecified uses 8

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Our survey of the 2012 literature (and unreviewed papers of previous years) again uncovered a large number of publications, including journal articles, reports, abstracts, theses, patents, etc., that mention use of TGRC stocks (see bibliography). Many references were undoubtedly missed, and cases of utilization by the private sector are generally not publicized. This publication record demonstrates the important role of the TGRC as a research resource, and its positive impact on many fields of investigation. The value of the collection for improving the tomato crop is shown by the many publications that address economic traits.

DOCUMENTATION Various modifications and enhancements were made to our database and website by Tom Starbuck. Our website (http://tgrc.ucdavis.edu) was updated in various ways to improve usability. Queries related to wild species accessions can now be viewed in a datasheet (tabular) format, in addition to a form view. The underlying data records can now be downloaded to a spreadsheet file, including all the fields that make up the essential ‘passport’ data on each accession. Groups of related accessions can now be displayed using an imbedded GoogleMap function. For example, one can plot the locations of all accessions of a species, or view all the collections of any species from a particular country or province. Clicking on individual accessions brings up all the accession details. In addition, many of our web-based query pages were rewritten to meet enhanced security standards in our web server environment. Our database was modified in various ways to further improve internal record keeping. We also finished our project to digitize the information contained in Charley Rick’s field notebooks from his collecting trips to South America. These notebooks represent the records of 15 trips to Peru, Ecuador and Chile, made by Dr. Rick and his associates between 1948 and 1995. They contain potentially useful information about our wild species accessions, including the locations of populations, local habitat characteristics, probable abiotic stress tolerances, disease symptoms, plant growth type, evidence of cross pollination, fruit shape and color, extent of genetic variability, indigenous plant names and medicinal uses, etc. During this process we used GoogleEarth to translate the relatively detailed collection site information (e.g. “50 Km East of Panamerican highway on the road to Cajamarca”) into more accurate and precise latitude and longitude coordinates for each accession (all were collected pre-GPS). As usual, our annual distribution records were provided to the USDA for incorporation into the GRIN database. We also issued a revised list of miscellaneous genetic stocks, which is available on our website and will be published in the Tomato Genetics Coop. Report (TGC), volume 62. RESEARCH In addition to the core genebank functions described above, the TGRC conducts research synergistic with the overall mission of the Center. Our current research focuses on the genetics of interspecific reproductive barriers. Wentao Li continued his study of pollen factors involved in unilateral incompatibility (UI), i.e. interspecific crosses that are compatible in one direction but incompatible when the pollen and pistil parents are reversed. He previously isolated the ui6.1 gene, one of two pollen factors from S. pennellii (the other is ui1.1) that are required for pollen to overcome UI on pistils of interspecific hybrids. More recently, he demonstrated that ui6.1 is also required for the expression of self-incompatibility (many of the wild species are self- incompatible). Jennifer Petersen is searching for natural variation in ui1.1 and ui6.1 among the

California Tomato Research Institute ~ 2012 Annual Report 42

green-fruited self-compatible species. She is also uncovering evidence of additional pollen factors in certain of her wide crosses. Another TGRC research project is to advance breeding lines representing the S. sitiens genome in the background of cultivated tomato, with the goal of developing a set of introgression lines for this wild species. Visiting scientist Yosuke Moritama genotyped a sample of early backcross generation lines (BC2-BC3) using DNA markers, and found that roughly 80% of the S. sitiens genome has been captured in these lines. They are still at a very early stage and more backcrosses and marker aided selection will be needed to recover a uniform cultivated tomato genome and to obtain lines with a single chromosome segment from S. sitiens. In addition, the missing genomic regions need to be recovered, and the overlap between adjacent chromosome segments in different lines verified.

PUBLICATIONS Chetelat, R. T. (2012) Revised list of miscellaneous stocks. Tomato Genetics Coop. Rep. 62. Powell, A. L. T., C. V. Nguyen, et al. (2012) Uniform ripening encodes a Golden2-like transcription factor regulating tomato fruit development. Science 336: 1711-1715. S.C. Sim, A. VanDeynze et al. (2012) High-density SNP genotyping of tomato (Solanum lycopersicum L.) reveals patterns of genetic variation due to breeding. PLoSONE 7(9): e45520. doi:10.1371/journal.pone.0045520.

SERVICE AND OUTREACH Presentations. Lectures, seminars and other presentations on the TGRC, our research projects, and related topics were given to the following groups: • presentation to Yolo County Master Gardeners. • seminar in the Plant and Microbial Biology Dept., UC-Berkeley • lecture to UCD class on Plant Conservation Genetics (ENH150) • presentation Seed Central group • presentation at the Plant and Animal Genome Conference, San Diego • presentation to the International Conference on Genetic Improvement for Crop Development, Santiago, Chile Press Coverage. Articles or videos mentioning or featuring the TGRC appeared in the following media sources: • Interview with NPR for How the Taste of Tomatoes Went Bad (and Kept on Going) • Interview with KQED radio for Building a Better, Tastier Tomato. • Interview with Rocky Mountain Collegian for Colorado State professor makes strides in flowering plant research. • Interview with Nancy Stamp, Binghampton University, SUNY. • Interview with Organic Gardening magazine. Visitors. Individuals from the following institutions visited the TGRC: • Juan Carlos Brevis, Enza Zaden Seed Company • Steven Loewen, University of Guelph, Canada • Suchila Techawongstien, Khon Kaen University, Thailand • George Kotch, Seed Biotechnology Center • William Reinert, Morning Star Co. • Elena Albrecht, Keygene

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PERSONNEL AND FACILITIES The TGRC lost two highly qualified and experienced staff members this year when Peter March and Alison Gerken resigned to pursue their interests in dentistry and veterinary medicine, respectively. They were replaced by Scott Peacock and Jennifer Petersen, both former members of the TGRC and exceptionally well qualified. Scott worked for Arcadia Biosciences in Davis after graduating and before returning to the TGRC. Jennifer completed her Ph.D. in Dan Potter’s lab and now works part time at the TGRC answering seed requests; she also works in the lab studying evolutionary aspects of interspecific reproductive barriers. Wentao Li continued his research on the molecular genetics of intra- and interspecific incompatibility. Yosuke Moritama from Sakata Seeds was a visiting scientist for 6 months and gave our S. sitiens introgression project a real boost by genotyping a large number of lines. Undergraduate students Samantha Melendy and Daniel Short assisted with greenhouse, field and seed lab operations at the TGRC. Christine Nguyen was a student intern. Tom Starbuck continues to maintain our database and website. Many thanks to each of these individuals for contributing to the success of our Center!

FINANCIAL SUPPORT We gratefully acknowledge receiving financial support from the following institutions this year. California Tomato Research Institute National Science Foundation Nunhems USA, Inc. UC-Davis Department of Plant Sciences UC-Davis College of Agricultural and Environmental Sciences USDA-ARS National Plant Germplasm System USDA-ARS Solanaceae Coordinated Agricultural Project

TESTIMONIALS “I think the TGRC is doing a really great job as a resource center for tomato research.” -- Maria Ivanchenko, Oregon State University “Nice website.” -- Hakan Aktas, UC Davis “Thank you for your cooperation and support to researchers all over the world.” -- Hisham Hussain, University Technology of Malaysia “The germplasm you maintain is a remarkable resource, and, of course, many of us wish we could have worked alongside Dr. Rick.” -- Lee Goodwin, J&L Gardens, Espanola, New Mexico “I greatly appreciate that this project in scientific solidarity exists.” -- Juan Sebastián Schneider, Argentina “It is an opportunity to say how important is your work for the breeders community, thanks!” -- Ari Efrati, Rootability, Israel

BIBLIOGRAPHY (Please see online version of this report, available at http://tgrc.ucdavis.edu/reports.aspx).

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Project Title: Tomato Powdery Mildew Control

Project Leader: Brenna Aegerter Farm Advisor University of California Cooperative Extension, San Joaquin County 2101 E. Earhart Ave., Ste. 200, Stockton, CA 95206 Phone: 209-953-6114 FAX: 209-953-6128 Email: [email protected]

Co-Investigators: Scott Stoddard Farm Advisor, UCCE Merced and Madera Co. 2145 Wardrobe Ave., Merced, CA 95340

Gene Miyao Farm Advisor, UCCE Yolo, Solano, and Sacramento Co. 70 Cottonwood St., Woodland, CA 95695 Phone: (530) 666-8732

Tom Turini Farm Advisor, UCCE Fresno Co. 1720 S. Maple Ave., Fresno, CA 93702 Phone: (559) 456-7157

Michelle Le Strange Farm Advisor, UCCE Tulare and Kings Co. 4437 S. Laspina St., Suite B, Tulare, CA 93274 Phone: (559) 685-3309 , Ext. 220

Summary: This was the final year of a four-year project looking at the impact of powdery mildew on processing tomatoes and evaluating control programs. These past three seasons there has been lighter disease pressure from powdery mildew in commercial fields than we had observed during the 2007 to 2009 seasons. In our 2012 trial fields, there was a moderate level of powdery mildew by mid-September at two of the four trial locations. Out of all eighteen trials over four years, ten developed significant mildew. From these, we conclude that the fungicide programs evaluated have the potential to increase soluble solids (observed in 9 out 10 trials), increase yield (2 out of 10 trials), reduce sunburning of fruit (5 out of 10 trials), improve fruit color (5 out of 10 trials), and lower fruit pH (2 out of 10 trials). The impact likely depends on a number of factors such as disease pressure, onset date, crop variety, and weather. Best control programs were those which included sulfur dust, and programs beginning 6 to 8 weeks after transplanting were generally more effective than programs starting later.

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Objective: To evaluate fungicide spray programs for their impact on powdery mildew control, fruit yield, and fruit quality.

Procedures: Four powdery mildew control trials were conducted in processing tomatoes in 2012. Two trials were located within commercial fields (north Dos Palos-area, Merced Co. and Union Island, San Joaquin Co.), while another two were conducted at the UC West Side Research and Extension Center near Five Points (Fresno Co.) and at the Plant Sciences field facility at UC Davis (Yolo County). Trials were established in fields transplanted in mid-May, three were in fields of the variety SUN 6366 or 6368, while one was H 9780 At each location, a minimum of eight treatments/control programs were evaluated. At most locations, additional treatments were evaluated. Four of the treatments were variations on a spray program of a strobilurin + DMI fungicide (azoxystrobin + difenoconazole = Quadris Top @ 8 oz per acre) rotated with sulfur dust (40 or 50 lbs per acre depending on the trial and treatment). These four programs varied in the timing of the applications (i.e. varying intervals and treatment start dates). Other treatments evaluated sulfur alone either as a dust or wettable sulfur formulation (10 to 20 lbs per acre depending on trial location). The eighth treatment was a nontreated control. Most trials also included other fungicides programs or experimental materials, but these varied by location and were supported with other funding sources, therefore we have not attempted to report on these treatments here, but you may obtain findings from individual advisors. Spray program details for each trial are listed in Table 1. Fungicides were applied with a backpack sprayer operating at 32 to 40 psi and a hand-held boom. Spray volumes were equivalent to 50 gallons water per acre. Sulfur dust was applied with a hand-crank operated duster. Plots consisted of a single bed and were 40 to 75 feet in length. Each plot was replicated four times at each location, in a randomized complete block design. There were non-treated buffer rows between each treatment row and between the trial rows and the rest of the field. Plots were evaluated for powdery mildew severity, foliar necrosis severity, marketable yield, sunburn damage, and fruit quality as determined by analysis by PTAB grading station staff. Results of each trial are reported separately due to differences in control programs and powdery mildew pressure between trial locations (see table 1 for trial details and control program/treatment descriptions).

Results: At the trial located on the UCD campus, powdery mildew infection occurred in mid-August, just over one month before harvest. Within two weeks, the disease had increased to a moderately high level (76% incidence), resulting in leaf drying. All treatments held up relatively well; the best programs were sulfur dust on a 7- or 14-day schedule, or sulfur dust alternated with Quadris Top on a 7-day schedule. Each of these three programs reduced disease incidence down to 13% (from 79% in the non-treated control). There were no statistically significant differences in yield (either total fruit or marketable fruit), but there were differences in fruit quality between groups. Fungicides as a group reduced sunburned fruit from 7.7% (% of affected fruit by weight) down to 5.6%. Soluble solids were increased to 5.7 °Brix in the fungicide-treated plots, up from 4.95 °Brix in the non-treated control. And raw fruit color was improved from 23.8 to 22.7. All results from the Yolo trial are presented in Table 2.

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At the Fresno County location (UC WSREC, Five Points), powdery mildew reached detectable levels by the end of July and increased slowly during the season. By August 20th, one month prior to harvest, the disease was still at a low level of 2 to 3% of the foliage affected in non- fungicide-treated plots. By September 10th, this level had increased to around 25% of the foliage affected. All fungicide programs held up well under these conditions; with fungicide treatments on average reducing disease to below 1% of the foliage affected (from ~25% in the non-treated). The best programs were those which included sulfur dust; wettable sulfur was not as effective as dust, although it still provided a commercial level of control. Fruit yield and quality was significantly impacted by the powdery mildew. Fungicide-treated plots had higher yield (20% higher than non-treated), improved soluble solids (6.76 vs. 6.13 °Brix), and slightly better color and pH. The incidence of sunburned fruit was also reduced slightly by the fungicide programs. All results from the Frenso trial are presented in Table 3.

At the San Joaquin County location (Union Island, north of Tracy, Steve Arnaudo), no powdery mildew was observed. There were no differences in fruit quality (PTAB measurements) and three blocks of the trial were harvested with no apparent yield differences between treatments.

At the Merced County location (north-Dos Palos-area, Nickels Farming, San Juan Ranch), there was a detectable but very low level of powdery mildew. There were no significant effects of the fungicide programs on disease, yield (two blocks harvested) nor on fruit quality as indicated by PTAB measurements.

Final Project Summary: Over a four-year period, our group conducted eighteen field trials funded by CTRI with additional treatments and trial locations conducted with the support of the chemical manufacturers. Out of the eighteen trials, ten trial locations developed powdery mildew to a sufficient extent to provide meaningful results.

Figures 1 a though f summarize some of our results from over the four years of trials. At all ten locations with powdery mildew, we are able to significantly reduce the level of mildew and necrosis with our fungicide programs (Fig. 1a). In general the most effective programs were those which included sulfur dust, wettable sulfur was somewhat less effective. Programs in which applications started early (at 6 to 8 weeks after transplanting) tended to be more effective than those program which started later (10 to 12 weeks after transplanting). In two trials, we saw a yield increase attributable to controlling the mildew (Fig. 1b), in both cases the disease got started in these fields in July, more than one month prior to harvest. At all other locations, we did not detect yield differences between treatments. The proportion of fruit exhibiting sunburn tends to be highly variable and therefore it can be hard to draw conclusions about treatment effects; however at five of the ten locations a significant impact of fungicides on sunburn was documented (Fog. 1c). Over the four years of trials, soluble solids increases due to mildew control were observed in nine out of ten trials where mildew was present (Fig. 1d). The average soluble solids increase from the weekly sulfur program was 0.6 °Brix (increase ranged from 0.07 to 1.38 °Brix). Color was improved in the fungicide-treated plots at half of the trial locations, and pH was improved at only two locations (Figs 1f and 1e, respectively).

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Many thanks to our grower cooperators for their generosity and assistance on this project: Dan Burns& Nickels Farming Hal Robertson Farms Dino Del Carlo & Double D Farms Steve Arnaudo John Bacchetti & Del Terra Farms Timothy & Viguie Button & Turkovich Ranches UC West Side Research & Extension Center staff UC Davis Plant Sciences field facility staff

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Fresno (UC WSREC/Five Points) Table 1. Programs evaluated, trial details Yolo (UC Davis) trial trial San Joaquin (Union Island) trial Merced (Dos Palos-area) trial Variety SUN 6366 SUN 6366 H 9780 N 6385 transplant date 26-May 13-May 16-May 15-May harvest date 20-Sep 19-Sep 27-Sept 25-Sep program 1: Quadris Top alternated w/ sulfur 7 applications; 7/15 to 9/3 11 applications; 6/27 to 9/4 9 applications; 7/11 to 9/5 8 applications; 7/5 to 9/10 dust, 7-day interval program 2: Quadris Top alternated w/ sulfur 4 applications; 7/15 to 8/27 6 applications, 6/27 to 9/4 5 applications, 7/11 to 9/5 4 applications; 7/5 to 8/27 dust, 14-day interval program 3: Quadris Top alternated w/ sulfur 4 applications; 8/13 to 9/3 6 applications, 8/1 to 9/4 5 applications, 8/8 to 9/5 4 applications, 8/13 to 9/10 dust, 7-day interval, delayed start program 4: Quadris Top alternated w/ sulfur 5 applications; 7/15 to 8/13 5 applications, 6/27 to 7/25 5 applications, 7/11 to 8/8 5 applications; 7/5 to 8/13 dust, 7-day interval, early stop

program 5; sulfur dust, 7 day interval 7 applications; 7/15 to 9/3 11 applications; 6/27 to 9/4 9 applications; 7/11 to 9/5 8 applications; 7/5 to 9/10

program 6: sulfur dust, 14-day interval 4 applications; 7/15 to 8/27 6 applications, 6/27 to 9/4 5 applications, 7/11 to 9/5 4 applications; 7/5 to 8/27

program 7 sulfur wettable, 14-day interval 4 applications; 7/15 to 8/27 6 applications, 6/27 to 9/4 5 applications, 7/11 to 9/5 4 applications; 7/5 to 8/27

program 8: Non-treated control none none none none

6 other programs incl. grower std: 2 Other programs evaluated with other funding various experimental materials sulfur fb. Luna fb. Quadris Top fb. sulfur dust at half rate of program sulfur dusts fb 2 Cabrio; sources, varies with the trial evaluated Luna fb. Quadris Top fb. Luna 6, 14-dy interval, 5 applications experimental materials incl. Quintec, Priaxor and BAS 700

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Table 2. Evaluation of fungicide programs; effect on powdery mildew severity, yield, and fruit quality, UC Davis campus trial, 2012. Powdery mildew disease severity (%) Soluble interval sprays 21-Aug 3-Sep 3-Sep 15-Sep 15-Sep Yield Sunburn solids (% fruit by Treatment (days) (#) incidence necrosis incidence necrosis incidence (tons/A) weight) (°Brix) color pH

Sulfur dust alt. w/ Quadris Top 7 7 2 18 3 25 13 38.0 6.4 5.80 22.8 4.43

Sulfur dust alt. w/ Quadris Top 14 4 2 18 3 22 22 38.5 4.7 5.68 23.8 4.47 Sulfur dust alt. w/ Quadris Top, delayed start 7 4 8 32 22 50 46 25.3 7.1 5.45 23.5 4.49 Sulfur dust alt. w/ Quadris Top, early stop 7 5 2 18 3 28 25 39.2 6.1 6.03 22.8 4.47

Sulfur dust 7 7 2 10 3 16 13 37.6 5.1 5.98 22.5 4.48

Sulfur dust 14 4 3 16 3 25 13 38.2 4.7 5.63 22.0 4.49

Wettable sulfur 14 4 2 32 5 39 29 27.4 6.0 5.56 22.0 4.55

Non-treated control - 0 9 69 76 76 79 36.3 7.7 4.95 23.8 4.47

Quadris Top 14 4 1 13 3 25 19 46.8 4.8 5.48 22.5 4.44 LSD 5% 3.7 12.2 7.8 13.3 16.4 NS NS NS NS NS CV 102 34 52 26 40 34 44 9 5 1 Group comparisons Non-treated control 9 69 76 76 79 36.3 7.7 4.95 23.8 4.47 vs. fungicide treated 2 20 6 29 22 36.4 5.6 5.70 22.7 4.48 P value 0.00 0.00 0.00 0.00 0.00 NS 0.139 0.008 0.10 NS Note: Means in the same column followed by the same letter are not significantly different. NS = not significant

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Table 3. Evaluation of fungicide programs; effect on powdery mildew severity, fruit yield and quality, UC WSREC trial, 2012. Powdery mildew severity PTAB lab analysis z Sunburn rating Yield Interval Sprays (% fruit by Soluble solids 20-Aug 10-Sep (tons/ acre) Color pH (days) (#) weight) (°Brix) Treatment

Sulfur dust alt. w/ Quadris Top 7 11 0.05 b 0.1 b c 34.0 a 1.49 20.3 6.88 a b 4.57

Sulfur dust alt. w/ Quadris Top 14 6 0.03 b 0.1 b c 29.2 a b 2.35 19.8 6.68 a b 4.57

Sulfur dust alt. w/ Quadris Top, 7 6 0.08 b 0.35 b c 29.5 a b 2.73 20.0 6.68 a b 4.61 delayed start Sulfur dust alt. w/ Quadris Top, b 7 6 0 0 c 30.9 a b 1.45 19.8 6.78 a b 4.53 early stop

Sulfur dust 7 11 0 b 0.05 c 29.5 a b 2.77 20.5 7.00 a 4.61

Sulfur dust 14 6 0 b 0.1 b c 28.9 a b 2.58 20.8 6.90 a b 4.56

Wettable sulfur 14 6 0.15 b 0.68 b 29.4 a b 2.37 20.5 6.45 a b 4.60

Non-treated control --- 0 0.98 a 3.13 a 25.2 b 3 20.8 6.13 b 4.66

LSD o.o5 0.2 0.62 6.3 NS 0.85 0.817

CV (%) 92.1 80.7 15.1 80.3 2.9 8.3 1.6 Group comparisons Non-treated control vs. 0.98 3.13 25.2 3 20.8 6.13 4.66 fungicide programs 0.04 0.2 30.2 2.25 20.2 6.76 4.58 P value <.0001 <.0001 0.041 0.058 0.024 0.043 0.042

Note: Means in the same column followed by the same letter are not significantly different. NS = not significant. Disease rating scale: 0 = no disease, 1 = 2.5 % of foliage affected, 2 = 10%, 3 = 21%, 4 = 35%, 5 = 50%, 6 = 65%, 7 = 79%, 8 = 90%, 9 = 97.5%, 10 = 100% (10-point pre-transformed rating scale)

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Fig 1a-d. Summary of impacts of fungicide programs by year and trial location. Programs evaluated varied slightly by year and location, see individual annual reports for details. Asterisks indicate that differences from the non-treated control were statstically significant at the 5% level.

*

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California Tomato Research Institute ~ 2012 Annual Report 53

28 Fig. 1f. Blended fruit color 27

26 Non-treated Treated Weekly sulfur program 25 24 23 LED color 22 21 20 19 Fresno Solano San Fresno Yolo Solano Fresno Yolo Fresno Yolo Joaquin 2009 2010 2011 2012

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Project Title: Toward the Development and Application of Degree Day Model and Risk Index to Predict Development of Thrips and Tomato Spotted Wilt Virus (TSWV) and Implement an IPM Strategy in California Processing Tomato Fields (2012)

Principal Investigator: Robert L. Gilbertson Department of Plant Pathology, UC Davis

Cooperating Personnel: Ozgur Batuman, Postdoctoral Researcher, UC Davis Li Fang Chen, Postdoctoral Researcher, UC Davis Michelle LeStrange, Farm Adviser, Kings County Tom Turini, Farm Adviser, Fresno County Scott Stoddard, Farm Adviser, Merced County Gene Miyao, Farm Adviser, Yolo County Neil McRoberts, Department of Plant Pathology, UC Davis Diane E. Ullman, Department of Entomology, UC Davis

Summary: The goal of this ongoing project is improved understanding of thrips population dynamics and Tomato spotted wilt virus (TSWV) incidence in processing tomatoes in Central California and application of this knowledge to the development of an effective IPM strategy. In 2012, monitoring of representative tomato fields in Fresno, Kings, Merced and northern (Yolo, Solano, Colusa and Sutter) Counties revealed the build-up of thrips populations in April-May, somewhat later than previous years. Interestingly, a drop in thrips populations was detected from mid-June to early July, and this was associated with implementation of thrips management during this period. Consistent with these results, the first detection of TSWV in tomato plants was in Fresno County in mid-April, and in early May in other counties. TSWV was eventually detected in most monitored fields, and a number of fields in the northern production areas had relatively high incidences by early June. However, the overall incidence was relatively low in 2012 (0-14%), even in the northern fields that had high early incidences. As in the last 2-3 years, fall crops (lettuce and radicchio) were monitored during fall/winter seasons. In general, these potential TSWV bridge crops had low thrips populations and TSWV incidence, although some fall- planted lettuce fields and a radicchio field in Fresno had high incidences of TSWV infection. As in previous seasons, winter and spring weed surveys revealed very low levels of TSWV infection (~0.2%). RT-PCR testing of thrips revealed that most thrips were not carrying the virus throughout the season, although thrips collected from infected tomato plants were positive for TSWV. Thrips-transmission efficiency experiments were completed and revealed that male adult thrips transmit TSWV more efficiently than female adult thrips. The overall transmission efficiencies of colonies from Fresno and Yolo were different, with thrips from the Fresno colony having a higher transmission rate (44%) than thrips from the Yolo colony (33%). In addition, the origin of the virus isolate also played a role in thrips transmission efficacy, because the TSWV- Fresno isolate was more readily transmitted by thrips than the TSWV-Yolo isolate.

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Results of our greenhouse experiments for the assessment of the role of the soil-emerging adult thrips as an inoculum source for early season tomatoes confirmed that adult thrips emerge from soil, but no TSWV was detected in these thrips. Laboratory experiments revealed that thrips can stay dormant in soil for up to 7 weeks, and that some emerging adults retained the virus and were able to infect plants after emerging from soil. This strongly suggests that adult thrips emerging from soil can be an inoculum source, and is a possible explanation for how single TSWV- infected plant may be observed within fields early in the season. In 2012 insecticide trials, materials that reduced thrips numbers included Radiant and possibly two newer materials (Grandevo + organo-silicone and Torac with Agri-Mek and Dynamic). Results of the 2012 trial generally supported results of earlier trials in that Radiant is among the top performing materials, and that Beleaf either alone or tank-mixed with a pyrethroid can provide some control. In 2011, we developed a TSWV Risk Index (TRI), for predicting the potential for losses due to TSWV in Central Valley processing tomato fields. Based on information for each field monitored in 2012, the TRI was moderate for most fields in 2012. However, with some of the additional data added to the TRI this year we identified a number of low and high risk fields in 2012, and the TSWV incidences in these fields correlated with the TRI. Our phenology or degree day model for thrips population development in the Central Valley accurately predicted the timing of adult thrips generations. Thus, we are now feeling that this model can be used as a reliable predictor of when thrips populations increase, and when it is best to apply thrips management strategies. We now believe that the IPM strategy generated for thrips and TSWV is effective at reducing disease incidence. Key aspects includes proper timing of thrips management strategies and being able to identify high risk fields where IPM practices should be implemented. We now hope to continue to validate the thrips model and risk index to make these more grower-friendly and facilitate use of IPM strategy.

Objectives: The objectives of this project in 2012 were 1) conduct surveys of selected tomato fields to gain insight into when and from where thrips and TSWV enter into commercial processing tomato fields and assess the capability of our degree day model to predict the appearance of thrips populations in 2012, 2) to gain insight into potential sources of thrips and TSWV for tomatoes in the Central Valley, 3) to assess the role of TSWV resistant (Sw-5) tomato varieties for selection of ‘resistance breaking’ TSWV-isolates in California, 4) to assess the role of soil emerging thrips in TSWV epidemiology, 5) to evaluate transmission efficiency of TSWV for thrips populations from different geographic origins, 6) to utilize a PCR method for detecting TSWV in thrips and develop improved diagnostics for other tomato-infecting viruses, 7) to assess various thrips control methods, 8) to continue to develop and validate a phenology model and a risk assessment system for thrips and tomato spotted wilt disease, respectively, and 9) to continue to develop and assess an integrated pest management (IPM) strategy for TSWV in the Central Valley.

Information on Materials and Methods can be found in our CTRI proposal for 2012 and available upon request.

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Results: Field Monitoring: Monitoring efforts for thrips and/or TSWV were initiated in selected fall crops (wheat, onion, radicchio, lettuce and in some weedy orchards) in fall 2011 and in processing tomato fields at the beginning of tomato growing season for 2012. In 2012, all monitored fields were established with transplants. Table 1 lists the 24 fields that were monitored in 2012 and indicates final TSWV incidence in each field.

Yellow sticky cards: In 2012, the build-up of thrips populations started in late April in Fresno and Kings Counties, and was not detected in most monitored fields until mid-May in Merced and northern (Yolo, Solano, Colusa and Sutter Counties). Populations reached high levels by June (>3000 thrips/card), but shortly dropped to moderate levels (<1500 thrips/card) during July. A second peak was detected in August (up to 9,000 thrips/card) in most monitored fields. High thrips populations persisted into September and gradually declined in October (Fig. 1). The apparent population drop in June-July (in all counties) was striking because it had not been seen in previous years and it was not predicted based on our degree-day model (there was no evidence of a noticeable delay in thrips generation period differences in weather temperatures in July compared with previous years). Thus, it is possible that these decrease in thrips population during June-July reflected the widespread implementation of thrips management in early June.

Flower sampling: Thrips populations in flowers were detected soon after flower emergence, and thrips continued to be detected in flowers for the rest of the season. In 2012, similar to other years, most of the monitored fields had populations of 2-5 thrips per flower throughout the blooming stage. Overall, it continues to appear that the populations determined by yellow sticky cards are more informative than populations determined from flowers.

TSWV incidence: In 2012, the first detection of TSWV in processing tomato was in Fresno County in 14 April in a field established near a spring lettuce field with TSWV-infected plants. TSWV was first detected in Merced and northern counties early May, whereas it was not detected in Kings County until late May. In 2012, the overall incidence of TSWV in processing tomato fields in Fresno and Kings Counties were, with a few exceptions, low to moderate (0- 14%, Table 1). In 2012, the overall incidence of TSWV in processing tomato fields in Merced County was very low (0-2%). In 2012, TSWV was widespread and present at higher incidences in northern counties (up to 90% only in a few fields). Although the overall incidence of TSWV in monitored fields was relatively low (0-12%) and did not cause economic losses, some fields had high incidences and may have experienced economic loss.

Thus, in 2012, the overall incidence of TSWV in monitored fields in Fresno, Kings and Merced Counties was lowest since the beginning of our project in 2007. The overall pattern of disease development was similar in all of these years: low TSWV incidence in early-planted fields and higher incidences in late-planted fields. However, potential for TSWV outbreaks was shown in fields in northern counties as well as some fresh market tomato fields in the I-5 corridor, in the Dos Palos/Firebaugh area, where high TSWV incidences (>35% in some parts of the field) were observed.

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Survey of potential hosts for TSWV and thrips: We continued our efforts to identify reservoir hosts of TSWV and thrips before, during and after the processing tomato season in 2012. We again surveyed spring- and fall-planted lettuce in Fresno, spring- and fall-planted radicchio in Merced, and numerous weeds collected in the winter and spring.

Lettuce: TSWV was not found in most spring lettuce fields; however, very low levels of TSWV (<1%) were observed in a few fields. Overall, spring lettuce was considered clean and not to be a major inoculum source for processing tomatoes in 2012. Interestingly, high levels of TSWV in fall lettuce did not carry over to the spring lettuce.

Radicchio: In the winter of 2012, a radicchio field in Fresno had very high levels of TSWV (up to 60%). In contrast, all monitored radicchio fields in Merced were free of TSWV and had low thrips populations. In spring 2012, TSWV was detected in low incidences in some monitored radicchio fields in Merced and Fresno, but the incidence was sporadic (<1%) and did not cause economic losses in this crop. In general, radicchio growers in Merced are effectively managing TSWV and thrips and minimizing its role as a source of TSWV.

Fava bean: Early in 2012, we monitored two fava bean fields in one location in Yolo County, and surveys revealed that despite of very low thrips populations there were TSWV infections (<3%) in these fields. In 2012, the first TSWV outbreak in tomato in Yolo County was detected in a field that was ~1.5 mile from these fava bean fields.

Weeds: In 2012, weeds were collected from areas with TSWV outbreaks, and tested for the virus (Table 2). Most symptomless weeds collected before and during 2012 tomato growing season were negative for TSWV. A few weeds with symptoms (necrosis and thrips-feeding damage) were found and these were infected with TSWV. In addition, TSWV-infected weeds (sowthistle, prickly lettuce and black nightshade) were collected from spring lettuce fields and weedy orchards. However, the overall incidence of TSWV infection in weeds was very low (a total of 10 TSWV-infected weeds detected/602 samples tested; overall incidence 0.2%) and this is similar to results from previous years. To date, we have not found evidence of any weed that is extensively infected by TSWV in the Central Valley of California.

Additionally, before the growing season in 2012, four wheat and two onion fields were monitored for thrips and thrips from these fields were counted and tested for TSWV with the RT- PCR assay. Thrips population densities on wheat were low through April. In onions, thrips population densities were also low until in early April, but populations rapidly increased in late April. To date, TSWV has not been detected in thrips collected from wheat and onions, which are non-hosts of the virus.

Assessment the role of TSWV resistant (Sw-5) tomato varieties for selection of ‘resistance breaking’ TSWV-isolates in California: In the Central Valley, more fields being planted with tomato varieties carrying the TSWV resistance gene (Sw-5), especially in fields with a history of TSWV or in late planted. In 2012, our survey results indicated that resistant tomato plants with Sw-5 in the Central Valley generally did not show symptoms of TSWV infection. However, in a couple fields, symptoms were observed in Sw-5 tomatoes and infection with TSWV was confirmed with RT-PCR tests.

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Furthermore, to assess whether these Sw-5-infecting viruses were ‘resistant-breaking’ TSWV, a molecular analysis of two genes was performed. Virus isolates from these plants, as well as from susceptible tomatoes, were examined and the results did not show any difference in the sequences of genes. These results indicated that the isolates from Sw-5 tomatoes were not resistance-breaking strains.

Interestingly, when some of these TSWV-infected Sw-5 plants were used for rub-inoculation experiments to assess if the virus isolates were able to infect Sw-5 and/or susceptible tomato plants, TSWV symptoms did not appear on Sw-5 or susceptible plants. However, different virus symptoms appeared on all inoculated plants and these were determined to be caused by Tomato mosaic virus (ToMV). Results of RT-PCR assays confirmed that plants were infected with both TSWV and ToMV. Furthermore, when we tested 30 more Sw-5 tomato plants with or without fruit symptoms for TSWV, 29/30 of the plants were found to be infected with TSWV and ToMV. One plant had characteristic TSWV symptoms (bronzing, necrosis and ring spots) on leaf and fruits and was negative for ToMV. Later, this plant and all other plants were tested by PCR to assure they were true Sw-5 variety and, not surprisingly, all plants but one tested positive for presence of Sw-5 gene. This one plant was found to have segregated for the Sw-5 gene, which is why it had characteristic TSWV symptoms. This unexpected finding of mixed infection of Sw-5 varieties with TSWV and ToMV is very interesting and more studies are needed to address whether these mixed infections allow TSWV isolates to infect Sw-5 varieties in California.

Assessment of the potential role of the soil-emerging adult thrips as inoculum sources of TSWV for early planted tomatoes: Soil samples collected from fields: In 2012, we again collected soil samples from various fields to assess for whether adult thrips emerged from soil. Similar to 2011, we found that adult thrips emerged from some of the soil samples, and we recovered more thrips from the 2012 soils than from the 2011 soils. Similar to 2011, most of the emerging thrips were captured in first or second week of the experiment. Thrips populations on these yellow sticky cards were variable (1-174 thrips/card), and highest populations were from soil samples collected from a plowed processing tomato field. Higher populations also came from soils from fall crops and weedy orchards (Table 3). None of the thrips from these soils tested positive for TSWV by the RT-PCR assay. Interestingly, in most containers, many weeds and volunteer crops germinated and started to grow during the experiment. These plants, as well as the fava bean indicators, did not develop symptoms of TSWV infection, consistent with the RT-PCR results indicating that the thrips were not carrying TSWV. To further test whether these volunteer tomatoes or weeds were infected with the TSWV, leaf samples from these plants as well as the fava beans indicator plants that were placed in each container were analyzed with RT-PCR. All of these plants were tested negative for TSWV.

Soil maintained under laboratory conditions: Initially, we tested rates of adult emergence from pupae of nonviruliferous thrips from various types of soil and for different periods of time at different temperatures (e.g., at 4, 15 and 25ºC). We found that 60-70% of adult thrips emerged from soil after pupae were incubated at 15ºC for 4 weeks or 4ºC for a week. Rates of emergence of nonviruliferous thrips were then tested by incubating pupae at 4ºC for 0 to 8 weeks.

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The results showed that the emerging rates declined over time to 10%, 6% and 0% for 6, 7 and 8 weeks of storage at 4ºC, respectively (Fig. 4A). We also found that viruliferous thrips had similar rates of emergence following 1, 2 and 3 weeks at 4ºC (Fig. 4B). Furthermore, we confirmed that after 3 weeks at 4ºC treatment, emerging adult thrips were able to transmit TSWV to healthy Datura seedlings. Thus, our results indicated that thrips pupae can survive and provide adult thrips from soil after 4ºC treatment for up to 7 weeks, and that emerged viruliferous adult thrips were able to transmit TSWV after at least 3 weeks of 4ºC treatment.

Together, these results indicated that thrips pupae can stay dormant in the soil up to seven weeks and that some adults emerging from these pupae may well retain TSWV (at least three weeks) and transmit the virus after emerging from soil. It appears that viruliferous adult thrips emerging from soil can be a potential inoculum source for early-planted tomatoes as well as other susceptible plants (weeds or bridge hosts), in which the virus can be amplified.

Detection of TSWV in thrips and studies of thrips biology: Periodic RT-PCR tests performed with thrips collected from flowers and yellow sticky cards revealed that none of the insects were positive for TSWV in 2012, whereas lab-reared viruliferous thrips controls and some of the thrips collected directly from TSWV-infected tomatoes were positive. These results indicated that most of the adult thrips present in processing tomato fields throughout the season were not carrying the virus. Overall, RT-PCR tests of thrips for TSWV does not appear to be an effective tool for predicting when TSWV will appear in the field because the number of thrips carrying the virus is so low.

Comparison of thrips transmission efficiency for thrips colonies from Fresno and Yolo: We completed our studies comparing the TSWV-transmission efficiency of thrips populations originating from Fresno and Yolo to transmit TSWV-Fresno and -Yolo isolates (TSWV-F and TSWV-Y). Consistently, our results showed that transmission rate of Fresno thrips with TSWV- F was greater (43.8%) than Yolo thrips with TSWV-Y (22%). Male thrips from both populations transmitted TSWV more efficiently than female thrips (Table 5). Interestingly, transmission rates increased to 37% for Fresno thrips with TSWV-Y, confirming that the Fresno thrips population had a greater transmission efficiency. Furthermore, transmission rates of the Yolo thrips population were also elevated (32.9%) when TSWV-F was used for transmission, suggesting that the TSWV-F isolate was more readily transmitted by both populations. Based on our findings, the Fresno thrips population showed higher transmission efficiency for both TSWV isolates compared with the Yolo thrips population. This was consistent with our finding that thrips populations are often higher in tomato fields in Yolo County, but the incidences of TSWV are typically higher in Fresno County. Furthermore, regardless of the geographic origin, male adult thrips transmitted TSWV more efficiently than female adult thrips, and this is in agreement with previous results of other researchers.

Development a phenology model and a risk assessment system for thrips and tomato spotted wilt disease in processing tomato fields in Central Valley of California: In 2011, we developed a predictive tool to assist growers to determine when thrips populations begin to increase. This phenology model is a “degree day’ model that utilizes the robust relationship between temperature and thrips development rates to project the timing of appearance of successive thrips generations.

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In 2012, this model was modified and validated, and compared with real-time thrips populations in monitored fields. The model predicted at least eight thrips generations during the tomato growing season. In most instances, the model was accurate in predicting the timing of these generations. We assume that thrips numbers will increase with the appearance of each generation, allowing the model to be validated by comparison with field data. Again, in 2012, after each successive prediction of thrips generation, an increase in cumulative thrips populations as determined on yellow sticky cards provided evidence of more thrips being generated ( Figs. 2 and 3).

As the predictions made by the model became available during the growing season, the information was regularly updated on the model web page and provided to growers through the monthly CTRI update. The model projections were provided in a window of up to 10 days in advance so that growers could implement thrips management in a timely manner. We believe that, in 2012, the drop in thrips populations in June-July was due, in part to timely implementation of thrips control based on the results of the model’s forecasts and backed up by field monitoring. We will continue to modify and validate the model for the 2013 growing season and improve the accessibility of model’s web page to growers and PCAs so that timely insecticide implementation can be made. The model’s web page on thrips population projections can be found on the following website (https://sites.google.com/site/cubelabsite/current- research/tomato-spotted-wilt-virus/thrips-population-projections).One possible new development will be to replicate the model-based projections on a dedicated Facebook page.

In 2011, we developed the TSWV risk index (TRI) for California processing tomatoes as a tool to help growers predict the relative level of risk for TSWV development in a given field based upon a variety of factors known to influence disease development. In 2012, evaluations of TRI revealed certain factors that were consistently more important than others, allowing us to modify the TRI to be more accurate (Table 6). In 2012, the proximity of TSWV-infected crops/weeds to fields appeared to be a very important factor and, thus, the point value for this factor was increased. Another important factor was the planting density, as it was apparent that TSWV impact in fields with single rows was more pronounced than those with double rows; thus, the point value for single row plantings was increased. The planting of a Sw-5 tomato variety dramatically reduces TSWV incidence; thus, the point value for this factor was changed to a credit (negative -35).

In 2012, using the current version of TRI, fields identified as high risk were consistently found to have higher TSWV incidences (e.g. monitored BF, YL and EG fields in Yolo with 7, 7 and 12% TSWV; and monitored North, Oakland and Ness fields in Fresno with 7, 12, and 14% TSWV) compared with other monitored fields (e.g. RO, PR and AO fields in Yolo and Harris, Mt. Whitney and Tranquility in Fresno with <2% TSWV). The risk index for the majority of monitored fields in 2012 was moderate, but some low risk fields were also identified. We hope to continue to evaluate and modify the TRI, as we believe this tool will be beneficial for decision making and will reduce risk of TSWV associated losses.

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Insecticide Trial: Two experiments were conducted at UC West Side Research and Extension Center in Fresno County to compare activity of insecticides against thrips on tomatoes and to assess the impact of these programs on TSWV in 2012. Processing tomato transplants (cv. H8004) were transplanted on 2 May, sprinkled for two weeks, and irrigated with buried drip for the remainder of the season. The 2012 evaluation of insecticide programs was conducted with treatments that were similar but not identical to those treatments that were tested in 2009 and 2010. In 2012, several materials reduced the levels of thrips when compared with the untreated control (Table 7). Results of the 2012 trial generally supported results of earlier work in that Radiant has consistently been among the top performing materials, and Beleaf either alone or tank-mixed with a pyrethroid has provided a level of control. Other treatments that resulted in lower levels of thrips were the new materials Grandevo with organo-silicone, and Torac with Agri-Mek and Dynamic. However, unlike 2007 and 2008 results, but similar to 2010 results, Venom also reduced thrips population densities. Although efficacy on thrips counts are still in progress and will be available through CTRI, in 2012, there were clearly differences among the foliar treatments in terms of yield (Table 8) and in incidence of TSWV symptoms on plants (Table 9). In 2010, there were extremely high levels of virus in the vicinity of the field station and it was present at intermediate levels in 2009, 2011 and 2012. Therefore, it is possible that the impact of insecticides is largely dependent upon whether the majority of the virus is due to spread within the field or with virus-carrying thrips from outside of the field. Regardless of the year, we have never seen a reduction in disease associated with the drip applied materials, but we saw an increase in yield this year in the treatment. No phytotoxicity symptoms were detected. Together, these results indicate that some materials continued to reduce thrips populations to some extent and reduce TSWV incidences, but that growers can not rely on insecticide application for efficient control.

Integrated pest management (IPM) for TSWV in Central California: Our accumulated research findings on thrips population densities and TSWV development on processing tomatoes in Central Valley of California are presented in Figure 4. Based on this understanding, the following IPM approach for managing TSWV in processing tomatoes has been developed. This approach has been presented to growers through many presentations, reports and a UCIPM flyer. The flyer is available for interested parties upon request. The IPM program is outlined below and continues to be modified and validated. The management strategies are segmented into preplant, in-season and post-harvest crop periods.

A) Preplant i) planting location/time of planting-this will involve determining if proximity to the foothills or other alternate crop hosts (e.g., lettuce or peppers) favors infection and/or if early or late- planted fields have higher incidences of TSWV. If either of these scenarios is found, then this may indicate possible management strategies. ii) resistant cultivars-these are available, but may not be necessary if other practices are followed. Resistant cultivars should be used in hot-spot areas or in late planted fields, especially in near those fields in which TSWV infections have already been identified. iii) weed management-maintain weed control in and around tomato fields and especially in fallow fields and orchards, as weeds are potential TSWV hosts. Indeed, our results here indicated that if weeds are allowed to grow in fallow fields, they can amplify thrips and TSWV and serve as inoculum sources for processing tomatoes.

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B) In-season i) monitoring for thrips/TSWV-monitoring thrips populations and TSWV incidence can indicate when to apply insecticides for thrips control, thereby reducing TSWV spread. All evidence indicates that thrips management should be initiated early (e.g., April/May) to reduce the development of virus-carrying adult thrips that can spread the virus within and between fields. This may even need to be done before disease symptoms are observed. More accurate timing of such treatments may be come from using the TRI and phenology model. ii) roguing – roguing of infected tomatoes before fruit set can be an efficient way of reducing TSWV inoculum in field especially early in the season. iii) weed management-maintain effective weed control in and around tomato fields.

C) Post-harvest i) sanitation-immediately plow under crop residue following harvest. ii) cover crops-if you plant cover crops, consider use of non-host cover crops (e.g., triticale and ryegrass) to reduce volunteers and weeds that can harbor TSWV and thrips vector (note that thrips can stay in soil long period of times). iii) bridge crops- 1) avoid planting radicchio, lettuce and fava beans, 2) establish fall crops of these plants away from late-planted tomatoes, 3) monitor for thrips and TSWV, 4) implement thrips management if necessary and, finally, 5) immediately plow under crop residue following harvest.

Current situation of thrips and TSWV in California: • Western flower thrips and tospoviruses have emerged as major pests in California crops and are likely to continue to be a problem in crops such as lettuce, pepper, radicchio and tomato. • It is difficult to predict when and where TSWV outbreaks will occur. • Not all aspects of thrips and TSWV biology fully understood. • No single approach is adequate for management of thrips or TSWV. • Evidence that the IPM approach is effective: -Losses due to TSWV in monitored fields have been minimal -Growers using some or all of the IPM practices have not experienced significant losses due to TSWV • Progress in managing thrips and TSWV in radicchio has been reduced TSWV in Merced • Economic losses due to TSWV in 2012 were minimal to none, although some fields did have high TSWV incidences (~14%) • The phenology (degree day) model can predict when thrips populations begin to increase and subsequent generations. • A risk index for tomato fields has been developed that can help growers predict the chances of developing TSWV in their field, thereby allowing for decision to be made regarding management practices.

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Table 1. List of monitored processing tomato fields: their locations and TSWV incidence in 2012.

Monitored Fields 2012 Northern Counties TSWV % RO Winters, Yolo 0 BF County Line, Colusa 7 AO County Line, Colusa 0 PR Dixon, Solano 2 EG Robin,Sutter 12 YL Yolo Town,Yolo 7

Merced County PT Rogers Rd, Paterson 2 GC Gun Club Rd, Gustine 1 FM Fentem Rd, Gustine 2 BC Bert Crane Rd, Merced 0 DF Dickenson Ferry Rd, Merced 0 LG Le Grand Rd, Merced (Fresh Market) 0.5 BH Buchanan Hallow Rd, Merced (Fresh Market) 0.5

Fresno County North Firebough area 7 Oakland Five Points area 12 Mt.Whitney Five Points area 0 Tranquility Tranquility area 2 Nees Firebough area 14 Harris Five Points area 0.5

Kings County Tomato #1 Lassen Ave between Phelps and Jayne 2 Tomato #2 Laurel Ave at Avenal Cutoff 0.3 Tomato #3 Nevada Ave & Kent 2 Tomato #4 El Dorado Ave near Dorris 5 Tomato #5 Lassen Ave & Tornado 7

California Tomato Research Institute ~ 2012 Annual Report 64

Average Thrips Populations per Yellow Sticky Card

12000 12000 Yolo/Colusa Co. Merced Co. 10000 10000 2012 8000 2012 8000 2011 2011 6000 6000 2010 2010 2009 4000 2009 4000 2008 2000 2000

0 0 4/8/09 5/6/09 6/3/09 7/1/09 9/9/09 4/5/12 5/3/12 8/9/12 3/11/09 3/25/09 4/22/09 5/20/09 6/17/09 7/15/09 7/29/09 8/12/09 8/26/09 9/23/09 3/22/12 4/19/12 5/17/12 5/31/12 6/14/12 6/28/12 7/12/12 7/26/12 8/23/12

Build up Peak Drop Highest in the peak Build up Peak Drop Highest in the peak 2009 8-May 14-Aug 11-Sep 2009 2008 4-Apr 16-May 10-Oct 2012 2010 21-May 13-Aug 23-Oct 2012 2009 6-Apr 15-May 2-Oct 2011 2011 26-May 14-Jul 24-Sep 2010 2010 14-May 23-Jul 5-Oct 2009 2012 17-May 13-Jun 6-Sep 2011 2011 12-May 21-Jul 15-Oct 2008 2012 10-May 1-Aug 2010 12000 6000 Fresno Co. Kings Co. 5000 10000 2012

4000 2011 8000

2010 2012 3000 2011 2009 6000 2010 2000 2008 2009 2008 2007 4000 1000 2007

2000 0

0 4/9/12 5/7/12 6/4/12 7/2/12 2/27/12 3/12/12 3/26/12 4/23/12 5/21/12 6/18/12 7/16/12 7/30/12 8/13/12 8/27/12 9/10/12 9/24/12 10/8/12

10/22/12 3/9/12 4/6/12 5/4/12 6/1/12 9/7/12 3/23/12 4/20/12 5/18/12 6/15/12 6/29/12 7/13/12 7/27/12 8/10/12 8/24/12 Build up Peak Drop Highest in the peak Build up Peak Drop Highest in the peak 2007 6-Apr 25-May 2011 2007 31-Mar 29-Jun August 2012 2008 9-Apr 29-May 20-Oct 2008 2008 3-Apr 1-May October 2011 2009 19-Mar 22-Jul 11-Aug 2010 2009 14-Apr 11-Aug October 2008 2010 3-May 21-Jul 21-Oct 2012 2010 23-Apr 26-Aug November 2010 2011 11-Apr 18-Aug 23-Sep 2009 2011 12-May 16-Jun November 2009 2012 23-Apr 17-Aug 2007 2012 25-Apr 9-Sep 2007

Fig. 1. Average thrips counts per yellow sticky card in monitored fields in Fresno and Kings Counties in 2007-2012, in Merced County in 2008-2012 and Yolo and Colusa Counties in 2009-2012. Note the thrips population build up, peak and drop dates are indicated below graphs. Highest thrips populations during peaks are ranked (high to low) from top to bottom.

California Tomato Research Institute ~ 2012 Annual Report 65

Table 2. Weed survey results for TSWV incidence during 2012. Table 4. Summary of the assessment of the potential role of the Weed a Tested (+) Weed a Tested (+) soil-emerging thrips (laboratory conditions) Black nightshade 10 (1) Curlydock 22 (0) Bindweed 58 (0) Malva 68 (0) Flaree 30 (0) Datura 10 (0) Pineapple weed 24 (0) Monocots 18 (0) Sowthistle 134 (7) Shepherd's purse 3 (0) Prickly lettuce 85 (2) Fiddler neck 5 (0) Russian thistle 16 (0) Pigweed 8 (0) Buckhorn Plantain 8 (0) Turkey mullein 15 (0) Wild radish and Other common 30 (0) 38 (0) Mustard weeds A B (+) number of plants tested positive for TSWV by immunostrips and RT-PCR. a, Total weed samples from all counties

Table 3. Summary of the assessment of the potential role of the soil-emerging thrips (soils from fields) Number RT-PCR RT-PCR Sample Source of the soil Collection Previous/Current Soils of tests of tests of # samples Date Crop Type Discarded captured thrips plants Yolo & Colusa Counties 1 HWY 113 1-Mar Weedy Prunus 129 Negative Negative 27-Apr 2 Sutter County 1-Mar Proc. Tomato 12 Negative Negative 27-Apr 3 Yolo/Colusa County Line 1-Mar Proc. Tomato 26 Negative Negative 27-Apr 4 Yolo Rd 29 1-Mar Fava Beans 40 Negative Negative 27-Apr Merced County 5 SM Sandy Mush - Merced 29-Feb Fall Radicchio 14 Negative Negative 27-Apr 6 LG La Grand Rd. -Merced 29-Feb Late Fresh Mark. To 2 Negative Negative 27-Apr 7 HT Hunt Rd. -Gustine 29-Feb Late Fresh Mark. To 1 Negative Negative 27-Apr 8 PT Paterson/Wastley 29-Feb Weedy Almond 9 Negative Negative 27-Apr Fresno County Table 5. Summary of assessment and comparison studies in 9 Gale & Butte 28-Feb Onion 37 Negative Negative 27-Apr 10 Woolf Creek 28-Feb Proc. Tomato 4 Negative Negative 27-Apr transmission efficiency of thrips and TSWV isolates 11 North -Fairbaugh 28-Feb Proc. Tomato 174 Negative Negative 27-Apr collected from Fresno and Yolo Counties. 12 Farming D -Five Point 28-Feb Spring lettuce 10 Negative Negative 27-Apr TSWV-Fresno isolate TSWV-Yolo isolate 13 North -Fairbaugh 28-Feb Almond 4 Negative Negative 27-Apr Fresno Thrips Yolo Thrips Fresno Thrips Yolo Thrips Kings County Male Female Male Female Male Female Male Female 14 John Farms 28-Feb Proc. Tomato 3 Negative Negative 27-Apr a 15 Huron 28-Feb Fall Radicchio 149 Negative Negative 27-Apr 45% (8) 42.5% (8) 40% (7) 25.7% (7) 42% (5) 32% (5) 26% (5) 18% (5) 16 Plymouth 28-Feb Weedy Almond 13 Negative Negative 27-Apr 43.8% 32.9% 37% 22%

17 UC Davis Greenhouse 28-Feb Sterile soil; (-) control 0 N/A N/A 27-Apr

California Tomato Research Institute ~ 2012 Annual Report 66

a Numbers in parentheses represent replicates of independent experiments Table 7. Insecticide efficacy against Western flower thrips in processing tomatoes in 2012. Table 6. Tomato spotted wilt virus Risk Index (TRI) for Processing Tomatoes Treatment 4 Aug in the Central Valley of California (2012 index) Nymphs Adults Tomato Variety1 Examples Risk Index Points a,b,c stunted plt w less fruit, very severe, dead like 50 d,e,f Res. size plt w less fruit, severe symptoms 40 g,h,i Nor. size plt w many fruits severe symptoms 30 Grandevo 3.0 lbs + organo-silicone 0.25% 1.3 30.7 j,k,l Nor. plt w many fruits some symptoms 20 62.7 m,n,o Vigor.Plt w many fruits almost no symptom 10 Torac 15EC (tolfenpyrad) 21 fl oz 0.0 p,q,r with SW5 -35 Venom 70SG 0.895 lb 0.3 70.0 Planting Date2 Prior to February 1 First planted fields in any given region 10 Radiant 7.0 fl oz 0.7 45.7 February 1-29 week or two later than first planted fields 15 March 1-15 week earlier than recommended period 10 HWG 86 10SE (cyazypyr) 20.5 fl oz 1.0 72.7 March 16- April 31 Recommended period (Majority of fields) 5 Agri-Mek SC 3.0 fl oz 57.7 May 1-20 week or two later than majority of fields 15 2.3 May 21- June 5 tree week or more later planted from major 25 Torac 15EC (tolfenpyrad) 21 fl oz + After June 5 latest planted fields in a given region 35 0.0 38.7 Plant Population3 Agri-Mek SC 3.0 fl oz + Dynamic 0.25% Less than 1 plant per foot single row (7000 per acre) 35 2 to 3 plants per foot double row (9000 per acre) 15 Entrust SC 7 floz/acre + MSO 0.5% 0.0 51.7 More than 3 plants per foot double row but more dens (>9000 per acre) 5 Untreated control 1.3 76.7 Planting Method Direct seeded 10 LSD0.05 1.9 36.1 Transplanted 5 Proximity to Known Bridge Crops CV (%) 143.0 36.9 adjacent radicchio, lettuce, fava, weed/fallow field, pepper or tomato 25 less than 1 mile radius distance (if TSWV confirmed add 20 more points) 15 z 1-2 mile radius distance (if TSWV confirmed add 10 more points) 10 Treated 10, 18 and 26 Jul with Co2-pressurized back pack greater than 2 mile or None (if TSWV confirmed add 5 more points) 5 Proximity to Thrips Source sprayer at 40 gal/acre. Unless otherwise specified, all adjacent wheat, pea, alfalfa or weedy patches etc. 20 materials were applied with Dynamic at 0.25%. less than 1 mile radius distance 15 y Collected 25 samples per plot in 70% Et-OH and counted 1-2 mile radius distance 10 None 5 nymph and adults under dissecting scope. At-Plant Insecticide None 15 for other pests (+ thrips) 10 specifically for thrips 5 Weed situation/Herbicide use w/out herbicide but weedy In-field ONLY weed population 15 w/out herbicide but not so weedy 10 w/out pre emergence herbicide or NO weed 5 Total Points (0-225) Risk of Losses Due to TSWV Less than or equal to 95 Low Greater than 100 or equal to 150 Moderate Greater than 150 High 1 Additional varieties will be included as data to support the assignment of an index value are available. 2 In those years when the normal date of planting for the first tomato in an area is delayed due to inclement weather, these date ranges should be moved later by an equal amount. In most years, these date ranges will also vary slightly with latitude. Dates can be shifted 5 days earlier in the extreme southern counties and 5 days later in the extreme northern counties.

Note that point values in the index are not final and shown here as an example.

California Tomato Research Institute ~ 2012 Annual Report 67

Table 8. Influence of insecticide programs for controlling: thrips, Table 9. Influence of insecticide programs for control of thrips and TSWV incidence. TSWV incidence, yield and other quality parameters. z y Treatment TSWV % Injections into drip irrigation system buried to 10 in 6 20 18 23

z Treatment Yield y x Jun Jun Jul Aug Fruit quality (% by weight) PTAB Injections into drip irrigation system buried to 10 in (tons/ w acre) red grn rot sun TSWV color solids pH Platinum75SG 3.7 oz (7 Jun), Venom 6.0 oz (27 J un) 0.1 5.4 28.7 19.8 brn Platinum75SG 3.7 oz (7 Jun), Venom 6.0 oz (27 Jun) 29.5 57.1 5.2 28.4 3.6 5.7 21.9 5.34 4.48 Platinum75SG 3.7 oz (7 Jun) cyazypyr 13.5 oz (27 Jun) 0.1 5.8 14.1 17.9 Platinum75SG 3.7 oz (7 Jun), cyazypyr 13.5 oz (27 Jun) 26.7 48.3 4.8 33.8 2.2 10.9 22.1 5.30 4.45 Untreated 24.3 47.6 5.9 35.2 3.2 8.1 22.3 5.41 4.45 Untreated 0.2 4.3 21.7 21.2 Drip injection, probabilityv 2.46 NS NS NS NS NS NS NS NS Probability NS NS NS NS Foliar applications Yield Fruit quality (% by weight) PTAB Trans. 12 Jun 22 Jun 29 Jun 9 Jul 18 Jul (tons/ acre) Foliar applications drench red grn rot Sun color solids pH TSWV brn Trans. 12 22 29 9 Jul 18 Jul TSWV % cyazyp Radiant Dimth Radiant Dimth Radiant 29.0 54.9 5.9 31.5 2.3 5.3 22.3 5.38 4.45 yr 10 fl oz 4EL 1pt. 10 fl oz 4EL 1pt. 10 fl oz drench Jun Jun Jun Radiant Dimth Radiant Dimth Radiant 28.3 54.7 5.8 27.9 3.4 8.2 21.8 5.26 4.44 10 fl oz 4EL 1pt. 10 fl oz 4EL 1pt. 10 fl oz cyazyp Radiant Dimth Radiant Dimth Radiant 0.3 4.3 13.7 13.2 Radiant Dimth 26.6 51.1 4.3 33.0 2.8 8.6 21.8 5.43 4.47 10 fl oz 4EL 1pt. yr 10 fl oz 4EL 10 fl oz 4EL 10 fl oz Untreated 23.0 43.1 5.2 37.5 3.4 10.9 22.6 5.34 4.48 v LSD0.05 3.07 NS NS NS NS NS NS NS NS 1pt. 1pt. AB 0.03 NS NS NS NS NS NS NS NS Radiant Dimth Radiant Dimth Radiant 0.0 5.2 31.9 13.2 CV (%) 58. 4.8 6.43 1.30 13.7 22.7 40.6 28.3 9 52.7 10 fl oz 4EL 10 fl oz 4EL 10 fl oz 1pt. 1pt. Radiant Dimth 0.3 4.5 16.8 18.6 10 fl oz 4EL 1pt. Untreated 0.0 6.6 23.7 33.5

LSD0.05 NS NS NS AB NS NS NS NS CV (%) 317.1 67. 108.6 36.87 38 zExperimental area was transplanted on 17 May with cv. H8004 processing z Experimental area was transplanted on 17 May with cv. tomato plants at UC West Side Research and Extension Center. Foliar H8004 processing tomato plants at UC West Side Research applications were made with a backpack sprayer at 30 gpa. and Extension Center. Foliar applications were made with a backpack sprayer at 30 gpa. y Twenty to 25 lbs samples were taken from a mechanical harvester, and hand y Percentage of plants exhibiting Tomato spotted wilt virus sorted. Fruit in each category were weighed and percentage by weight was symptoms per plot (n=55 to 65) calculated. xv Least significant difference at probability of 0.05. NS x A sample of 50 red fruit from each plot were tested for color solids and pH signifies that there is no significant difference. by Processing Tomato Advisory Board laboratory in Helm, CA. w Yields per acre were calculated based on machine-harvests on 9 Sep. v Least significant difference at probability of 0.05. NS signifies that there is no significant difference.

California Tomato Research Institute ~ 2012 Annual Report 68

Fig 2. The phenology model predictions for thrips generations in monitored fields and their comparison with actual thrips dynamics (cumulative data) recorded in 2012. 10 35000 10 35000 Adults 9 Adults Yolo/Colusa Co. 9 Merced Co. 30000 Egg 30000 8 8 Egg overwinter 7 25000 7 25000 overwinter thrips/card 6 6 thrips/card 20000 20000 5 5 15000 15000 4 4

3 10000 3 10000 2 2 5000 5000 1 1 0 0 0 0 11/3 12/23 2/11 4/1 5/21 7/10 8/29 10/18 12/7 11/3 12/23 2/11 4/1 5/21 7/10 8/29 10/18

10 35000 10 35000 9 Adults Fresno Co. 9 Adults Kings Co. 30000 30000 8 Egg 8 Egg 7 25000 7 25000 overwinter overwinter 6 6 20000 20000 thrips/card thrips/card 5 5 15000 4 15000 4 3 10000 3 10000 2 2 5000 5000 1 1 0 0 0 0 11/3 12/23 2/11 4/1 5/21 7/10 8/29 10/18 12/23 2/11 4/1 5/21 7/10 8/29 10/18

Note that left axis are thrips generation numbers, right axis are cumulative thrips numbers per card and horizontal short lines projected from adults indicate insecticide implementation windows for growers to assure regional thrips control.

California Tomato Research Institute ~ 2012 Annual Report 69

California Tomato Research Institute ~ 2012 Annual Report 70

Fig 3. The phenology model predictions for thrips generations in monitored fields and their comparison with actual thrips dynamics (thrips/card data) recorded in 2012.

Yolo/Colusa Co. Merced Co.

Fresno Co. Kings Co.

Note the period from May/June until early July, thrips numbers went down while degree days ramped up. One explanation is that early spraying in May/June, targeting generations 2 or 3 knocked the thrips back in July.

California Tomato Research Institute ~ 2012 Annual Report 71

Development of TSWV in Processing Tomato Fields Winter Early-Mid Season Late Season Off Season TSWV overwinters at Infections with TSWV – Potential for higher Persistence in weeds, low levels in weeds, low incidences, incidence/epidemics reservoir hosts, bridge bridge crops and thrips depending on and economic losses in crops (i.e., radicchio populations of virus late-planted crops. Late and lettuce) carrying thrips infections may be High limited to some shoots. Thrips emerging from soil Thrips emerging from soil (When?) Amplification in susceptible crops (When?) (dependent on initial inoculum, Low thrips populations)

Western Flower Thrips Population Dynamics in the Central Valley of California

Winter: Thrips Spring: Thrips Summer: Peak Fall: Populations overwinter at very low populations increase populations decrease levels

High Thrips emerging from soil Thrips emerging from soil Target: 2nd and 3th Adult thrips Generations

Increased Viruliferous Low thrips populations

December January February March April May June July August September October November

Fig. 4. Schematic presentation of thrips population dynamics and development of tomato spotted wilt diseases in processing tomatoes in the Central Valley of California. The recommended thrips management period is highlighted with dashed loop.

California Tomato Research Institute ~ 2012 Annual Report 72

Project Title: Development of a Virus Integrated Pest Management Strategy for Processing Tomatoes in California’s Central Valley

Project Leader: William M. Wintermantel USDA-ARS, Salinas, CA

Introduction : This project is funded jointly by the California Tomato Research Institute (CTRI) and the California Curly Top Control Board (CTCB), and sets the stage for future IPM grants focused on understanding the dynamics of annual virus infections by identifying important reservoir hosts of tomato viruses, identifying key viruses in new areas of processing tomato production, and monitoring vector incidence (sticky cards) in correlation with virus incidence. The primary goal of the larger project is to develop targeted IPM strategies to minimize impact of viruses on tomato production based on knowledge of epidemiology including important reservoir hosts and vectors by region. This project focused specifically on curly top, and involved both a field component and a lab component. The lab component was focused on competitiveness and dominance of the two predominant species as well as an older curly top virus species that was once common in California, but is no longer prevalent in the field (California/Logan Strain now known as Beet curly top virus or BCTV). The lab tests allowed for controlled inoculations, focused on standardized inoculation conditions for uniformity in studies. The field component examined dominance and competitiveness of the two primary virus species responsible for curly top disease in California among prevalent crop and weed hosts of the virus, and focused on several sites along the west side of the San Joaquin Valley identified through cooperation with the CTCB and sampled cooperatively with UC Extension. The intent has been to determine what factors lead to emergence of new curly top variants in the field, since other states have recently seen the emergence of new curly top species in pepper and pumpkin not yet reported in California. The two curtovirus species common in California and most of the American West, Beet severe curly top virus (BSCTV) and Beet mild curly top virus (BMCTV), have been the dominant forms for approximately two decades now after replacing the earlier “California/Logan Strain” or BCTV.

Objectives: Brief Synopsis: Sets stage for and complements planned IPM grants focused on understanding the dynamics of annual virus infections by identifying important reservoir hosts of tomato viruses, identifying key viruses affecting processing tomato production, and determining threats to tomato from emerging virus variants. Our long-term goal is to develop targeted IPM strategies to minimize impact of viruses on tomato production based on knowledge of epidemiology including important reservoir hosts and vectors by region. The initial focus is curly top, but detection and monitoring methods are being developed for several tomato- infecting viruses through this project for use in studies on additional viruses and for routine detection.

California Tomato Research Institute ~ 2012 Annual Report 73

1. Field-test tomato virus detection tool-kit for effectiveness in identification of most common tomato viruses affecting production in California.

2. Complete studies on transmission of Beet mild curly top virus (BMCTV) and Beet severe curly top virus (BSCTV) from tomato and alternate crop and weed hosts in relation to virus concentration in the host plants. Compare competition between BMCTV and BSCTV with newly identified variant curtovirus isolate to determine potential impact on tomato production.

3. Complete studies on incidence and concentration of specific curtoviruses in weed and crop hosts.

Progress on specific objectives : Objective 1. Field-test tomato virus detection tool-kit for effectiveness in identification of most common tomato viruses affecting production in California.

During year 1 of this project it became clear that the ability to rapidly identify key tomato viruses would greatly streamline this project. We developed a multiplex virus detection system allowing for minimal reaction testing for the presence of viruses common to California tomato production using polymerase chain reaction (PCR) and reverse transcription- polymerase chai n reaction (RT-PCR). RT-PCR is an enzyme-based system used routinely by laboratories to identify viruses infecting plants. Multiplex detection involves using primers (small pieces of DNA that match target sequence used for initiation of RT-PCR) that specifically identify each target virus, but using primers that produce different sized products. Our system allows the identification of all major curtovirus species known in California, as well as TSWV, INSV, CMV and AMV. A fully develop system for differentiation of criniviruses already exists for differentiation of TICV from Tomato chlorosis virus (ToCV), a related species (Wintermantel and Hladky, 2010; Journal of Virological Methods [doi:10.1016/j.jviromet.2010.09.008]), and TICV is not common in processing tomato production regions; therefore TICV was not included in development of the current multiplex system. Similarly, we had already developed primers for differentiation of the viruses causing curly top disease through previous studies, and in fact these are used in studies under Objective 3, below. During the past year we have attempted to “field-test” the system using isolates obtained from fields collections to confirm reliability for detection of significant variation among isolates of each virus. Although we appear to have effectively developed the ability to detect all viruses these studies have demonstrated problems with the multiplex system that are being addressed in the lab. Some isolates of AMV have not been reliably and consistently detected, and primers are being modified to resolve this issue, which requires re- testing. We have also had insufficient samples to effectively evaluate CMV detection. Once the new AMV primers are added back in we should again be able to revisit field testing. This is not a difficult task, but one that can only truly be addressed using field samples. It is our hope that primer issues and re-testing can be resolved by the December meeting, but most likely will take until later this winter.

California Tomato Research Institute ~ 2012 Annual Report 74

Objective 2. Complete studies on transmission of Beet mild curly top virus and Beet severe curly top virus from tomato and alternate crop and weed hosts in relation to virus concentration in the host plants. Compare competition between BMCTV and BSCTV with newly identified variant curtovirus isolate to determine potential impact on tomato production.

Prior to the beginning of this project, our laboratory had developed molecular methods for differentiation of curtovirus species from single and mixed infections. This was done through a method known commonly as PCR (abbreviation for “polymerase chain reaction’). These primers allow us to determine whether one or more than one curtovirus is present in a plant, but do not allow determination of virus concentration. During the first year of this project we designed and successfully tested quantitative (real-time) PCR primers (qPCR primers) which allow not only differentiation among curtoviruses, but also determination of concentration of specific viruses from lab and field samples. These new primers (also known as TaqMan Probes) allow specific determination of the concentration of each virus, even during mixed infections of multiple curtovirus species, and are now being used in studies to quantify accumulation of different curtovirus species among the target hosts identified above.

Our laboratory maintains a population of beet leafhoppers, used for studies on curly top, as well as isolates of both BMCTV and BSCTV. In laboratory and greenhouse experiments, BSCTV and BMCTV were established as single and mixed infections in several efficient host plant species, including sugarbeet, tomato, bean, London rocket, and shepherd’s purse. Each experiment involved inoculation of 4 to six plants each in single or mixed infection, and with the exception of sugarbeet, experiments were only counted if single infection controls and mixed infections were successfully established. This resulted in several incomplete experiments; however, eventually we established sufficient rates to allow reliable analysis. Infections were confirmed at 3 weeks post-inoculation using traditional PCR, verifying either single or mixed infection. This was necessary because quantitative PCR (qPCR) is a much more expensive endeavor, and we did not wish to perform qPCR unless we know the plant is of interest based on its infection status due to budget constraints. Once single and mixed infections were confirmed, plant extracts were tested by qPCR to determine the concentration of BSCTV and BMCTV in single and mixed infections in individual plants of each host, with results summarized in Figure 1. Plants with single infections along with selected plants with mixed infections were subsequently used for transmission experiments. Ten to twelve virus-free leafhoppers were placed in clip cages for virus acquisition feeding on source plants for 48 hours, then transferred to test plants for inoculation feeding for an additional 48 hours. The 48 hour time period allows for hoppers to settle on the plant and feed sufficiently to acquire or transmit virus. The goal is to determine the impact of virus concentration on efficiency of transmission by beet leafhopper, as well as impact of the host plant itself. This will clarify some of the important factors impacting curly top transmission in the field and provide information on which hosts are of greater significance as virus reservoirs for transmission.

Essentially we are attempting to determine if transmission is related more closely to virus concentration in the host plant, with the more highly accumulated virus being transmitted preferentially as we anticipate; however, there is no guarantee this is always the case as other factors related to host or vector preference could impact transmission.

California Tomato Research Institute ~ 2012 Annual Report 75

This could indicate how a curtovirus may become dominant in its ecological niche, if it is able to out-compete other viruses. These studies will indicate if such occurrences happen in California. Interestingly, data to date as presented in Figure 1 suggest variation by host, with BMCTV dominating mixed infections in bean and shepherd’s purse (Fig. 1 A&B), and to some extent tomato (Fig. 1D); whereas BSCTV dominates in sugarbeet (Fig. 1C).

Interestingly we observed very limited mixed infections in tomato, and when mixed infections did occur, levels of both viruses were reduced compared to single infections. The ability to establish mixed infections it tomato seemed to be related to tomato cultivar, as multiple tests with the variety, SRT, did not yield mixed infections, whereas an older variety propagated by our lab (Tomato3) was able to maintain some mixed infections (Fig. 1D). This difficulty to establish mixed infections in tomato was an unanticipated occurrence and limited our numbers for analysis. Similarly, it was difficult to establish BMCTV infection of sugarbeet (Fig. 1C), a result consistent with previous information that BMCTV is mild on sugarbeet and much less aggressive in establishment on this host than BSCTV. Interestingly, BSCTV seems to not establish well on London rocket (data not shown), suggesting perhaps that infection of London rocket may be exclusively by BMCTV. Consequently follow up studies on transmission were not performed on London rocket.

Transmission From Mixed Infections Favors the Higher Titer Virus, but there are Exceptions. To summarize, we have confirmed previous work demonstrating that some host plants, such as bean and shepherd’s purse accumulate BMCTV better than BSCTV, while others such as sugarbeet, accumulate BSCTV better, as noted above. Tomato accumulates BMCTV better than BSCTV, but both viruses readily accumulate in tomato and it remains unclear how this influences transmission since establishment of mixed infections in this host has been more challenging as noted above, being somewhat variety-specific. Interestingly, transmission studies from some infected source plants have closely reflected the concentrations of the virus population in those source plants. Transmission from mixed infection in shepherds purse resulted in 93% transmission of BMCTV and only 20% transmission of BSCTV. This is certainly not surprising since levels of BMCTV in co-infected shepherds purse are many times higher than for BSCTV (Fig. 1B). Transmission from mixed infections in tomato were virtually identical with 55% transmission of each virus from mixed infections. This is surprising, since levels of BMCTV are higher in mixed infections in tomato, yet both viruses transmit from mixed infections with equal efficiency. It should be noted that in tomato we only had five mixed infections to base these results on as initial studies in the variety SRT did not produce mixed infections in any of the initial tests. When we changed varieties to an older lab propagated variety known as Tomato #3 we were able to generate some mixed infections, but numbers were low. It is possible results would change with a larger sample set, and this will require further study to determine if equal transmission from plants in which BMCTV dominates mixed infections is the standard or an anomaly. Similar results were obtained for sugarbeet, in which both BMCTV and BSCTV were transmitted with 71% efficiency from mixed infections even though BSCTV accumulates much better in this host plant during mixed infections. With sugarbeet the difficulty was establishing infection with BMCTV in both single and mixed infections using transmission by beet leafhopper.

California Tomato Research Institute ~ 2012 Annual Report 76

These results indicate tomato and sugarbeet do not favor one virus over the other when acting as a source for transmission, even though virus titer in tomato and sugarbeet clearly favors one virus over the other. This suggests the relationship between virus titer in the source plant and transmission to new hosts may be a host plant-specific relationship. Although we are not requesting additional funds for this project some work will continue to clarify relationships in the latter two hosts.

Figure 1. Effect of single and mixed curtovirus infections on accumulation of BSCTV and BMCTV in different host plants. Note: Numbers on x (left side) axis are in mean log copy number (amount of virus).

A. Effect of single and mixed curtovirus infections on accumulation of BSCTV and BMCTV in bean (Phaseolus vulgaris). Vertical axis = mean log copy number.

9.00 8.00 7.00 6.00 5.00 4.00 3.00 Single Infection Single Infection Mixed Infection Mixed Infection BSCTV n=14 BMCTV n=14 BSCTV n=14 BMCTV n=14

B. Effect of single and mixed curtovirus infections on accumulation of BSCTV and BMCTV in Shepherd’s purse (Capsella bursa-pastoris). Vertical axis = mean log copy number.

9.00

8.00

7.00

6.00

5.00

4.00

3.00 Single Infection Single Infection Mixed Infection Mixed Infection BSCTV n=20 BMCTV n=20 BSCTV n=20 BMCTV n=18

California Tomato Research Institute ~ 2012 Annual Report 77

C. Effect of single and mixed curtovirus infections on accumulation of BSCTV and BMCTV in Sugarbeet (Beta vulgaris).

9.00

8.00

7.00

6.00

5.00

Average Log Copy Number 4.00

3.00 Single Infection Single Infection Mixed Infection Mixed Infection BSCTV (n=9) BMCTV (n=9) BSCTV (n=9) BMCTV (n=9)

D. Effect of single and mixed curtovirus infections on accumulation of BSCTV and BMCTV in Tomato (Solanum lycopersicum). Vertical axis = mean log copy number.

9.00

8.00

7.00

6.00

5.00

4.00

3.00 Single Infection Single Infection Mixed Infection Mixed Infection BSCTV (n=18) BMCTV (n=10) BSCTV (n=5) BMCTV (n=5)

California Tomato Research Institute ~ 2012 Annual Report 78

Objective 3. Complete studies on incidence and concentration of specific curtoviruses in weed and crop hosts.

Sampling of weed and crop hosts for curly top yielded very low curtovirus incidence again in 2011. After two springs of very low curly top incidence in the field (spring 2010 & 2011), we decided to focus our analysis of virus incidence and emergence in the field studies on archived weed samples available from a previous study (and maintained in storage at -80C), along with the limited number of new samples from the field since it became apparent that significant numbers of infected field samples were not available due to low virus incidence in recent years. PCR was used to determine the presence of a curtovirus in each sample, after which a subset of the isolated nucleic acid samples were used for sequence analysis, followed by comparison with known viruses to identify the closest genetic relatives of the field isolates. Results demonstrated an abundance of both BSCTV and BMCTV, but a limited number of samples matched recently described curtoviruses that were only recently identified in California (PepCTV) or have not yet been identified (PYDV) in California (Table 3). It should be noted that only a species-specific region of the genome was analyzed in these studies. Follow-up analysis of the samples with sequence of unusual curtovirus species will be necessary, and studies to date suggest that the isolate from sugarbeet listed as PepCTV in Table 3, referred to in last year’s report is actually a recombinant virus in which the region analyzed initially by PCR matched PepCTV, but other portions of the genome were more closely related to BSCTV. This was determined by sequencing additional portions of the genome. Similar analyses will be needed on the PYDV isolates. Even if the latter occurred it is interesting that the sequence occurred in California at all since PYDV has only been identified in New Mexico to date. Although PepCTV has been reported in California, it is not yet common in the state.

The findings in Table 3 illustrate the importance of continued periodic monitoring for variation in the curtovirus population in California, as these or other viruses may emerge to compete with BMCTV and BSCTV resulting in a shift in population and perhaps new issues in management such as shifts in severity of virus on tomato or other crops.

California Tomato Research Institute ~ 2012 Annual Report 79

Table 3. Identification of curtovirus species from a range of weed and crop host plants from San Joaquin Valley, California by DNA sequence analysis of select isolates

Plants Collected from Fields #Pos/#Total* Sequence Analysis**

Amaranthus retroflexus (redroot pigweed) 5/16 2 BMCTV, 1 BSCTV Bassia hyssopifolia (five hook bassia) 6/26 3 BMCTV Sisymbrium irio (London rocket) 9/28 1 BMCTV, 1 BSCTV Chenopodium album (lambsquarters) 4/16 2 BMCTV, 1 Mix Chenopodium murale (nettle leaf goosefoot) 7/24 2 BMCTV, 2 BSCTV, 1 Mix Portulaca oleracea (purslane) 5/13 3 BMCTV, 1 Mix Atriplex sp. (saltbush) 8/27 2 BMCTV, 1 BSCTV Amaranthus blitoides (prostrate pigweed) 6/21 2 BMCTV, 1 BSCTV Five-Horned Smotherweed 1/1 NT Fogweed 1/19 NT Brassica sp. misc. mustard 5/16 1 BMCTV, 1 PYDV, 1 Mix Capsicum annuum (pepper) 1/1 NT Tribulus terrestris (puncture vine) 6/14 1 PYDV Salsola tragus, etc. (Russian thistle) 8/25 4 BSCTV Capsella bursa-pastoris (shepherd’s purse) 1/6 1 BMCTV, Beta vulgaris (sugarbeet) 6/10 2 BMCTV, 3 BSCTV, 1PepCTV Solanum lycopersicum (tomato) 5/13 2 BMCTV

TOTALS 23/43 BMCTV 13/43 BSCTV 4/43 Mixed infection 2/43 PYDV 1/43 PepCTV

* Not all positives were sequenced ** BSCTV = Beet severe curly top virus, BMCTV = Beet mild curly top virus, PepCTV = Pepper curly top virus, PYDV = Pepper yellow dwarf virus, Mix = mixed population

Our initial efforts at obtaining a California Specialty Crops Block Grant made round two but was not funded in 2012.

Financial support of the California Tomato Research Institute and CDFA-Curly Top Control Program and are greatly appreciated!

California Tomato Research Institute ~ 2012 Annual Report 80

Project Title: Movement of Fusarium Oxysporum Via Equipment

Project Leader(s): Gene Miyao UC Cooperative Extension 70 Cottonwood Street, Woodland, CA 95695 Phone: (530) 666-8732 [email protected]

Mike Davis CE Specialist Dept. Plant Pathology, UC Davis 1 Shields Ave, Davis, CA 95616

Results: The level of Fusarium wilt infection nearly tripled from the 2011 initial infestation level. Clearly, Fusarium oxysporum established quickly and spread readily.

Objectives: Evaluate establishment and movement of Fusarium oxysporum in causing Fusarium wilt from diseased tomato tissue introduced into non-infested soil.

Procedures: Race 3 of Fusarium wilt diseased tomato plant tissue was collected from 2 commercial fields in late 2010. Dry stem pieces were buried about 6 inches deep in the center of established beds in late 2010 in a non-infested soil at a UC Davis Plant Pathology field research facility. The plot design was a randomized complete block with 4 replications. The plot area was a single, 5-foot centered bed by 90 feet long. The Fusarium infested plant tissue was placed 30- foot away from the headland of each row. A tomato planting in the infested soil was initiated in 2011. Twelve plants were diseased with Fusarium wilt by season’s end. The following year in 2012, a second consecutive year of tomatoes were grown. Plants were tagged when symptoms developed and all flagged plants were sampled to send suspect diseased tissue to the lab for confirmation.

Results: A total of 34 plants were lab confirmed to be diseased with Fusarium wilt from the test plot. Disease incidence was not closely tied to initial introduced inoculum level.

California Tomato Research Institute ~ 2012 Annual Report 81

Discussion: Our field study indicates that Fusarium wilt can establish relatively quickly in a new soil environment and infect the follow season.

The results suggest equipment especially tomato harvesters and vine diverters should be cleaned and inspected before moving into new fields. Vigilance in equipment cleaning may reduce the introduction of Fusarium wilt from fields where Fusarium wilt is present. While our study only involved handling of diseased plant tissue, infested soil may also be tied to the movement of Fusarium wilt. We intend to replant to tomatoes in 2013. We expect to witness the continued spread of Fusarium as well as an increased level of infection.

California Tomato Research Institute ~ 2012 Annual Report 82

Project Title: Evaluation of Fungicides, Bio-Pesticides and Soil Amendments for the Control of Southern Blight in Processing Tomatoes

Project Leader: Joe Nunez Vegetable/Plant Pathology Advisor, UC Cooperative Extension 1031 So. Mount Vernon Ave., Bakersfield, CA 93307 Office: 661-868-622, Fax: 661-868-6208, Email: [email protected]

Co-Investigators: Mike Davis, Plant Pathology Specialist, Department of Plant Pathology University of California, Davis, CA 95616 Office: 530-752-0303, fax: 530-752-1199 Email: [email protected]

Four separate trials where conducted in a Kern County grower’s tomato field that was heavily infested with Sclerotium rolfsii. The trials consisted of: 1) Metam Sodium Fumigation, 2) Fungicide, 3) Lime and 4) Variety trials. Once southern blight developed each trial was evaluated on a weekly schedule. Evaluations included of number of symptomatic plants per plot, percent of plot infected with southern blight and overall canopy chlorophyll readings with a chlorophyll meter (data from chlorophyll meter not shown due to bindweed overgrowth).

Metam Fumigation Trial The objective of this study was to determine if lower rates of metam sodium applied by roto-vate and roll implement could be used to reduce southern blight infection. The roto-vate and roll implement only applies the metam sodium in the top 6-8 inches of soil where the active sclerotia of S. rolfsii reside.

Metam sodium was applied using a single row roto-vate and roll bed shaper (see photo 1). It consisted of a 48 inch roto-tiller with bed shapers attached to a wrap around frame with a roller on the back. A spray boom was placed in front of the tiller’s tines and a spray tank and pump were mounted onto the implement. This implement was also used to incorporate all other materials in the fungicide and lime trials (see photo 2).

Application rates were 44, 33 and 21 gallons of metam per acre along with a non-treated control. After 3 weeks seedlings were planted using the grower’s normal transplanting methods. Plots were monitored during the season and weekly evaluations were made once southern blight infections appeared.

Metam Trial Summary Metam fumigation by roto-vate and roll did not significantly reduce the number of strikes and rate of infection as compared to the non-treated control (table 1). The 33 gallon per acre rate was actually more efficacious than the higher rate of 44 gallons per acre.

California Tomato Research Institute ~ 2012 Annual Report 83

Table 1. Number of strikes and percent plot infected in metam fumigation trial. Treatment # of Strikes % Plot Infested 1. Control 4.8 36.7 2. Metam 44 gals/A 4.2 28.3 3. Metam 33 gals/A 2.7 17.5 4. Metam 21 gals/A 4.2 25.8 Prob= 0.5944 0.4584 % CV= 70.29 74.71

LSD p=0.05 NS NS

Figure 1. Percent of plot infected with southern blight in metam fumigation trial.

Fumigation Trial-Percent Infection

40

35

30

25 Percent Infection 20 with S. rolfsii

15

10

5

0 1. Control 2. Metam 44 gals/A 3. Metam 33 gals/A 4. Metam 21 gals/A

Figure 2. Number of plants infected with southern blight per plot in metam fumigation trial.

Fumigation Trial-# of Strikes per 30 ft

5 4.5 4

3.5 3

# of strikes per 30 ft 2.5

2 1.5

1 0.5 0 1. Control 2. Metam 44 gals/A 3. Metam 33 gals/A 4. Metam 21 gals/A

California Tomato Research Institute ~ 2012 Annual Report 84

Fungicide Trial The goal of the fungicide trial was to identify any fungicide that may have prolonged residual activity, that is also effective in the control of S. rolfsii. Getting timely fungicide applications to the soil surface in processing tomatoes is difficult under current growing practices due to developed plant canopies at the time when southern blight becomes an issue. Therefore if fungicides are to be used, they need to be applied in the early stages of crop growth.

The fungicides fludioxonil (Cannonball), tebuconazole (Orius), azoxystrobin (Quadris) and penthiopyrad (Fontellis) were applied to the soil surface and incorporated with the roto-vate and roll implement just prior to transplanting. Penthiopyrad and azoxystrobin were also applied using a super absorbent polymer (SAP), Zeba and incorporated into the soil. The objective was to determine if an SAP laced with a fungicide, would provide a slow release functionality for the fungicide.

Literature from previous studies have indicated that certain compounds could stimulate sclertotia of S. rolfsii to germinate without the presence of a host plant. Black strap molasses was one compound that was identified as having these properties and is readily available. The objective was to confirm (or contest) that these earlier findings using black strap molasses. In theory, if successful, the S. rolfsii would germinate and deplete itself, thus reducing sclerotia population levels. Black strap molasses was tested alone, and in combination with penthiopyrad (Fontellis).

Fungicide Trial Summary Penthiopyrad showed the greatest reduction in incidence of southern blight, followed by fludioxinil and azoxystrobin. These numbers, however, were not significant from the non- treated control - again likely due to the variability of the disease. Results from the SAP trial seemed to indicate that Zeba “ties up” the fungicides, as they did not get released and performed poorly. The same was true with the black strap molasses, which also did not provide any benefit.

Table 2. Results of fungicide trial Treatment # of Strikes % Plot Infested 1. Control 7.5 57.5 2. fludioxonil 5.3 42.5 3. tebuconazole 7.3 62.5 4. azoxystrobin 4.5 42.5 5. azoxystrobin/SAP 6.8 67.5 6. penthiopyrad 4.0 35 7. penthiopyrad/SAP 6.3 70 8. molasses 5.3 52.5 9. molasses/penthiopyrad 6.0 52.5 Prob= 0.7284 0.4481 % CV= 51.04 44.32 LSD p=0.05 NS NS

California Tomato Research Institute ~ 2012 Annual Report 85

Figure 3. Percent of southern blight infection - Fungicide Trial

Fungicide Trial-Percent Infection

70

60

50

40 Percent Infection 30

20

10

0 control fludioxonil tebuconazoleazoxystrobinazoxystrobin/Zebapenthiopyradpenthiopyrad/ZebaMolasses Molasses/penthiopyrad

Figure 4. Number of southern blight strikes - Fungicide Trial

Funicide Trial-# of Strikes per 30 ft

8 7 6 5 # of Strikes/30 ft 4 3 2 1 0 control fludioxonil tebuconazoleazoxystrobin azoxystrobin/Zebapenthiopyrad penthiopyrad/ZebaMolasses Molasses/penthiopyrad

California Tomato Research Institute ~ 2012 Annual Report 86

Lime Trial Increasing soil pH is a common practice in the management of southern blight for several crops, particularly peanuts. Sclerotium rolfsii does not grow well at pH 7 or above, thus increasing soil pH is potentially an effective a method of reducing southern blight infections. The objective of this trial was to determine the validity of that theory by increasing soil pH with lime, as well as combinations of lime and other products.

In the previous year, chicken manure proved effective in being to be able to reduce southern blight infection. For this trial it was used alone and in combination with lime. The biological product, Serenade Soil was also used both alone, and in combination with lime. Lastly two fungicides, penthiopyrad (Fontellis)and boscalid (Endura), were combined with lime to determine if disease control by efficacious fungicides could be enhanced by the addition of lime.

Lime was added at a rate of 3 tons per acre. It and all other products were incorporated with the roto-vate and roll implement before planting.

Lime Trial Summary The greatest disease reduction was observed with the combination of lime and penthiopyrad; southern blight was reduced to undetectable levels with this combination. Chicken manure, at 8 tons per acre, reduced southern blight incidence and severity. Lime alone also reduced the impact of southern blight. The differences, however, were not statistically significant in this trial. Again - the variability of the disease makes it difficult to get significant differences - even in replicated trials.

Table 3. Results of lime trial Treatment # of Strikes % Plot Infested 1. Control 2.5 22.5 2. Lime 2.0 16.3 3. Lime & penthiopyrad 0.0 0.0 4. Chicken Manure 1.3 15.0 5. Lime & Chicken Manure 1.8 22.5 6. Serenade Soil 2.0 22.5 7. Lime & Serenade Soil 2.3 20.0 8. Boscalid 4.0 35.0 9. Lime & boscalid 2.5 25.0 Prob= 0.1328 0.1193 % CV= 79.37 69.9

LSD p=0.05 NS NS

California Tomato Research Institute ~ 2012 Annual Report 87

Figure 5. Percent of southern blight infection - Lime Trial

Lime Trial-Percent Infection

35

30

25

20 Percent Infection with S. rolfsii 15

10

5

0 1. Control 2. Lime 3. Lime & Fontelis4. Chicken Manure5. Lime & Chiken6. Serenade Manure Soil7. Lime & Serenade8. Endura Soil 9. Lime & Endura

Figure 6. Number of southern blight strikes - Lime Trial

Lime Trial- # of strikes 4

3.5 3

2.5 # of strikes per 30 ft 2 1.5 1 0.5 0 1. Control 2. Lime 3. Lime & Fontelis4. Chicken Manure5. Lime & Chiken6. Serenade Manure 7.Soil Lime & Serenade8. Endura Soil 9. Lime & Endura

California Tomato Research Institute ~ 2012 Annual Report 88

Variety Trial Using transplants from the mid-season variety trial of the Statewide Processing Tomato Variety Trial, one replication was planted as an observation trial. The objective was to see if there were any differences in susceptibility to southern blight among processing tomato varieties.

Variety Trial Summary There were great differences in susceptibility among the varieties tested, with percentages ranging from 10% to 90% infection. The variety N 6402 had the least amount of disease while HM 9905 and SUN 6366 also had notably low amounts of loss to the disease.

Table 4. Results of variety trial Treatment # of Strikes % Plot Infested 1. AB 0311 9 60 2. AB-2 (STD) 3 30 3. BQ 163 7 60 4. BQ 205 4 40 5. DRI 0319 4 30 6. H-5508 6 60 7. H-5608 3 60 8. H-9780 (STD) 8 70 9. HM 9905 3 20 10. N 6402 2 10 11. N 6404 10 80 12. PX 024 8 1245 4 50 13. SUN 6366 (STD) 1 20 14. UG 19006 3 50 15. UG 19306 11 80 16. UG 19406 10 90

California Tomato Research Institute ~ 2012 Annual Report 89

Figure 7. Percent of southern blight infection among selected tomato varieties

Variety Trial Percent Infection

90 80 70 60

Percent Infection 50 with S. rolfsii 40 30 20 10 0 1. AB 03112. AB-2 (STD)3. BQ 1634. BQ 2055. DRI 03196. H-55087. H-56088. H-97809. (STD) HM 990510. N 640211. N 640412. PX 02413. 8 1245 SUN 636614. UG (STD) 1900615. UG 1930616. UG 19406

Figure 8. Number of southern blight strikes among selected tomato varieties

Variety Trial- # of Strikes per 30 ft

12

10

8

# of Strikes per 30 ft 6

4

2

0 1. AB 03112. AB-2 (STD)3. BQ 1634. BQ 2055. DRI 03196. H-55087. H-56088. H-97809. (STD) HM 990510. N 640211. N 640412. PX 02413. 8 1245SUN 14.6366 UG (STD) 1900615. UG 1930616. UG 19406

Conclusions Like most soil borne pathogens, southern blight is highly variable in the field. There are spots in the field that have a high concentration of sclerotia and other areas - often nearby, that have little to no sclerotia. Conducting field trials is impacted by this variability, making it difficult to see clear differences between treatments. This remains true with replicated trials such as these. The field experiments did not identify any one treatment that could significantly reduce southern blight.

The major benefit resulting from these trials is an indication that there are materials which appear to reduce the incidence and severity of southern blight. The metam treated plots had less southern blight but was still present. So while metam sodium is the industry standard for disease control of S. rolfsii, this research shows that it does not completely eliminate it. For the third year in a row penthiopyrad proved it has the greatest efficacy for control of this disease.

California Tomato Research Institute ~ 2012 Annual Report 90

Azoxystrobin and fludioxonil did not look as promising as penthiopyrad but warrant further study.

Liming the soil, especially in combination with penthiopyrad, shows promise and may be a treatment with potential for disease suppression. Chicken manure, once again, showed that it has some positive effect, and may be a component of a successful disease control strategy.

The sixteen varieties in this observational trial showed great differences in severity of infection. Initial findings appear to show some differences in susceptibility among varieties, which could be used to grower’s benefit. This was, however, only an observational trial, and southern blight is known to be sporadic in its field distribution. So caution should to be applied when interpreting the data.

The most promising information gained from these trials is that simply choosing the the best, resistant variety for fields known to be infested will S. rolfsii, may be the best option in a management/control strategy against southern blight.

Lastly, we were able to fulfill the goal of assembling a new tool that can be used to apply and incorporate various products so we can easily evaluate them for disease suppression. The one row, “roto-vate and roll” implement is a success, and has been used in this and other tomato trials - and will be incorporated into the process for future tomato trials.

Photo 1. Application of metam sodium with “roto-vate and roll” implement

California Tomato Research Institute ~ 2012 Annual Report 91

Photo 2. Incorporation of lime and chicken manure

California Tomato Research Institute ~ 2012 Annual Report 92

Project Title: Influence of Drip Irrigation on Tomato Root Health

Project Leaders: Mike Davis Cooperative Extension Specialist, Department of Plant Pathology One Shields Ave, University of California, Davis, CA 95616 Phone: 530-752-0303 Email: [email protected]

Johan Leveau Assistant Professor, Department of Plant Pathology One Shields Ave, University of California, Davis, CA 95616 Phone: 530-752-5046 Email: [email protected]

Gene Miyao Cooperative Extension Farm Advisor, Yolo-Solano-Sacramento counties 70 Cottonwood Ave., Woodland, CA 95695 Phone: 530-666-8732 Email: [email protected]

Objectives: 1. Determine the effect of drip irrigation on root health, root and soil microflora, and tomato fruit yield and quality. 2. Evaluate the efficacy of composted animal manures and drip tape-delivered fungicides and biocontrol agents on the management of soilborne pathogens of tomato.

Abstract: Experiments were conducted in two Yolo County commercial fields using buried drip irrigation. In one location, K-pam was applied through the drip tape to two treatments 5-7 weeks before planting. In one of the treatments with K-pam, Serenade Soil was injected into the drip tape four times during the season. Three applications of a combination of Quadris and Ridomil, four applications of Serenade Soil, four applications of potassium sulfate, and four applications of Actinovate, all applied through the drip tape, were included. In the other location, identical treatments were applied with the exception of Actinovate. At both locations, treatments included pre-plant-incorporation of chicken manure at 10 or 20 tons/A. The second location received an additional treatment with a different source of chicken manure. Periodically, soil cores were collected from each plot. Verticillium propagules and total culturable fungi and bacteria were enumerated. DNA was extracted for later determination of soil microbial community structure and pathogen inoculum levels. Disease incidence was assessed prior to harvest. Samples were processed in the lab for determination of disease-causing organisms in stems. At one site, Verticillium wilt was widespread. At the second site, root knot nematode was prevalent; Verticillium and Fusarium wilts as well as Fusarium crown and root rot were common. Yields were generally increased in the plots with incorporated chicken manure but the incidence of disease was generally not affected by any treatment.

California Tomato Research Institute ~ 2012 Annual Report 93

Procedures: Objectives 1 and 2. Drip irrigation and root health. Experimental setup Field trials were set up in two commercial processing tomato fields. Both fields were drip- irrigated and had a history of disease. Site 1 was northeast of Woodland, CA; site 2 was southwest of Woodland. Site 1 was planted with transplants of Sun 6366 late April and was harvested mid-August; site 2 was planted with HyPeel 849 mid-May and harvested late September. We used a randomized complete block design for our trials, with one treatment per block and four replicated blocks. Each replicated treatment included one 100-ft section of a planted row. Fungicides and biological materials were drip applied three to six times at three week intervals starting at planting; the composted chicken manures were incorporated before planting; K-Pam was applied before planting; and Potassium was applied weekly (4 times) starting at fruit set.

Treatments Site 1 Site 2 Control Control Quadris and Ridomil Quadris Ridomil Serenade Soil Serenade Soil Manure 10T Manure 10T Manure 20T Manure 20T K-pam and Serenade K-pam and Serenade K-pam K-pam Potassium multiple Potassium multiple Actinovate Compost 10T, different source

Rates Treatment Rate per acre K-pam 15 gallons Actinovate 340 g Quadris 183 ml Ridomil Gold 473 ml (3 applications) Serenade Soil 5678 ml

Potassium 50 lb Composted chicken manure 10 or 20 tons

Soil sampling Six bulk soil cores, each 1 inch in diameter and 12 inches in length were randomly taken from each replicated treatment, one time before application of the treatment and then three times at six week intervals throughout the season.

California Tomato Research Institute ~ 2012 Annual Report 94

All six soil cores from each replicated treatment were hand homogenized into one composite sample and saved at -20°C for DNA extraction. A portion of the composite sample was also air dried at room temperature for Verticillium isolations. Rhizosphere soil samples were collected from 12-13 plants in the harvest area.

Disease assessment Disease incidence in our experimental blocks was rated once during the season at both sites. Final disease severity was rated for both sites before harvest. Tissue isolations were made on semi-selective media to confirm visual ratings. At harvest, roots were dug from the 11 ft hand harvested area. These roots were washed, rated for symptoms, and samples were plated onto semiselective media.

Microbiota Analysis For all soil samples, we have samples saved at -20C. Soils from select time points were taken for isolation of total culturable bacteria and fungi. Work on the culture independent analysis of the soil samples remains ongoing. We are currently extracting DNA from our soil samples in preparation for microbial community analysis using Illumina sequencing, a high throughput method for sequence based identification of microbial taxa. We will be looking at both bacterial and fungal communities in our soils.

Harvest Both sites were hand harvested. Harvest area was a 11 ft long section of the treated tomato bed that had been minimally disturbed during the season. Harvested fruit were divided into the following categories, (i) marketable, (ii) pink, (iii) green, (iv) sun burnt, and (v) mold. A sample of the fruit was also taken for quality analysis.

Results:

Table 1. Marketable yield and biomass, tons per acre, Site 1. % sun % # of yield Treatment apps. tons biomass burn mold Control - 39.4 b 44.1 b 3 2 Quadris Ridomil 3 40.0 b 46.1 b 3 2 Serenade Soil 5 39.7 b 44.1 b 3 2 Manure 10T 1 55.7 a 61.0 a 2 1 Manure 20T 1 61.1 a 65.4 a 2 0 K-pam and Serenade 5 41.5 b 48.2 b 3 2 K-pam 1 43.9 b 49.1 b 2 1 Potassium multiple 4 38.0 b 43.4 b 4 1 Actinovate 5 37.7 b 43.2 b 4 2 LSD @ 5% 7.2 7.2 1.3 NS % CV 11.2 10.0 31 53

California Tomato Research Institute ~ 2012 Annual Report 95

Composted chicken manure resulted in about 50% greater yields than the non- treated control (39.4 tons/acre). Foliar necrosis was also reduced in the pots that received chicken manure by about half (data not presented). No other treatment influenced foliar symptoms. There was no reduction in the incidence of Verticillium wilt based on tissue isolations. The incidence in our trial area was greater than 94%. The other apparent disease at this location was tomato spotted wilt virus with an incidence of about 2%.

In the row at the right, composted chicken manure at the rate of 20 tons/acre was incorporated prior to planting. Yields were increased about 50% with manure.

Table 2. Group comparisons, site 1 Yield Color Brix pH Sunburn % Green % Mold % Control vs 39.4 25.5 5.25 4.28 3.0 6.0 1.9 Manures 58.4 24.6 5.48 4.27 1.7 5.2 0.8 Probability 0.00 NS 0.03 NS 0.02 NS 0.05

Control vs 39.4 25.5 5.25 4.28 3.0 6.0 1.9 Fungicides 39.7 27.0 5.22 4.30 3.2 7.3 2.1 Probability NS 0.04 NS NS NS NS NS

Control vs 39.4 25.5 5.25 4.28 3.0 6.0 1.9 K-pam 42.7 27.0 5.19 4.30 2.8 7.6 1.8 Probability NS 0.05 NS NS NS NS NS

California Tomato Research Institute ~ 2012 Annual Report 96

Composted poultry manure applications on the top of the bed ahead of spring tillage increased fruit yields from 40 tons per acre to 55-60 tons, increased Brix slightly, and slightly reduced sunburn and mold, perhaps due to better canopy cover protecting fruit.

Table 3. Mineral analysis, whole leaf tissue samples from select treatments, Site 1. Near full Early Near flowering ripening harvest Manure %N % P % K %N % P % K %N % P %K Control 4.47 0.39 2.55 3.36 0.23 0.94 2.15 0.18 0.41 10 tons 4.67 0.42 2.83 3.36 0.22 0.95 2.28 0.21 0.43 20 tons 4.84 0.49 3.13 3.47 0.24 1.12 2.27 0.19 0.43 K - - - 3.45 0.23 1.19 2.14 0.18 0.43 LSD 5% NS 0.034 0.364 NS 0.11 0.11 0.10 0.10 NS CV% 4 5 7 3 4 15 3 8 6

Group comparisons Control vs 4.47 0.39 2.55 3.36 0.23 0.94 2.15 0.18 0.41 manure 4.75 0.45 2.98 3.42 0.23 1.04 2.27 0.20 0.43 Probability 0.06 0.00 0.02 NS NS NS 0.01 0.09 NS

NPK levels were all statistically significantly greater (or nearly so) at full flowering in plants grown in plots that received chicken manure relative to the controls, but were similar at the fruit ripening stage. At harvest, N tissue levels were slightly higher in the manure treatments, but P and K levels were not different than the control. Chemigation with potassium sulfate did not change K tissue levels. Overall, the NPK levels of the plants were within acceptable ranges and plant nutrition alone apparently cannot account for the yield gains due to the chicken manure.

Table 4. Marketable yield and biomass, tons per acre, Site 2. # of yield fruit % sun % Treatment apps. tons/A biomass Burn mold Control - 42.5 51.2 9 4 Quadris Ridomil 3 43.3 51.9 8 3 Serenade Soil 4 40.7 49.1 7 6 Manure 10T 1 55.2 65.4 5 4 Manure 20T 1 40.0 49.3 12 4 K-pam and Serenade 4 38.2 44.7 10 3 K-pam 1 39.9 49.8 11 6 Potassium 6 41.4 49.1 8 5 Manure 10T, source 2 1 44.8 52.6 9 3 LSD @ 5% NS NS NS NS % CV 22 19 54 44

California Tomato Research Institute ~ 2012 Annual Report 97

Table 5. Group comparisons, site 2 Yield Color Brix pH Sunburn % Green % Mold % Control vs 42.5 23.3 4.9 4.37 8.8 3.2 3.8 Manures 46.7 23.6 4.7 4.40 8.7 2.1 3.7 Probability NS NS NS NS NS NS NS

Control vs 42.5 23.3 4.9 4.37 8.8 3.2 3.8 Fungicides 40.7 23.8 4.8 4.30 8.4 2.2 4.1 Probability NS 0.04 NS NS NS NS NS

Control vs 42.5 23.3 4.9 4.37 8.8 3.2 3.8 K-pam 39.0 23.5 4.7 4.37 10.8 1.1 4.3 Probability NS NS NS NS NS 0.10 NS

Table 6. Disease assessment, site 2 14-Sep 26-Sep leaf leaf # of necrosis necrosis Treatment apps. % % Control - 50 71 Quadris Ridomil 3 65 71 Serenade Soil 4 69 61 Manure 10T 1 36 51 Manure 20T 1 54 70 K-pam and Serenade 4 61 74 K-pam 1 61 77 Potassium multiple 6 46 54 Manure 10T, source 2 1 43 64 LSD @ 5% NS NS % CV 35 30

There was no significant difference between treatments for marketable fruit yield, biomass or any of the measured fruit quality characteristics at site 2. No treatment affected premature vine decline. At harvest, about 60% of the plants in our trial area had died. Root knot nematode pressure was high. Fusarium and Verticillium wilts and Fusarium crown and root rot were also present. None of the treatments affected the incidence of these diseases.

California Tomato Research Institute ~ 2012 Annual Report 98

Table 7. Mineral analysis, whole leaf tissue samples from select treatments, Site 2. early ripening Treatment %N % P % K Control 3.06 0.19 0.75 10 tons 3.13 0.18 0.80 20 tons 3.35 0.19 0.81 K 3.23 0.19 0.94 10 tons, source 2 3.14 0.18 0.70 LSD 5% NS NS NS CV% 5 8 19

Group comparisons Control vs 3.06 0.19 0.75 manure 3.21 0.18 0.77 Probability NS NS NS

There was no increase in NPK levels in leaves of plants from plots treated with chicken manure or by the addition of potassium.

Microbiota We plated for total culturable bacteria, fungi, and Fusarium oxysporum from select time points. On average we recovered: bacteria, 1.65 x 107 cfu/g dried soil and fungi, 4.8 x 105 cfu/g dried soil. Their culturable populations did not significantly vary between treatments at multiple time points. We are currently prepping our soil samples for microbial community analysis using Illumina sequencing. Results from this work will be reported at a later date.

Discussion: We observed a yield increase of about 50% with incorporated chicken manure at one site. Similar trends were observed last season. This season tissue analysis did not explain the increase in yield with manure because NPK levels in the nontreated plots were not deficient. Apparently, NPK contributed by the manure didn’t fully account for the dramatic yield increase at site 1. However, it is unclear if the yield increase was due to pathogen suppression. At site 1, there was no detectable difference in Verticillium wilt incidence between the manure and non-treated control plots. But disease incidence may not correlate with disease severity, and the degree or timing of colonization by Verticillium may affect plant growth and yields. To better understand this dynamic, we propose to examine this interaction more carefully in greenhouse-based experiments.

Site 2 was heavily impacted by root know nematodes and there was a great deal of variability of plant responses across replications. The soil microbial community that underlies the yield and disease outcomes in our trials may be key to understanding the benefits of incorporated chicken manure.

California Tomato Research Institute ~ 2012 Annual Report 99

Over the past season we have gathered valuable bulk and rhizosphere soil samples from our treatment areas. We intend to soon sequence and analyze those communities for changes in patterns of bacterial and fungal communities and how they might correlate with plant health and yield responses. Of immediate interest to us will be how the microbial community in the manure- treated soil changes. And importantly, we will attempt to identify metrics that can be used to predict when a positive growth response to applications of manure will result.

California Tomato Research Institute ~ 2012 Annual Report 100

Project Title: Breeding for Resistance to Bacterial Speck and Monitoring California Pseudomonas syringae Strains

Principal Investigators: Gitta Coaker Associate Professor, Department of Plant Pathology University of California Davis Phone: 530-752-6541 E-mail: [email protected]

Gene Miyao Farm Advisor, Vegetable Crops Cooperative Extension Yolo County Phone: (530) 666-8732 E-mail: [email protected]

Introduction: Bacterial speck of tomato, caused by Pseudomonas syringae pv. tomato, can significantly impact plant health and lead to decreased yields, fruit symptoms that can pose problems for whole-peel processors, as well as plant death in seedlings. Traditionally P. syringae pv. tomato has been controlled by a combination of copper sprays and genetic resistance conferred by the tomato genes Pto and Prf (Pedley and Martin 2003). Pto and Prf are effective in mediating resistance against Race 0 strains. However, Race 1 strains were first detected in California in 2000 (Arredondo and Davis 2000). In 2005, 2010 and 2011, outbreaks of bacterial speck occurred (Kunkeaw, Tan et al. 2010). The PI (G. Coaker) has been monitoring field strains of P. syringae over the last four years and has found that almost all field strains are exclusively Race 1 and possess moderate to high levels of copper resistance (Kunkeaw, Tan et al. 2010). Bacterial speck of tomato has become an increasing problem in recent years in California due to a combination of favorable weather promoting disease development in 2010-2011, the emergence of race shifting strains, and moderate to high levels of copper resistance. Thus, the most viable form of disease control will be genetic resistance.

Identification of resistant S. peruvianum germplasm In this report, I have outlined our progress for the last two years of funding from the CTRI. In our first year of funding (2011), we verified that the wild tomato Solanum peruvianum and hybrids derived from it are resistant to current strains of Pseudomonas syringae pv. tomato, found that most strains of P. syringae pv. tomato exhibit moderate to high levels of copper resistance, and characterized the population structure and virulence of existing strains collected in California. Some wild species of tomato, in particular S. peruvianum, have increased resistance to P. syringae and the bacterial grow 10-20 fold less on these plants (Figure 1). Figure 1 illustrates the disease severity of the hybrids and controls after inoculation in the greenhouse with strain A9, a representative P. syringae strain isolated from the field in Northern California.

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We have quantified bacterial populations in tomato leaves after inoculation with P. syringae pv. tomato strains in the greenhouse. Our results demonstrate that the hybrids support 10 to 20-fold lower bacterial population sizes than susceptible controls.

Figure 1. S. peruvianum and derived hybrids exhibit resistance to P. syringae pv. tomato. Plant genotypes were dip inoculated with P. syringae pv. tomato and pictures were taken four days post-inoculation. S. esculentum PI204978 was initially crossed to S. peruvianum to generate the hybrids PI568258 and PI306812. S. esculentum cv. Bonnie Best is a susceptible control.

A field trial was also conducted in 2011. Prior to transplant in the field, all tomato genotypes were inoculated with a mixture of P. syringae pv. tomato strains A9 and 407. Disease severity was monitored over time. The results of the field trail indicate that the wild tomato species S. peruvianum as well as hybrids derived from S. peruvianum crosses are more resistant to bacterial speck under field conditions (Table 1).

Table 1. Statistical analyses of disease ratings in the field. Tomato plants were growth in the Least Mean Square Table greenhouse and inoculated with a mixture of Mean P. syringae pv. tomato strains A9 and 407 Genotype Least Sq Mean Separations one day prior to transplant in the field. Disease severity was rated once per week. A Bonnie Best 4.3478261 A higher incidence of disease is represented by a higher value. Disease rankings were PI 204978 2.6956522 B statistically analyzed using ANOVA followed by LSD mean separations. PI 586258 2.2222222 B C Genotypes that exhibit significantly different disease symptoms are denoted by different PI 306812 2.0833333 B C letters.

L. Peruvianum 1.5217391 C

Characterization of P. syringae strains for copper resistance, virulence, and phylogeny. We have also analyzed P. syringae strains isolated from infected tomato leaf tissue for their phylogeny and disease severity compared with other strains that were isolated over a decade ago. Representative P. syringae strains were inoculated onto Rio Grande 76R, which exhibits resistance to race 0 strains, but not race 1 strains.

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We found that, in general, representative California P. syringae strains were more aggressive than previously characterized strains, causing more severe disease symptoms and growing to higher population sizes inside susceptible plant leaves (Figure 2). Our phylogenetic analyses indicated that all California P. syringae strains are very closely related and cluster together (Figure 3). Furthermore, all strains were analyzed for their resistance to copper by growth on plates containing various concentrations of copper (cupric sulfate). One hundred different strains collected in California were tested and most exhibited moderate to high levels of copper resistance (0.2 to 0.8mM minimal inhibitory concentration of cupric sulfate). Collectively, these data indicate that current P. syringae pv. tomato strains can cause significant disease when environmental conditions are favorable and copper applications may not provide effective disease control in many circumstances. Thus, the most effective form of disease control would be genetic resistance.

Figure 2. Pseudomonas syringae pv. tomato strains isolated in California are hypervirulent compared with the control race 1 strain P. syringae T1. A. Four- week-old Rio Grande 76R tomato plants were dip inoculated with different P. syringae strains and subjected to growth curves 0 and 4 days post-inoculation. Strains 838-16, A9, and 19 were collected in California. Dip inoculations were performed at a concentration of 1 × 107 CFU/ml. Results are shown as the mean (n = 4), including standard deviation. Statistical differences were detected by Fisher’s least significant difference, α = 0.05. B. Picture of disease symptoms taken 4 days post-inoculation.

Figure 3. Pseudomonas syringae pv. tomato strains isolated in California are closely related to one another. The neighbor-joining tree was generated by sequencing five key housekeeping genes. A number of other P. syringae strains infecting other plants were analyzed for comparisons. Red arrows indicate where California strains cluster and the number of strains corresponding to each group is indicated in parentheses. Pto18 strains were found to be weak pathogens on tomato, but all other strains were found to be strong pathogens on tomato. Pseudomonas syringae pv. syringae B728A (PsyB728A) was used as the outgroup. Pto = P. syringae pv. tomato, Pan = P. syringae pv. antirrhini, Pma = P. syringae pv. maculicola, and Psy = P. syringae pv. syringae.

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Identification of S. habrochiates resistant germplasm. In the current funded year (2012), we have focused our efforts on (1) generating a mapping population to ultimately generate markers associated with resistance for S. peruvianum, (2) screening other wild tomato accessions with existing mapping populations in place for resistance to representative California race 1 P. syringae strains, and (3) Investigate the relatedness of Race 1 P. syringae pv. tomato strains collected from fields in 2011 and 2012.

With respect to the first objective, we had previously screened through a collection of wild germplasm for resistance and identified S. peruvianum and two hybrids as resistant to P. syringae pv. tomato (Figure 1, Table 1). Both are hybrids between processing tomatoes and the wild tomato species S. peruvianum, which have subsequently been self and open pollinated for 5 generations. Resistance is quantitative (not all or none) against California P. syringae strains A9 and 407. The germplasm exhibits less severe disease symptoms in the greenhouse and field as well as lower bacterial titers after inoculation in the greenhouse compared to parental controls (Figure 1, Table 1). Although the S. peruvianum hybrids exhibit resistance to P. syringae, they also obviously have significant amounts of “wild” DNA and exhibit an indeterminate growth habit, reduced germination, and small fruit size. In order to generate markers linked with resistance that can be used to introgress only the segments of DNA controlling resistance, we have crossed these hybrids to a variety of inbred processing tomato breeding lines that have performed well in California. We have obtained F1 seed.

As a secondary approach, we have screened other wild tomato accessions that already have existing inbred line populations. In addition to the susceptible cultivar Bonnie Best and the known resistant accession S. peruvianum, we screened three other wild tomato accessions: S. habrochaites, S. pimpinellifolium, and S. pennellii (Figure 4). An additional source of resistance from the wild tomato species S. habrochaites was identified (Figures 4-5). Importantly, this particular accession of S. habrochaites already has a set of recombinant inbred lines developed (Monforte and Tanksley 2000). Recombinant inbred lines (RILs) are made by crossing two inbred parents followed by many generations of selfing to produce a population with individuals that are homozygous mosaics of each parent’s genome. In this RIL population, there are 89 lines, each containing a different segment of S. habrochaites DNA with the remaining genome belonging to cultivated tomato S. esculentum cv ES6203 (Monforte and Tanksley 2000). Taken together, the RIL population covers 83% of the S. habrochaites genome. The genetic location of S. habrochaites DNA is mapped in each line, which can be used to rapidly narrow down regions conferring resistance and provide markers for future breeding efforts. We have begun screening the S. habrochaites RIL population and can identify specific individuals segregating for resistance, indicating that this approach will be rapid and fruitful.

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Figure 4. The wild tomato S. habrochaites accession LA1777 possesses a similar level of resistance to P. syringae pv. tomato as S. peruvianum. Five-week-old wild tomato accessions and the susceptible cultivar Bonnie Best were dip inoculated with P. syringae strain A9. Leaf samples were taken four days post-inoculation to count the bacterial population sizes. Note that S. habrochaites displays ~20-fold lower bacterial population sizes than the susceptible control.

Figure 5. The wild tomato Solanum habrochaites exhibits resistance to P. syringae pv. tomato race 1 and the resulting S. habrochaites x ES6203 population segregates for resistance. Five-week-old tomato plants were dip inoculated with a mixture of P. syringae pv. tomato strain A9 and 407. Dip inoculations were performed at a concentration of 1 × 107 CFU/ml. Pictures were taken 4 days post- inoculation. Individual LA lines are members of the RIL population and LA3919 exhibits resistance to P. syringae pv. tomato.

More detailed characterization of P. syringae pv. tomato strains for phylogeny. We had also proposed to analyze the relatedness of California Race 1 P. syringae pv. tomato strains collected from tomato fields in 2011 and 2012. As there was almost no bacterial speck in 2012, we only collected one strain from a single field. Therefore, we have analyzed the strains collected in 2011 only. Previously, with our collaborator Boris Vinatzer, we sequenced 5 genomes of P. syringae pv. tomato. After sequencing 5 genomes of P. syringae pv. tomato, we were able to develop 10 informative PCR-based single nucleotide polymorphism (SNP) markers to more deeply assess P. syringae phylogeny (Cai, Lewis et al. 2011).

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Placing these 10 SNP markers on a subset of strains has revealed that California strains cluster within three sub-groups present within one main group of most isolates collected throughout North America and Europe (Figure 6) (Cai, Lewis et al. 2011). Currently, we are screening through the remaining strains in our collection and analyzing their relatedness using this approach. The California P. syringae strains are quite closely related to each other and closely related to other strains present in the USA. Thus, sources of genetic resistance have promise in more broadly controlling P. syringae pv. tomato infection beyond California in areas like Ohio and New York where speck can also be a problem.

Figure 6. The similarity between P. syringae pv. tomato strains isolated worldwide. A total of 112 P. syringae pv. tomato strains collected over the last 60 years were analyzed using DNA sequencing and SNP markers. A. The majority of all current strains cluster with the T1 sub- group. This includes all California strains analyzed. B. World map with pie charts showing ratio of T1-, JL1065-, and DC3000-like strains for the continents from which strains were collected.

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References: Arredondo, C. and R. Davis (2000). "First Report of Pseudomonas syringae pv. tomato Race 1 on Tomato in California." Plant Disease 84(3): 371. Cai, R., J. Lewis, et al. (2011). "The Plant Pathogen Pseudomonas syringae pv. tomato Is Genetically Monomorphic and under Strong Selection to Evade Tomato Immunity." PLoS Pathog 7(8): e1002130. Kunkeaw, S., S. Tan, et al. (2010). "Molecular and evolutionary analyses of Pseudomonas syringae pv. tomato race 1." Mol Plant Microbe Interact 23(4): 415-424. Monforte, A. J. and S. D. Tanksley (2000). "Development of a set of near isogenic and backcross recombinant inbred lines containing most of the Lycopersicon hirsutum genome in a L. esculentum genetic background: A tool for gene mapping and gene discovery." Genome 43(5): 803-813. Pedley, K. F. and G. B. Martin (2003). "Molecular basis of Pto-mediated resistance to bacterial speck disease in tomato." Annu Rev Phytopathol 41: 215-243.

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California Tomato Research Institute ~ 2012 Annual Report 108

Project Title: Management of Root-Knot Nematodes with Novel Nematicides

Project Leaders: J. Ole Becker, Department of Nematology 1463 Boyce Hall, UC Riverside, CA 92521 Phone: (951) 827 2185 Email: [email protected]

Antoon Ploeg Department of Nematology, UC Riverside, CA

Joe Nunez UCCE Kern County, Bakersfield, CA

Summary: Two field trials were conducted to evaluate the efficacy of novel soil nematicides and anti- nematode microbials on root-knot nematode population development, tomato root health and yield. Our 2012 nematicide evaluation trials at the UC South Coast Research and Extension Center (SCREC) and at the former USDA Shafter Station found significant rkn disease-reducing efficacy early in the season by two products. At the end of the season such an effect is typically no longer evident, in particular under such heavy disease pressure. However, as in the previous year the development product MCW-2 significantly reduced root galling until harvest and increased yield by about one quarter compared to the non-treated check at SCREC. In Shafter MCW-2 was not as effective but another development product that we were not able to test at SCREC showed significant activity.

Introduction and Objectives: Plant-parasitic nematodes are responsible for at least $10 billion in US crop losses; more than half of those are caused by various species of root-knot nematodes (Meloidogyne spp.). Root- knot nematodes in CA processing tomato production have been responsible for 10-20% yield reductions, despite the wide-spread use of resistant tomato cultivars or nematicides (Koenning et al, 1999). The increasing occurrence of Mi-1 gene resistance-breaking root-knot nematode strains in CA processing tomato production fields (Roberts, 1995, Kaloshian et al., 1996, Williamson and Kumar, 2006) is considered an increasing problem not only because of the potential yield loss to the individual farmer but the danger of wider dissemination of these strains. Also, there is the realistic concern about the potential introduction of new invasive species. For example, Meloidogyne enterolobii (syn. Meloidogyne mayaguensis) is a subtropical root-knot nematode species that was first detected in the US about a decade ago. In Florida, it is now considered one of the most important nematode species in vegetable production (Brito et al., 2004a,b). The nematode is morphologically indistinguishable from our common root-knot species and reproduces well on all resistant tomato cultivars.

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In the past few decades, management of soilborne pathogens in high cash crops has primarily relied on the use of soil fumigants (Noling and Becker, 1994). Although often superior in efficacy compared to contact pesticides, many fumigants have negative attributes, such as potential health hazards, and groundwater or air pollutants. Consequently, several soil fumigants were banned while others have been restricted in use. The few remaining fumigants are generally limited by regulatory restrictions related to their high emission rates (volatile organic compounds), and toxicity. Furthermore, organophosphate and carbamate nematicides have been severely restricted or taken off the market as a consequence of the Food Quality Protection Act. With development cost of $80-100 million for a new pesticide, the agrochemical industry has neglected R & D of nematicides for a number of years in favor of the more profitable markets of fungicides, insecticides or herbicides. More recently however, a number of new compounds for nematode management in both conventional and organic tomato production have been under development but little data are available concerning efficacy against plant parasitic nematodes under CA conditions.

Methods: One tomato field trial was conducted from 22 May to 23 Aug 12 at the University of California South Coast Research and Extension Center (SCREC). The other field trial was performed at the same time at the former USDA Cotton Station at Shafter where we have created a suitable site for nematicide tests against root-knot nematodes (M. incognita). The SCREC soil at the trial site was a San Emigdio sandy loam with 13% sand, 75% silt, 11.6% clay, 0.4% organic matter, pH 7.3 (ANR Analytical Laboratory, University of California, Davis). The test site at SCREC is also infested with the Southern root-knot nematode, M. incognita. For the past five years at least one host crop has been grown to keep the rkn population at a high level. During the winter months the field was cropped to wheat (cv. Yecoro Rojo). For the tomato trial, each individual plot was 6.1 m long and 0.6 m wide with plant spacing of 0.3 m. The trials were designed as a randomized complete block with 5 replications. At the beginning (pi) and end (pf) of the trial, six soil cores were taken to a depth of 25 cm from each plot, pooled and a subsample was extracted for J2 rkn. Mean rkn population density at planting was 46 second-stage juveniles (J2)/100 cm3 (Baermann funnel with approx. 35% extraction efficacy). All preseason treatments were suspended in 7.5 L water, applied with a sprinkler can in a 0.5 m band and rototilled into the top 10-12 cm. An additional 22.8 L water was then sprinkled on top of each plot. Before planting, low volume irrigation tubing (2 L/hr emitter output, 0.3 m spacing) was buried at approximately 10 cm depth. Both trials were planted with root-knot nematode susceptible cultivar Halley 3155. Post-plant soil treatments, suspended in 7.5 L water, were applied with a sprinkler can as a 0.5 m wide band along the tomato seedlings. Movento was applied as a foliar spray in 188 L/ha. Soil temperatures at SCREC at 15 cm depth were 23.9˚C (7 dbp), 21.5˚C (@p), 19.8˚C (7 dap), 21.7˚C (14 dap) and 21.8˚C (28 dap); air temperature during foliar spray application was 16˚C. Six weeks after transplanting and at harvest, 5 tomato root systems per replication were evaluated for rkn disease symptoms. Treatment effects on root galling (arcsine(sqrt(x/10)), rkn population levels (log(x+1)), and yield were subjected to ANOVA and, if significant, to means separation by Fisher's protected LSD test or contrast comparisons (SuperANOVA, Abacus, Berkeley, CA).

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Results: The general conditions for the field trials were excellent. No major pest or disease, other than caused by root-knot nematodes, was observed. A vigor rating two weeks after transplanting indicated no differences among the treatments (data not shown). Root galling at SCREC six weeks after transplanting was still fairly low but with major differences among the treatments (Tab. 1). In particular, plants in the MCW-2 treatment had very few galls and significantly fewer than any other treatment. At harvest again only MCW-2 reduced root galling. This was reflected in a yield increase of about 25% compared to the non-treated check. None of the treatments had an influence on the root-knot nematode population development.

At Shafter, root galling at mid-season was considerably higher than in the milder climate at SCREC (Tab. 2). Vydate and the most frequent DPnema application were effective in reducing disease symptoms. The effect of the latter treatment on galling was still present at harvest, but at this time tomato roots were severely galled in nearly all treatments due to the immense disease pressure.

Tab. 1 Root galling, yield and nematode population development at SCREC Treatment, rate/ha 6 wk-gall gall rating tomato yield rkn (application timingz) ratingy at harvest (kg/plant) pf/pi 1. Non-treated check 1.76 bcx 7.7 bc 0.99 67.8 a 2. Vydate L, 2.34 L/ha (7 dbp, 28 dap) 1.43 bc 7.2 b 1.14 43.4 a 3. MCW-2 480 EC, 6.2 L/ha (7 dbp) 0.74 a 6.6 a 1.27* 39.8 a 4. MCW-2 480 EC, 8.3 L/ha (7 dbp) 0.53 a 6.4 a 1.24* 108.2 a 5. NemaQ, 28.1 L/ha (5 dbp, 14 dap) 1.58 bc 7.7 bc 0.90 22.3 a 6. Actinovate 0.44 L/ha (7 dbp, @p, 14, 28 1.66 be 7.7 bc 1.17 38.6 a dap) 7. RDL-29, 2.34 L/ha (7dbp, 14, 28 dap) 1.24 b 7.6 bc 1.11 107.6 a 8. Vydate L, 2.34 L/ha (7 dbp); Movento 240 1.28 bc 7.4 bc 1.18 57.0 a SC, 0.37 L/ha + 0.25% Dyne-amic (14, 28 dap) 9. Dazitol, 58.5 L/ha (7 dbp) 1.83 c 7.8 c 1.13 80.6 a 10. Sesamin EC 9.34 L/ha (7 dbp, 14 dap) 1.51 bc 7.7 bc 1.02 27.0 a z days before planting (dbp), at planting (@p), days after planting (dap) y Zeck's 0-10 rating scale in which 0 indicates gall-free roots and 10 max galling. x Column numbers followed by the same letter are not significantly different at P=0.05 (gall ratings, rkn multiplication) as determined by Fisher's protected LSD test. * sig. different from non-treated check (contrast comparisons, #1 vs #3, P=0.049; #1 vs #4, P=0.079).

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Tab. 2 Root galling at the Shafter Station Treatment, rate/A mid-season gall rating gall rating* at harvest* 1. Non-treated check 7.06 abcd 10.00 a 2. Vydate L, 3pt/A 3.48 f 9.56 a 3. Movento, 4 fl oz/A, 2 foliar app. 7.86 ab 9.88 a 4. Sesamin EC, 1 gal/A 8.38 a 10.00 a 5. NemaQ, 28.1 L/ha 8.34 a 10.00 a 6. MeloCon, 4 lb/A 8.28 a 9.68 a 7. Dazitol, 6.25 gal/A 8.42 a 10.00 a 8. MCW-2 480 EC, 6.2 L/ha 5.40 cdef 9.76 a 9. MCW-2 480 EC, 8.3 L/ha 6.06 bcde 8.92 a 10. DPnema, 1 pt/A 7.46 abc 9.80 a 11. DPnema, 1 qt/A 7.40 abc 9.72 a 12. DPnema, 1 pt + 0.5 pt post 5.16 def 8.96 a 13. DPnema, 1 pt + 2 x 0.5 pt post 4.00 ef 7.24 b 14. Ecozin, 56 fl oz/A 8.94 a 10.00 a Prob= 0.00 0.0032 % CV 23.95 10.35 LSD(p=0.05) 2.090 1.253

*root gall rating (1-10) Literature cited: Brito, J., J. Stanley, R. Cetintas, T. Powers, R. Inserra, G. McAvoy, M. Mendes, B. Crow, and D. Dickson 2004a. Meloidogyne mayaguensis a new plant nematode species, poses threat for vegetable production in Florida". 2004 Annual International Research Conference on Methyl Bromide Alternatives and Emissions Reductions. Orlando, FL. Kaloshian, I., V. Williamson, G. Miyao, D.A. Lawn, and B.B. Westerdahl 1996. “Resistance- breaking” nematodes identified in California tomatoes. California Agriculture 50(6):18- 19. Koenning, S.R., C. Overstreet, J.W. Noling, P.A. Donald, J.O. Becker, and B.A. Fortnum. 1999. Survey of crop losses in response to phytoparasitic nematodes in the United States for 1994. J. Nematology 31:587-618. Noling, J.W., and J.O. Becker 1994. The challenge of research and extension to define and implement alternatives to methyl bromide. J. Nematology 26:573-586. Roberts, P.A. 1995. Conceptual and practical aspects of variability in root knot nematode related host plant resistance. Annual Review Phytopathology 33:199-221. Williamson, V.M., and A. Kumar 2006. Nematode resistance in plants: the battle underground. Trends Genet. 22:396-403. Zeck, W.M. 1971. A rating scheme for field evaluation of root-knot nematode infestations. Pflanzenschutz-Nachrichten, Bayer AG 24:141–144.

California Tomato Research Institute ~ 2012 Annual Report 112

Project Title: Assessing the Potential of Nematode-Resistant Wheat Varieties for Control of Root-Knot Nematode on Tomato

Project Leader: Valerie Williamson Department of Plant Pathology University of California, Davis, CA 94516 Phone: 530-752-3502 Email: [email protected]

Co-investigator: Howard Ferris Professor, Dept. of Entomology and Nematology

Objectives: 1. Maintain cultures of resistance-breaking nematodes from tomato fields in different locations in California 2. Use microplot experiments to compare the effects of nematode resistant and susceptible wheat rotations on root-knot nematode damage to tomato 3. Use molecular markers to identify the species of up to 6 field cases of Mi-breaking root- knot nematodes from California tomato fields.

Procedures: 1. Root-knot nematodes that can infect tomato with the Mi-1 gene have been obtained from several tomato-growing regions of California. We maintain cultures of a representative set of strains to be used for screening germplasm and molecular characterization. Nematode cultures were transferred to new tomato plants every 2-3 months.

3. While assessing potential rotation crops for CTRI, we discovered a new source of root- knot nematode resistance in the cultivated wheat variety Lassik. This result was surprising as the genetically similar wheat variety Anza is known to be a host for the root- knot nematode Meloidogyne incognita. Lassik is a recently released Hard Red Spring wheat variety, and, although very similar to Anza, it carries a translocation from a wild relative of wheat that contains several resistance genes including nematode resistance. This resistance is effective even on Mi-virulent root-knot nematode isolates. We carried out microplot trials to test the value of including nematode- Fig. 1. Microplots on UC Davis campus with stands of wheat and resistant wheat in a crop sequence for fallow controls. managing root-knot nematode damage to tomato.

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4. A set of 48 microplots that are 24 inches in diameter and 42 inches deep, embedded in the soil, and located on the UC Davis campus were used in these experiments (Figure 1). Each microplot was provided with an irrigation emitter.

On October 21, 2011, we inoculated half of the microplots with chopped roots of tomato plants that were heavily galled by root-knot nematode (Meloidogyne incognita). Inoculum was incorporated into the top 6 inches of soil of each plot. The remaining 24 microplots were not inoculated with nematodes and were used as controls. Both inoculated and uninoculated plots were immediately planted with 19 seedlings of either Anza wheat or Lassik wheat or left fallow so that there were eight replications of each combination. Treatments were arranged in a randomized complete block design.

On April 23, 2012, the wheat was removed and three tomato seedlings (UC82) were transplanted into each microplot. After 3 months (July 23), tomato plants were harvested and roots dug from the soil for evaluation of nematode galling. Throughout the growth cycle of both wheat and tomato, plots were hand-weeded and insects managed as necessary. Chicken wire enclosures were installed around each plot to exclude vertebrate herbivores.

3. DNA was extracted from juveniles hatched from egg masses collected from roots of galled field samples. Species-specific primers and/or mitochondrial DNA differences were assayed to determine nematode species.

Findings: Objective 1. Cultures of Mi-virulent nematodes have been maintained on tomato plants with the Mi gene in our greenhouse for several years. We continue to test new DNA markers in an attempt to develop a molecular detection method to identify these resistance-breaking strains. Analyses indicate that the ability to infect tomato cultivars that have the Mi gene has developed independently on many occasions and a single molecular test that identifies all such nematode strains may not be possible.

Objective 2. We assessed tomato plants from the 48 microplots using the following parameters: Vigor: Vigor of plants was based on ratings under four criteria: vegetative growth, senescence, fruit load and fruit ripeness. In calculationg Overall Vigor, indices for vegetative growth and fruit load were considered to be positive while those for senescence and ripeness were considered negative. For standardization, all ratings of vigor were done by one individual (Figure 2). Plant weight: Total weight of above ground plant parts with fruit removed. Fruit weight: Total weight of fruit collected from each microplot. Fruit, % red: The % red of the total fruit from each microplot was estimated by visual examination. Root knot index: The degree of galling was assessed for roots removed from each microplot. Galled roots were categorized into eight infection classes that were then transformed to a 0-100 Root-knot Infection Index.

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Table 1 shows the average value of these parameters for the 8 microplots for each of the 6 treatments. Within each column, parameter values that are significantly different (P < 0.05) among treatments are indicated by different letters.

Figure 2. Microplots three days before harvest of tomato plants.

Table 1. Comparison of tomato plant parameters after indicated treatments. Overall Plant weight Fruit weight Fruit, % red Treatment vigor (kg) (kg) No RKN / fallow 3.63 B 1.37 B 6.12 A 31.2 B No RKN / Lassik 4.38 A 1.55 B 7.04 A 28.1 B No RKN / Anza 4.00 B 1.60 A 6.86 A 26.9 B M. incognita / fallow 3.00 B 1.32 B 5.70 A 28.1 B M. incognita / Lassik 4.13 B 1.51 B 6.31 A 23.1 C M. incognita / Anza 2.25 C 1.19 C 5.70 A 31.9 A

In sum, overall vigor and weight of tomato plants appeared to be significantly higher following the wheat variety Lassik (resistant) than following Anza (susceptible) or fallow when no nematodes were present. In the nematode infested microplots, tomato plant vigor and plant weight were significantly lower following susceptible wheat than following resistant wheat. Also, the percent red fruit was higher following susceptible wheat than resistant wheat or fallow. A possible explanation for the higher percent of red fruit is early senescence due to nematode stress. We also assessed the root knot index of the tomato plants after each treatment (Table 2). While the index was lowest following resistant wheat, this value was variable and the difference was not statistically significant (probability < 0.05).

California Tomato Research Institute ~ 2012 Annual Report 115

Table 2. Root-knot index following Lassik (resistant) and Anza wheat Ave. root-knot index Treatment RKN/fallow 63.8 A RKN/ Lassik 38.6 A RKN/Anza 51.1 A

3. We determined the species of virulent populations of root-knot nematode for six samples from resistant tomato fields using molecular markers. In four cases the species was Meloidogyne incognita. This is the species most commonly found on tomato in California. In one case the species was M. javanica. For one sample collected in early July, a mix of M. incognita and M. hapla was found. Roots collected from the same field at a later date appeared to have only M. incognita. It may be that M. hapla, which is not controlled by the resistance gene Mi, infects tomato early in the season, but is not active during the hot weather. We also carried out bioassays on two of the field samples. In both cases we confirmed that the nematodes were able to reproduce on tomato with the Mi gene. We also tested a preserved sample of resistance-breaking root-knot nematode from a tomato field in Mexico and determined by DNA analysis that it was Meloidogyne enterolobii (Guava nematode). This nematode is not controlled by the Mi gene and is a problem on tomato in Florida, South America, Asia, Africa, but has not been found yet in California.

Conclusions from microplot experiments: Microplot experiments indicated that using resistant wheat has potential to be a valuable tool for management of root-knot nematodes in crop rotation systems. Additional studies will be required to optimize recommendations for implementation. Wheat varieties that carry the nematode resistance gene Rkn3 and are appropriate for use in California have been developed at UC Davis by Dr. J. Dubcovsky. Commerically available varieties include Patwin, a hard white spring wheat available from Adams Grains, and Lassik, a hard red spring wheat available from Baglietto Seeds.

Budget details: Salaries and other Responsibility Cost ($) expenses Lab assistant Monitor and maintain microplot 6711 (YuYun Xiang) experiments; assist in data collection Student help Monitor and maintain greenhouse cultures; 2900 (Kiho Sung) nematode ID using molecular techniques Employee benefits 3823 Supplies and Microplot maintenance; lab supplies; 2589 expenses greenhouse space rental Total: 16,023

Project Title:

California Tomato Research Institute ~ 2012 Annual Report 116

Protection of Tomato Root Health by Bacteria from the Genus Collimonas

Project Leader: Johan Leveau Associate Professor, Department of Plant Pathology One Shields Ave, University of California, Davis, CA 95616

Co-Investigators: Mike Davis Cooperative Extension Specialist Department of Plant Pathology One Shields Ave, University of California, Davis, CA 95616

Gene Miyao Cooperative Extension Farm Advisor, Yolo-Solano-Sacramento counties 70 Cottonwood Ave, Woodland, CA 95695

Budget: $39,917

Key findings: • We isolated a Collimonas strain native to California soils with in vitro activity against a large collection of plant-pathogenic fungi and oomycetes, including Fusarium oxysporum f. sp. lycopersici (Fol). • When combined with Serenade Soil, this strain Cal35 prevented Fol-induced vascular discoloration and loss of plant biomass in a greenhouse trial with tomato. Results varied with different Fol isolates. • Collimonas Cal 35 appeared to lower the frequency with which eggs of the root knot nematode Meloidogyne hatched in a laboratory experiment. • Collimonas Cal35 survived in autoclaved potting soil with an estimated half-life of 4.2 days. Survival could be modulated by the addition of chitin and/or the volcanic mineral Green Tuff. This final report covers the period between January 1, 2012 (project start date) and November 9, 2012 (final report due date). The official end date for the project is December 31, 2012. An appendix to the final report will be available upon request after this date: it will summarize the results of the experiments that will be performed between November 10 and December 31, 2012.

Introduction: Based on previous demonstrations of the antifungal and chitinolytic nature of bacteria from the genus Collimonas, we believe that these so-called collimonads have practical potential for the management of soil fungi and nematodes that are of concern to tomato growers in California. Presently, this potential remains untapped because the model strain that has been used to demonstrate biocontrol properties of Collimonas, i.e. C. fungivorans Ter331, is a foreign import, which prevents it from use in trials that involve its deliberate and controlled release into the field environment.

California Tomato Research Institute ~ 2012 Annual Report 117

The decision to include Collimonas in future field trials would be easier to make if more information were available 1) on the types and abundances of collimonads that occur naturally in Californian soils, especially soils that are used for production of processing tomatoes, 2) on the ability of these collimonads to perform as well as or even better than strain Ter331 in greenhouse experiments against fungal pathogens such as Fusarium oxysporum, 3) on the untested possibility that collimonads also protect tomato plants from attack by nematodes, and 4) on the fate of Collimonas bacteria after release in the soil environment.

Results: We have tested a collection of soil samples from tomato production fields in Yolo county for the presence of Collimonas bacteria. While some of these samples scored positive for Collimonas using a PCR-based detection method (Höppener-Ogawa et al, 2007), we were not able to isolate culturable representatives from these soils, which would be a requirement for biocontrol purposes. However, we were able to isolate and characterize numerous Collimonas strains with antifungal activity from the mineral layer of forest soils in Northern California (Uroz et al, manuscript in preparation). One of these, Collimonas arenae strain Cal35, showed superior ability to suppress the hyphal growth of a number of plant-pathogenic fungi and oomycetes on agar plates, including Fusarium oxysporum f. sp. lycopersici, the causal agent of Fusarium wilt of tomato.

For this experiment, 13 bacterial strains (Table 1) were tested in a standardized confrontation assay (Mela et al, 2011) to quantify the effect on mycelial growth of 22 fungi or oomycetes (Table 2). In total, 286 bacterium-fungus/oomycete pairs were evaluated in triplicate on Water Yeast Agar (WYA) plates supplemented with 2 mM N-acetylglucosamine and scored as shown in Figure 1.

Table 1: Bacterial strains used in this study. Genus Species Strain Score* Escherichia coli Top 10 5.06 Pseudomonas putida 1290 5.02 Collimonas arenae Cal35 1.75 Collimonas arenae Ter10 2.84 Collimonas fungivorans Cal1 2.37 Collimonas fungivorans Cal2 2.30 Collimonas fungivorans Cal39 2.47 Collimonas fungivorans Ter6 2.30 Collimonas fungivorans Ter14 2.06 Collimonas fungivorans Ter331 2.91 Collimonas pratensis Cal31 3.04 Collimonas pratensis Ter91 2.75 Collimonas sp. D25 2.90 *Shown is the score averaged over 3 replicate assays and over 22 tested fungi/oomycetes. Scoring was done as shown in Figure 1.

Averaged over all tested fungi, the inhibitory performance was greatest for strain Collimonas sp. Cal 35 (score=1.75), followed by C. fungivorans Ter14 (2.06) and Collimonas sp. Cal 2 (2.30). The weakest performing Collimonas strain was C. pratensis Cal31 (3.04).

California Tomato Research Institute ~ 2012 Annual Report 118

Collimonas sp. Cal35 was unique and superior among the tested Collimonas strains in that it was the only one to completely inhibit the growth of Sclerotium rolfsii and Rhizoctonia solani as well as the oomycetes Pythium violae, Pythium ultimum, and Phytophthora capsici. It shared with C. fungivorans Ter14 the ability to completely inhibit Pythium irregulare. Strain Cal 35 was also the sole best inhibitor of Fusarium circinatum, Fusarium oxysporum, and Mucor sp. 1 2 3 4 5

Figure 1. Scoring of bacterial impact on mycelial growth. Scores ranged on a scale of 1: (near-)complete inhibition of mycelial growth to 5: mycelial growth not at all affected. Shown here are exemplary scores for several bacterial strains in confrontation with Sclerotium cepivorum. The plate on the far right is a control, with no bacteria inoculated across the center of the agar surface. The overall least affected by the co-inoculation with Collimonas bacteria (Table 2) were the fungus Fusarium circinatum (score=3.9) and the oomycete Phytophthora cactorum (4.0). Three fungi were completely or near-completely inhibited (<1.7) by all Collimonas strains tested, i.e. Monilinia fructicola, Botrytis cinerea, and Geotrichum candidum. All three are known as important postharvest pathogens of fruits, including tomato. None of the fungi tested were negatively affected by E. coli or P. putida (>4.50). In some cases, fungal growth actually seemed to be stimulated by the presence of E. coli or P. putida (e.g. as was the case for Phytophthora capsici).

Table 2: Fungi or oomycetes used in this study. Phylum Subphylum Class Order Family Genus Species Scor e Ascomycota Saccharomycotin Saccharomycetes Saccharomycetale Dipodascaceae Geotrichum candidum1 1.05 a s Perizomycotina Eurotiomycetes Eurotiales Trichocomaceae Aspergillus niger2 1.42 carbonarius3 2.50 Dothideomycetes Pleosporales Pleosporaceae Alternaria alternata4 2.77 Botryosphaeriales Botryosphaeriaceae Botryosphaeria stevensii5 2.36 Sordariomycetes Hypocreales - Fusarium circinatum6 3.91 oxysporum7 3.27 Glomerellaceae Colletotrichum acutatum8 2.84 Magnaporthales Magnaporthaceae Magnaporthe grisea9 2.76 Phyllachorales - Verticillium dahliae10 2.33 Diaphorthales Cryphonectriaceae Cryphonectria parasitica11 1.91 Leotiomycetes Helotiales Sclerotiniaceae Botrytis cinerea12 1.04 Monilinia fructicola13 1.00 Basidiomycota - Agaricomycetes Atheliales Atheliaceae Sclerotium rolfsii14 2.27 cepivorum15 1.64 Cantharellales Ceratobasidiaceae Rhizoctonia solani16 3.09 Heterokontophyt Oomycetes Pythiales Pythiaceae Pythium violae17 3.14 a irregulare18 2.36 ultimum19 3.17 Peronosporales Pythiaceae Phytophthora capsici20 3.09 cactorum21 4.00 Zygomycota Mucormycotina Zygomycetes Mucorales Mucoraceae Mucor sp. 22 3.46 1: causative agent of sour rot on fruits and vegetables; 2: model strain CBS120.49; 3: sour rot of grape; 4: tomato mold; 5: tree cankers; 6: pitch canker of pine; 7: f. sp. lycopersici, race 3, tomato wilt; 8: fruit rot; 9: rice blast; 10: Verticillium wilt of tomato; 11: chestnut blight; 12: bunch rot of grape; 13: brown rot of peach; 14: Southern blight; 15: Allium root rot; 16: damping off disease; 17: cavity spot of carrot; 18/19: damping off disease of carrot; 20: rot of bell pepper; 21: root rots; 22: common soil fungus.

California Tomato Research Institute ~ 2012 Annual Report 119

It was noted that the results with the Collimonas Ter strains in confrontation with the model fungus Aspergillus niger differed from those reported in the literature (Mela et al, 2012), in that we saw little variation in the ability of Collimonas strains Ter6, Ter10, Ter14, Ter91, and Ter331 to slow the growth of A. niger. However, using a different confrontation medium (0.1x ISP2: 0.4 g/L yeast extract, 0.5 g/L malt extract, 0.4 g/L dextrose, 1.5% agar), we were able to replicate the data from the literature: mycelial growth of A. niger was impaired by Ter331 and Ter14, but not Ter6, Ter10, and Ter91 (Figure 2). With Cal35, we also saw impaired growth of the fungus, suggesting that 0.1x ISP2 represents a medium of choice in future confrontation assays between this Collimonas strain and A. niger.

control

Ter6 Ter14

Ter10 Ter331

Ter91 Cal35 Figure 2. Confrontation of Aspergillus niger on 0.1x ISP2 agar plates with various Collimonas strains. Spores of A. niger were spotted at one side of the agar surface (the dime-size circular spot in each photograph) and challenged with a streak of bacteria across the center of the agar surface (top of each photograph). Mycelial outgrowth from the spot of inoculation was as on the control plate (no bacteria streaked) for Ter6, Ter10, and Ter91, but slowed down in the presence of Ter14, Ter331, and Cal35.

In greenhouse experiments, when applied as prophylactic root dip and subsequent soil drenches, Collimonas sp. Cal 35 was able to suppress the effects of Fusarium wilt (measured as vascular discoloration and dry weight) on tomato plants that were dipped with a laboratory isolate of F. oxysporum f. sp. lycopersici race 3 (Figure 3). However, this suppression was only seen when Cal35 was applied as a 1:1 mixture with the commercial biocontrol product Serenade Soil (Agraquest, Davis, CA). Co-inoculation of Cal35 with Serenade Soil on WYA plus N- acetylglucosamine confrontation plates did not result in greater reduction of mycelial growth by F. oxysporum f. sp. lycopersici, as compared to Cal35 alone (results not shown). This suggests that the synergistic effect which we observed between Cal35 and Serenade Soil in the greenhouse experiment depends on the presence of soil or plant roots.

California Tomato Research Institute ~ 2012 Annual Report 120

4.5 16 4 A 14 B 3.5 12 3 10 2.5 8 2 6 1.5 dry weight (g)

vascular discoloration 1 4 0.5 2 0 0 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 treatment treatment

Figure 3. Effect of the following treatments on vascular discoloration (A) and dry weight (B) on greenhouse tomato plants. 1: no treatment 2: Collimonas root dip, followed by water root dip 6 days later, followed by water drenches 3: water root dip, followed by Fusarium root dip 6 days later; followed by water drenches 4: Collimonas root dip, followed by Fusarium root dip 6 days later, followed by Collimonas drenches 5: Serenade Soil root dip, followed by Fusarium root dip 6 days later, followed by Serenade Soil drenches 6: Serenade Soil root dip, followed by water root dip 6 days later, followed by Serenade Soil drenches 7: Collimonas/Serenade Soil mixture root dip, followed by water root dip 6 days later, followed by water drenches 8: Collimonas/Serenade Soil mixture root dip, followed by Fusarium root dip 6 days later, followed by bacterial mix drenches Vascular discoloration was scored on a scale of 0 to 4 as follows:

The greenhouse experiment was repeated with a different isolate of F. oxysporum f. sp. lycopersici race 3. This time, none of our treatments, including the Collimonas/Serenade Soil treatment, was able to prevent vascular discoloration or reduction in plant dry weight (results not shown). The result may indicate that there exists variation among F. oxysporum f. sp. lycopersici isolates in susceptibility to the antagonistic synergism between Collimonas and Serenade Soil. To confirm or reject this hypothesis, a third repetition of the experiment is underway, in which we include both of the previously tested isolates of F. oxysporum f. sp. lycopersici. The outcome of this experiment will inform our recommendation to use a Collimonas/Serenade mixture (‘Collinade’) in next year’s field trials as part of the parallel CTRI project ‘Influence of drip irrigation on tomato root health’ (Dr. Mike Davis et al).

In collaboration with Dr. Howard Ferris (Department of Entomology & Nematology at UC Davis), we are currently testing the ability of strain Cal35 and other Collimonas strains to prevent eggs of the tomato pathogenic root knot nematode Meloidogyne from hatching. Preliminary results (Figure 4) show significant variability between replicates, which was expected (eggs from different sacks were laid at different times) but which complicates assessment of the impact of bacteria on egg hatching. However, the trend looks promising for Cal35 and we will follow this up with experiments that include more replicates.

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10 10 10 9 9 9 8 8 8 7 A 7 B 7 C 6 6 6 5 5 5 4 4 4 eggs hatched eggs hatched eggs hatched 3 3 3 2 2 2 1 1 1 0 0 0 0 1 2 3 4 5 6 7 8 0 1 2 3 4 5 6 7 8 0 1 2 3 4 5 6 7 8 time (days) time (days) time (days) Figure 4. Effect of bacterial presence on the hatching of Meloidogyne eggs. Shown are the cumulative numbers of hatched eggs as a function of time, in the presence of bacteria of Collimonas arenae Ter10 (B) or Cal35 (C), compared to no bacteria added (A). Each one of the four lines represents a replicate.

We also quantified the ability of Collimonas to survive in soil. For this purpose, UC Davis standard potting soil was autoclaved and seeded with a suspension of strain Cal35 (at an OD600 of 0.03; 0.5 ml was added per g soil for a final concentration of approximately 107 cells per g soil), either alone or mixed with chitin (final concentration 5 mg per g soil) and/or Green Tuff powder (final concentration 5 mg per g soil). Green Tuff is a type of volcanic mineral and was kindly provided by Dr. Yoichiro Hirose. Addition of chitin, Green Tuff, or a mixture of both led to a greater initial increase in Collimonas population sizes compared to Collimonas added alone to the soil (Figure 5). Addition of chitin plus Green Tuff also resulted in a two-week delay in the decline of population sizes compared to no chitin, no Green Tuff (Figure 5). However, the decline of Collimonas after peaking was two times faster in the chitin plus Green Tuff treatment than in the no chitin, no Green Tuff treatment. After 50 days, surviving bacteria were detected only in the chitin plus Green Tuff treatment. We are planning additional experiments to verify whether these observations can be replicated under a variety of different conditions, for example by using non-autoclaved potting soil and soil samples from tomato production fields. Combined, these preliminary results suggest that survivability of Collimonas in soil may be modulated by the addition of chitin/Green Tuff mixtures. This may be of interest in the context of formulation of Collimonas for application in the field.

1.00E+09

1.00E+08

Cal 35 + UCD soil 1.00E+07

Cal 35 + UCD soil + Green Tuff 1.00E+06 forming units - Cal 35 + UCD soil + Chitin 1.00E+05 colony Cal 35 + UCD soil + Green Tuff + Chitin 1.00E+04

1.00E+03 0 20 40 60 time (days) Figure 5. Survival of Collimonas Cal35 in UC Davis potting soil as a function of addition of chitin, Green Tuff, or a combination of the two. Survival was measured and plotted on the Y-axis as colony-forming units that could be recovered per gram soil.

California Tomato Research Institute ~ 2012 Annual Report 122

Literature Cited: Höppener-Ogawa S, JHJ Leveau, W Smant, JA van Veen, W de Boer. 2007. Specific detection and real-time PCR quantification of potentially mycophagous bacteria belonging to the genus Collimonas in different soil ecosystems. Applied and Environmental Microbiology 73: 4191- 4197. Mela F, K Fritsche, W de Boer, JA van Veen, LH de Graaff, M van den Berg, JHJ Leveau. 2011. Dual transcriptional profiling of a bacterial/fungal confrontation: Collimonas fungivorans versus Aspergillus niger. The ISME Journal 5: 1494–1504. Mela F, K Fritsche, W de Boer, M van den Berg, JA van Veen, NN Maharaj, JHJ Leveau. 2012. Comparative genomics of bacteria from the genus Collimonas: linking (dis)similarities in gene content to phenotypic variation and conservation. Environmental Microbiology Reports 4: 424- 432.

California Tomato Research Institute ~ 2012 Annual Report 123

California Tomato Research Institute ~ 2012 Annual Report 124

Project Title: Evaluation of Environmental Influence on Tomato Plant Health via Soil Transfer From Five Points to Yolo

Project Leader(s): Gene Miyao UC Cooperative Extension 70 Cottonwood Street, Woodland, CA 95695 Phone: (530) 666-8732 E-mail: [email protected]

Mike Davis CE Specialist Dept. Plant Pathology, UC Davis 1 Shields Ave, Davis, CA 95616

Summary: Plants grown in place in a native Yolo soil produced equivalent yields and had similar plant vigor as plants grown in soil excavated in the fall from a Fresno Westside field and placed in adjacent pits in a commercial tomato field near Woodland.

Objectives: Evaluate the environmental versus the soil influence on processing tomato production via a small transfer of highly productive soil from a Fresno Westside commercial tomato field with a history of high production to be placed into a Yolo County field with a history of tomato production and late growth cycle vine decline. The attempt was to address the issue: Is vine decline associated mostly with soil or the environment? Procedures: In the fall of 2011 under dry weather conditions, top soil from a Five Points field was excavated with a back hoe and transported via cardboard, melon bins to hand-dug pits (~48” long x 36” wide x 30” deep) in a bedded, buried drip irrigated, commercial field to be planted to tomatoes in 20

California Tomato Research Institute ~ 2012 Annual Report 125

The native Yolo soil and the Five Points soil were submitted for lab analysis to compare. Soil samples were also submitted to check for root knot nematode. Pits were dug and filled to compare Yolo and Five Points soils as a set of 5 replicates of these 2 pairs. To remove the soil disturbance influence, the native Yolo soil was also hand-dug and placed back into comparable pits in the same general profile as dug. Tomatoes were mechanically transplanted by the grower’s crew. Plant health was observed during the season. Unfortunately, Tomato spotted wilt virus was especially concentrated in the northern area of our field where the trial was located. Individual plants centered on the pits were harvested separately as well as 2 additional plants immediately neighboring the central plant. Fruit was weighed and sorted for culls as well as a subsample of fruit submitted to a local inspection station of the Processing Tomato Advisory Board to measure fruit quality (color, Brix and pH). Aboveground portion of the plant centered on the soil pit was collected, forced-oven dried and weighed to compare vine biomass. Plants were observed during the season to visually compare plant growth. A schedule of field activities is listed in Table 1. Results: Lab analysis of soils indicated the general soil parameters, including macro and micronutrients, were similar between the selected Five Points and Yolo soils. Analysis of the excavated soil in the fall of 2011 indicated that P, Na and pH were higher in the Five Points soil (Table 2), while analysis of the soil overwintered in the refilled soil pits in spring 2012 indicated that the soils were generally similar except for lower calcium and higher magnesium levels in Yolo (Table 3).

Plant tissue analysis from whole plants at harvest indicated that nutrient levels grown in the two soils were similar to each other. Nutrient levels from the Yolo plants had slightly higher levels of potassium, manganese and magnesium (Table 4). Yield of marketable and total fruit were similar between the plants grown in the 2 soils (Table 5). Plant biomass (without fruit) and the percent of cull fruit were also similar. There were no statistically significant differences in fruit quality as measured for color, Brix and pH. Discussion: Our field observational exploration indicated that soils as well as plant growth from the Fresno Westside, Five Points soil was more similar than divergent to the native Yolo soil from a select field near Woodland.

While we would have preferred to not have interference from Tomato spotted wilt virus, there was never a dramatic difference in tomato plant growth from transplanting through harvest of the Yolo crop.

California Tomato Research Institute ~ 2012 Annual Report 126

While a more extensive and careful comparison of an array of soils from the Westside as well as a true exchange of soils between Five Points and Yolo might have been more revealing, there was no indication that a Westside soil would be a major contribution to improved plant health over the native Yolo soil. Acknowledgements: Growers Frank and Louie Muller of Joe Muller and Sons of Woodland and Frank Coelho of Five Star Ranch in Five Points greatly assisted with the field test with contribution of land, labor and equipment. Roger Scriven and Perry Ranch provided assistance with the soil transfer as did UC Davis student Hung Doan. Yolo field assistant Mark Kochi and student summer helper Austin Brickey contributed to the research effort. We are thankful for support from PTAB.

Table 2. Lab analysis of select Five Points and Yolo soil, sampled in fall, 2011.

SP Sand Silt Clay EC Ca (SP) Mg (SP) Na (SP) Cl (SP) B (SP) HCO3 (SP) CO3 (SP) > % pH % % % ds/m meq/L meq/L meq/L meq/L meq/L meq/L meq/L > 1 Five Points 44 7.5 34 35 31 2.0 7.5 8.2 6.0 7.0 0.7 - 2.5 4.3 <0.1 to 0. 4 2 Yolo 47 6.6 24 41 36 2.2 11.4 9.5 2.3 9.1 0.6 3.3 <0.1 v v v

CEC NO3-N Olsen-P X-K X-K X-Na X-Na X-Ca X-Mg (estimated) OM (LOI) Zn (DTPA) Mn (DTPA) Cu (DTPA) Fe (DTPA) ppm ppm ppm meq/L meq/L meq/L meq/L meq/L meq/L % ppm ppm ppm ppm 1 Five Points 19 65 448 1.1 171.5 0.7 12.8 10.8 25.5 2 2.0 8 1.1 13 2 Yolo 17 22 521 1.3 71.5 0.3 14.6 9.3 25.6 3 1.7 16 2.9 28 v Note: soils were more similar to each other than divergent

California Tomato Research Institute ~ 2012 Annual Report 127

Table 3. Lab analysis of select Five Points and Yolo soil, sampled in spring, 2012.

% % % % dS/m meq/l meq/l meq/l mg/l ppm ppm ppm ppm SP pH Sand Silt Clay EC Ca Mg Na B NO3-N PO4-P K Zn 1 Five Points 59 7.9 33 30 37 1.2 5.4 2.1 4.0 0.3 18 22 332 2.9 2 Yolo 58 7.6 26 38 36 1.3 4.3 4.9 3 1.9 33 31 319 1.5

Ammonium Acetate Extractable Cations Estimated Ca/Mg K/Mg ppm ppm ppm % ppm ppm ppm meq/100g meq/100g meq/100g meq/100g Ratio Ratio Mn Fe Cu OM Ca Mg Na Ca Mg Na CEC 1 Five Points 15.1 12.5 1.5 1.6 4790 766 189 24 6.3 0.8 32 3.8 0.1 2 Yolo 17.8 24.5 3 2.5 2753 1394 124 14 11.5 0.5 27 1.2 0.1

Table 4. Tissue sample analsyis at harvest, soil transport from Five Points to Yolo, 2012

% % % ppm ppm % ppm % % ppm ppm Soil origin N P K Zn Mn Na B Ca Mg Fe Cu 1 Five Points 1.67 0.13 0.91 29 88 0.27 194 5.22 1.75 504 6.8 2 Yolo 1.78 0.16 1.09 30 127 0.22 193 4.64 2.09 739 9.0 LSD 5% NS NS 0.18 NS 26 NS NS NS 0.25 NS NS % CV 4 11 10 27 14 15 22 10 7 72 20 probability 0.07 0.06 0.05 0.77 0.01 0.13 0.96 0.14 0.02 0.45 0.10 ^ Whole plant sample significant non-additivity Comment: Nutrient levels in tissue are similar to each other, except Yolo had slightly higher percent potassium, manganese and magnesium (and marginally higher and nearly significant N and P).

Table 5. Yield and fruit quality, soil transport from Five Points to Yolo, 2012 (composite of 3 plants per plot)

lbs plant marketable lbs % % % lbs % lbs per dry weight origin of soil red fruit total fruit pink green burn BER TSWV 50 fruit grams color °Brix pH 1 Five Points 38.4 54.3 1 3 6 0 20 7.50 383 28.2 4.84 4.28 2 Yolo 37.6 52.2 0 2 6 0 19 7.24 357 28.2 4.98 4.27 LSD 5% NS NS NS NS NS NS NS NS NS - NS NS % CV 31 22 91 80 27 117 23 6 29 - 12 1 probability 0.92 0.79 0.18 0.52 0.93 0.49 0.83 0.43 0.72 - 0.72 0.92

Comment: √ High level of variation with complication with high level of spotted wilt √ Fruit production outcome was similar between soils

California Tomato Research Institute ~ 2012 Annual Report 128

Project Title: Field evaluation of root knot nematode resistant wheat as a cover crop ahead of tomato production

Project Leader: Gene Miyao, Farm Advisor UC Cooperative Extension 70 Cottonwood Street, Woodland, CA 95695 Phone: (530) 666-8732 Email: [email protected]

Results: With our late planting and weak stand from lack of timely rainfall, the test was not successful in demonstrating the effectiveness of nematode resistant wheat when used as a cover crop to reduce the impact of root knot nematode on the subsequent tomato planting.

Objective: Assess the ability of nematode resistant wheat to reduce a population of a resistance-breaking strain of root knot nematode for tomato production.

Procedures: Wheat was drilled in the late fall as a winter-grown cover crop in a commercial field cropped to tomatoes in 2012 (Table 1- schedule). The field had a Mi resistance breaking population of nematode identified in the 2011 tomato planting. The treatments included Anza either with or without the 2NS gene associated with nematode resistance; and included a vegetation-free fallow control. The seeding rate was about 120 lbs per acre.

The trial design was a randomized complete block with 12 replicates with each plot measured at 100 feet long of a single, 5-foot centered bed. The trial was contained within 6 beds by 600 feet long.

Soil samples to measure the nematode population were taken prior to tomato planting and again at harvest. Wheat samples of aboveground biomass was taken of the wheat from 2 square feet areas and weighed after over-drying. An assessment of root galling in tomato plants was measured at harvest.

Tomato fruit yield was measured by mechanical harvesting the entire row and weighing into a special ‘GT’ wagon. A 5-gallon bucket sample of fruit was taken prior to sorting off the machine and separated by weight into marketable red, green, pink, sun-damage, mold and blossom end rot categories and reported as culls as a percent by weight. A 6-pound subsample of red ripe, non-defect fruit was submitted to a local Processing Tomato Advisory Board inspection station to measure fruit color, Brix and pH.

California Tomato Research Institute ~ 2012 Annual Report 129

Results: Soil samples in the 2012 spring ahead of transplanting tomatoes, indicated the fallow treatment had the lowest level of root knot nematodes (240 vs. wheat with 1000 plus) (Table 2). At harvest of the tomato crop, there were no significant differences in nematode population level or root galling amongst the treatments.

Average fruit yield was ~ 44 tons per acre, with 5.1 Brix (Table 3). None of the cull categories were different amongst the 3 treatments.

Discussion: The assessment of the benefit of the reported root knot nematode was a poor showing perhaps because of: late planting, poor stand, and early termination of the crop. The adjustment in future tests would be to plant the wheat earlier in the fall and to grow the wheat as a grain crop to allow longer exposure to the actively growing wheat roots.

Acknowledgements: Grower cooperators Steve and Sam Meek and John Pon assisted with the planting and harvesting of the field test. General consultation was provided by UCD Nematologist Valerie Williamson. Nematode soil samples were processed in the UCCE Nematologist Becky Westerdahl lab through Cindy Anderson. UC Davis wheat breeder/geneticist Jorge Dubcovsky program supplied Anza wheat with the 2NS gene associated with the nematode resistance; and also provided the conventional Anza seed.

Table 1. Evaluation of Anza wheat with 2NS nematode resistance, planted as a winter cover crop ahead of 2012 tomatoes, J.H. Meek and Sons, Woodland, 2012

planted: wheat, Dec 2, 2011 biomass 23 Feb 2011 for above ground wheat biomass vapam: chemigation, April 4, 2012 in field except trial area spring soil sampled April 9 transplant 14 May, 2012 double lines per 5' centered bed variety Nunhems Sun 6404 VFFN SW Soil type: Sycamore sility clay loam, drained location Meek #8, north of Willow slough, east side of CR 99 previous crop: tomatoes in 2011 harvest September 25, 2012 tomatoes fall soil sample 26-Sep Comments: late wheat planting, late emergence and weak stand. Glyphosate sprayed ~April 1.

California Tomato Research Institute ~ 2012 Annual Report 130

Table 2. Evaluation of nematode resistance wheat as a cover crop on nematode population, J.H. Meek and Sons, Woodland, 2012

9-Apr at harvest root root knot root knot galling Treatment # per liter # per liter 0= none winter cover crop (ave 12 reps) (ave 6 reps) 5= severe 1 Control (fallow) 240 5280 3.2 2 wheat (Anza) 1040 6480 3.2 3 wheat (nema resistant) 1133 3587 3.6 LSD 5% 559 NS NS % CV 82 59 19 ^ signficiant non-additivity ^

root galling visually assessed at harvest, average of 6 of 12 reps

Summary: √ root knot nematode population in spring was higher in resistant wheat treatment compared to the fallow control. √ By harvest, root knot population and root galling were statistically not different among treatments

Table 3. Evaluation of nematode resistance wheat as a cover crop on tomato fruit yield, quality and culls, J.H. Meek and Sons, Woodland, 2012

% blossom Treatment yield % % % % end winter cover crop tons/A Brix color pH pink green burn mold rot 1 Control (fallow) 44.3 5.1 21.1 4.38 0 1 13 0 2 2 wheat (Anza) 43.0 5.1 21.3 4.37 1 1 12 1 1 3 wheat (nema resistant) 44.6 5.0 21.3 4.37 0 0 11 0 1 LSD 5% NS NS NS NS NS NS NS NS NS % CV 5 6 2 1 181 107 23 363 104 ^ significant non-additivity ^ ^ ^

Summary: No significant differences in yield, fruit quality or cull level amongst treatments

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Project Title: Within-row Weed Control System for Transplanted Processing Tomatoes

Principle Investigator: David C. Slaughter, Professor Biological & Agricultural Engineering Department University of California, Davis, CA 95616 Phone: (530) 752-5553 Phone: [email protected]

Cooperators: Fadi Fathallah, Burt Vannucci, Chris Gliever, Laura Tourte & Gene Miyao, University of California, Davis Manuel Pérez-Ruiz, Universidad de Sevilla, Spain

Abstract/Summary: The goal of this project is to establish the overall economic feasibility of a semi-automated system for within-row weed control in transplanted processing tomatoes. Significant improvement was made in 2012 in the level of synchronization in the planting pattern between adjacent Holland-type tomato transplanters. Both the synchronized 3-bed transplanter, and the synchronized 3-row, semi-automated within-row weed control system were successfully operated in a trial on a commercial tomato farm in California. An economic design tool was created to allow economic impacts of various aspects of the system design to be evaluated and to help guide future design improvements to the synchronized planting and weed control systems. Development of a Synchronized Precision Transplanter: An improved, 3-bed, synchronized precision transplanter was completed and tested in 2012. The first key feature of this design was the use of precisely manufactured planting wheels (shown in

_Splined_ synchronization _shaft. (a) (b)

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Figure 1. Photographs of: (a) workers loading plants into the synchronized planting arms and (b) a planting wheel with the splined, PTO-style, index shaft used for synchronization. figure 1b) designed to allow a simple mechanical linkage to connect adjacent planters. A torque- limiting hub was mounted in the center of each planting wheel to allow both overload protection

Synchronization shafts.

(a)

Feedback sensor _for control of _planting arm speed.

Hydraulic motor and chain drive for planting wheel shaft. Plant spacing_ control &_ display. Travel speed sensor. Ground wheel.

(b)

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Figure 2. Photographs showing: (a) the PTO-style synchronization shafts (black with yellow safety end covers) connecting the three planting wheels, (b) the ground-wheel speed sensor and feedback control system for maintaining the desired plant spacing. (in the event of a clod getting jammed in the planter) and keyed drive shaft. Splined drive shafts (similar to those used for power takeoff (PTO) connections in small tractors) were manufactured to mount on the planting wheel drive shafts and allow the alignment of each planting wheel to be mechanically locked together so that all planting arms were precisely aligned. Standard agricultural grade PTO connecting linkages were used to mechanically link the planters as shown in figure 2a. Because they are telescoping linkages, this allowed a flexible means of connecting the splined shafts of each planting wheel allowing some independent vertical movement of each planter while maintaining the alignment of the planting arms.

Another design improvement implemented in 2012 was to mechanically decouple the rotation of the packing wheels from the rotation of the planting wheels. New packing wheels (shown in black in the inset photograph in figure 2b) were constructed from forklift style rims, selected because they were the largest off-the-shelf steel rim that would fit below the synchronization shaft. A hydraulic gear motor was used, with a chain drive system, to provide power to spin the planting wheel as shown in the inset photograph in figure 2b. A standard non-powered, agricultural implement gage wheel, developed in a previous CTRI project, was used as the odometry and speed sensor (shown in the bottom of figure 2b). This unpowered wheel has an optical shaft position encoder connected via a mechanical linkage that outputs an electronic signal when the sled is in motion. A low cost (~$60) digital controller1 was used to continuously monitor the rotation speed of the ground wheel and to control the output signal sent to an electrohydraulic servo-valve, which supplied the desired flow of hydraulic oil to the hydraulic motor to spin the planting wheel at the proper speed required to obtain the grower's selected plant spacing. A second optical encoder (shown in blue in the top right corner of figure 2b) was used as a real-time feedback sensor in the closed-loop control system to ensure that the planting wheel rotation speed always matched the actual travel speed of the planter. Five planting arms were used in the 2012 trial because the desired plant spacing along the row was 15-inches and five arms provided a nearly zero travel speed relative to the soil in the 1 to 1.5 mph tractor speed window to be used at planting.

Development of a Synchronized Within-Row Weed Knife System: An improved, 3-row, automated within-row weed knife system was also developed and tested in 2012. For each row, a pair of small, mechanical weed knives was mounted on a scissor-like linkage as shown in figures 3a & 3b. Two pneumatic cylinders were mounted, one per arm, between the linkage and the support frame. An electropneumatic airflow control valve was used to power the knives, locking them either in the closed position shown in figure 3a or the open position in figure 4a. An upgraded compressed air system was added in 2012 to allow continuous field operation of the three pairs of pneumatic knives at tractor speeds up to 3 mph. In order to precisely synchronize the knife opening and closing events, a separate airflow control valve was required for each knife pair in order to keep the air hose connections between the valves and their respective air cylinders as short as possible and all the same length. The unpowered gage wheel, shown in figure 2b, was also used as the odometry sensor for the 3-row

1 http://www.arduino.cc/en/Main/arduinoBoardMega California Tomato Research Institute ~ 2012 Annual Report 135

weed knife system. A digital controller was used to monitor the forward travel of the weed control sled and to automatically open and close the in-row weed knives according to the odometry pattern set by the operator.

Right Knife Pair

_Center Knife Pair

(a)

Left_ Knife_ Pair_

(b) (c) Figure 3. Photographs of the 3-row, within-row automatic weed control system. Figures 3a and 3b show the triangular weed knives (in red) in the closed (weed killing) position and the scissor-style linkage (in yellow) with the two pneumatic air cylinders. Figure 3c shows a side view of the three pairs of in-row weed knives in operation in a commercial organic tomato field in 2012.

A number of alternative seating positions for the operator were evaluated in 2012. Since the UC Davis precision cultivation sled has lateral position control available to the operator that is independent of the tractor's position and since the precision between-row cultivation was being done simultaneously with the precision within-row cultivation, the forward-facing operator position, shown in figure 4b, was selected for the 2012 trial since it allowed the operator to simultaneously view the lateral centering of the weed knives about the tomato row as well as the knife opening and closing pattern about the tomato plants along the row. Figure 4b shows the sled operator monitoring the in-row weed knives during the 2012 trial.

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The operator is holding a controller that allows him/her to: 1) shift the sled to the right or left, 2) shift the in-row knife pattern forward or backward, and 3) expand or contract the uncultivated "safety-zone" around each tomato plant. While, an emergency "knife open" button is available to the operator, in general, the opening and closing of the knives is completely automated, and the operator's

_In-row weed knives. _Shown in the open _position

(a)

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(b) Figure 4. Photograph of the synchronized transplanter taken during a planting trial on the UC Davis campus farm in 2011. Notice that the fingers are about to grab both the tomato plant in the foreground and tomato plant in the center. responsibility is primarily to make periodic adjustments to the knife pattern, while the digital controller is responsible for the plant-to-plant knife movements.

Due to the size of the tomato plants at the time of first cultivation in the commercial field trials in 2012, it was not possible to effectively use a pair of Alloway-type close cultivation disks without severe damage to about 5% of the tomato plants. Thus, for each row, an inward facing set of stationary (relative to the sled) sweep knives was used in place of the disks, as shown in figure 4a. The knife standards for the sweeps were placed about 19-inches apart, which allowed the tomato plants to pass by unharmed. The length of the sweep knives were such that the tips, at the closest point, were about 6-inches apart. The pneumatic in-row knives were placed slightly above the stationary sweeps to allow them to be opened as shown in figure 4a. In the open position, the uncultivated strip was ~2.5-inches wide. This provides a very close between-row precision cultivation along the tomato safety-zone. When the knives are closed, as shown in figure 3b, all plants are killed, either by the sweeps, or the in-row knives.

Experimental Methods: Field tests were conducted in a commercial organic tomato field in Northern California to evaluate the performance of both the 3-bed synchronized transplanter and the 3-row within-row automatic weed control system. Three separate field trial sites were selected based upon historical records of significant levels of weed pressure at those sites in prior years and the expectation that the weed pressures in 2012 would be comparable. However, the weed pressures at the time of first cultivation in the test fields were substantially below the expected levels in 2012 and as a result, the complete set of experimental treatments and assessments was reduced to a single site consisting of a 0.63 acre test plot that had the most weeds present. All results reported here were collected in that 0.63-acre trial.

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All pre-planting soil tillage and seedbed preparation operations were completed as part of the normal farming operation in the field where the test plot was located. The target plant spacing along the row was 15-inches and the planter travel speed was 1.5 mph. A team of six experienced farm workers assisted with the synchronized transplanting operation. The synchronized tranplanter was used to plant all rows of the 0.63-acre trial. To evaluate the performance of the synchronized transplanter, a large, 11-foot by 10-foot aluminum frame was utilized, with 12-foot measuring tapes mounted to each of three braces running the length of the frame. In the field, the frame was placed adjacent to the three rows of tomato plants in a 3-bed set. The plant location of each of the 27 tomato plants in a set was then recorded by reading the location of each plant on the adjacent measuring tape. Ten sets of 27 tomato plants in a 3-bed planting sets along the length of the trial were measured and the results analyzed to determine the accuracy at synchronizing the plant placement. After planting, the test plot was divided into two equally sized subplots. One subplot was used as the control, where the grower's standard weed control practices were applied. In the second subplot, the within-row weed knife system was operated before the hand weeding crew entered the field to remove weeds left after the first cultivation. Baseline weed counts were made before any weed control tasks were conducted in both the control and in-row subplots. Since the focus of the trial was in-row weed control, the weed counts were restricted to a 10-inch band about the row centerline. Weeds outside this central band were expected to be removed by standard between row cultivation and were not considered. Weed counts were made at 24 randomly selected locations distributed along the length of each subplot. Due to the commercial nature of the trial and the size of the tomato plants at the time of first cultivation, a slightly risk-adverse strategy was selected where the safety zone size was set to be approximately 7-inches in length. Preliminary tests indicated that a travel speed on 0.75 mph was a reasonably safe speed at which the operator could perform the monitoring and adjustment tasks over a full workday. While the system could be successfully operated at higher travel speeds of 1 to 1.5 mph for short time periods, the density of the canopy as it passed between yellow support frames shown in figure 4a made it difficult for the operator to locate the tomato plants' main stems at these higher travel speeds. As a result, the travel speed was set to 0.75 mph for the operation of the precision within-row weed control system in the experimental trial. After the in-row weed control system was operated, the number of tomato plants accidentally killed by the in-row knives was counted. After the automated in-row weed control operation, manual hoeing was conducted in the entire 0.63-acre trial by an experienced farm worker. The order in which the rows in the trial were hoed was selected at random, to avoid any bias due to fatigue. The time required to hoe each row was recorded in order to assess the labor savings associated with operating the automated in- row weed control system. At harvest, the tomato yield was determined by weighing the fruit collected in a load-cell equipped gondola for each of three 75-foot sections of row in each row of the trial. In addition, 50-pound inspection samples were collected in each harvested section and submitted to the Processing Tomato Advisory Board inspection process to determine if there was any impact of in-row weed control on the quality of the harvested fruit.

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Figure 5. Photograph showing the harvest of experimental plots. Harvested fruit are dumped into a weight hopper shown behind the harvester. At the end of each plot, the harvester stops to allow the harvest weight to be recorded. PTAB grade samples are shown in the foreground. Results: A significant improvement was made in the planting pattern synchronization in 2012. The distribution of the plant alignment between the three synchronized planters in 2012 is shown in the lower two histograms in figure 6. The two upper histograms in figure 6 show the 2011 results for comparison. The goal is to have most of the data concentrated at the origin in each histogram. A red vertical reference line has been placed at the origin in each set. The mean error was -0.2 inches between the between the plants planted by the left-side planter and the center planter in 2012. This is less than half the -0.5 inch mean error observed in 2011. On the right side, the mean error was also -0.2 inches in 2012, which is one third the +0.6 inch error observed in 2011. The total range of error dropped from 6.25 inches in 2011 to 4.75 inches in 2012, a 24% improvement. Further the distributions from 2012 are symmetric about the origin, which is superior to the skewed distributions observed in 2011. These results appear to show that the new hydraulic powered drive system improved the planting precision. We hypothesize that the fact that both the right and left planters lagged the center planter by -0.2 inches on average, was due to a torque load on the PTO synchronization shafts. In the future a larger diameter shaft, that is more resistant to torsion, should be investigated to see if this could completely eliminate the mean error in plant placement.

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2011 2011

2012 2012

Figure 6. Histograms showing the distributions of plant alignment, comparing the plant locations on the right and left sides to the center. The top two histograms are from the on-campus trial of the 2011 prototype. The bottom two histograms are from the 2012 trail in a commercial tomato field using the improved system. The red vertical lines are placed at the origin, as a reference. Ideally all plants would be close to this line. A field test of the three-row, within-row weed knife system was successfully conducted in a commercial organic processing tomato field. The systems approach we have proposed, that by synchronizing the planting pattern across each 3-bed set, a single sled operator can successfully perform semi-automated within-row weed control across all three rows simultaneously by monitoring only the knife pattern in the center bed, was validated in the 2012 on-farm trial. In the key metric of minimizing collateral damage (i.e. cultivator blight) to tomato plants the in-row weed knife system performed well and only 0.51% of the tomato plants in the rows treated by the in-row weed control system were accidentally killed by the in-row weed knives. Further the number of tomato plants in the two outside rows was equal or less that the number killed in the center row that the operator monitored, demonstrating the practical feasibility of the synchronized planting/synchronized in-row weed control concept. Fortunately for the grower, but unfortunately for this study, the weed load in the 2012 trial was low, with a median weed count of only 3.9 weeds per square meter in both subplots just prior to the first cultivation. This low level of weed pressure limited our ability to show differences in weed control performance. While a 25% reduction in the amount of hand hoeing labor was observed in the rows treated by the automated in-row knife system, the difference was not statistically significant (α=0.05). In addition to the low weed pressure, a contributing factor in being unable to show statistical significance was that bindweed was the predominant weed species present at the time of hand hoeing and a single mechanical treatment, as was conducted in the in-row knife trial, is generally insufficient to control bindweed. The harvested yield in the subplots treated by the automatic in-row weed control system were not significantly different (p-value = 0.54) than the yield in the control subplots. These results

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indicate that the 0.5% of tomato plants accidentally killed by the in-row weed knives did not adversely affect the yield of tomato fruit at harvest. Further, there were no significant differences (α=0.05) observed in any of the PTAB defect grade categories between the fruit harvested from the rows treated by the automatic in-row weed control system as compared to the fruit from the control rows. These results indicate that yield and quality of the harvested fruit were not adversely affected by the use of the in-row weed control system. Finally an economic design tool was created that allows engineers and economists to evaluate the relative economic impacts of various aspects of the system design including equipment investment costs, operation and maintenance costs (including travel speed effects), hand hoeing labor costs (including the effects of different weed loads), and the potential benefits associated with reduced labor costs due to the proportion of weeds removed by the prototype in-row weed control system. For example, an economic analysis of the 2012 prototype indicates that the travel speed of the in-row cultivation task, the level of weed pressure in the field, and the proportion of hand hoeing labor eliminated by the automatic system are the dominant factors in the economic success of the design. Additional research is needed to better understand the relationship between the size of the uncultivated safety zone, the proportion of tomato plants killed and its impact on yield, and the amount of hand hoeing labor required in follow-up weed removal.

Acknowledgements: The authors would like to express their gratitude to CTRI for the research funding provided and to Scott Park of Park Farming Organics for allowing our team to conduct research on his farm and for the generous in-field support he provided to make this project a success.

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Project Title: Field Bindweed Management in Drip Irrigated and Furrow Irrigated Processing Tomatoes

Principal Investigator: W. Thomas Lanini, Extension Weed Ecologist, Department of Plant Sciences Mail Stop 4 One Shields Avenue University of California, Davis 95616 Phone: (530) 752-4476 Email: [email protected]

C. Scott Stoddard Farm Advisor, Merced & Madera Counties University of California Cooperative Extension 2145 Wardrobe Ave Merced, CA 95341-6445 Phone: (209) 385-7403 Email: [email protected]

Summary: Field studies were conducted at UC Davis and WSREC near Five Points to evaluate the potential of registered herbicides to control field bindweed (Convolvulsus arvensis) without significant injury to tomatoes. The herbicides tested suppressed field bindweed growth, but none of the herbicides provided complete control. We found that Treflan was the most effective preemergence treatment for suppressing established field bindweed, and that post emergence treatments with Matrix or Shark improved control in most instances. Slight crop phytotoxicity was noted at WSREC for Prowl, Treflan, and Zeus preplant incorporated; phytotoxicity was increased with post emergent applications of either Matrix or Shark. However, symptoms of herbicide damage were not apparent by the end of the season.

Justification: Field bindweed is extremely difficult to control. It propagates from seed or vegetatively from buds formed in the roots. Tillage is not an effective method for controlling bindweed, as the cut root pieces have a great capacity for regeneration. Seedlings can be controlled with tillage when very young, but they develop the capacity to regenerate new shoot growth (become perennial) very rapidly. Chemical control of seedlings is possible, but established plants are much more difficult to control. An example is spraying the field after a post-harvest irrigation of the field with Roundup can suppress, but does not eliminate bindweed. Established plants often have a large root system relative to the amount of top growth, and thus not enough leaf area for absorption of postemergence herbicides to kill the entire root system.

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Additionally, the rapid adoption of drip irrigation and the economic necessity of maintaining the beds and replanting with only minimal tillage for multiple seasons in processing tomatoes seems to have exasperated the problem.

Mullen et al. (1999) found that Matrix (1 or 2 oz/a), Devrinol (2 lb/a), Dual (2.5 lb/a), Treflan (0.5 lb/a) PRE or POST applications of Matrix at 1 or 2 oz/a and metribuzin at 0.25 lb/a failed to control field bindweed. Other researchers have noted partial control with Matrix applied PRE or POST, Shark applied POST, and Treflan applied PRE. Combinations of PRE and POST treatments have not been reported. Additionally, PRE application of Prowl H2O has not been reported for field bindweed control.

The purpose of this study was to evaluate these materials alone or in combination for field bindweed “management”. The term management is used rather than control, as it is unlikely that any registered herbicide will completely control field bindweed in a single season. Hopefully the right combination of herbicide treatments can suppress field bindweed enough to achieve maximum yield potential with minimum hand weeding.

In 2011 trials, we found that Treflan was the most effective preemergence treatment for suppressing established field bindweed, and that post emergence treatments with Shark or Matrix also improved control in most instances. Dual Magnum, Matrix and Spartan applied PRE were not effective in suppressing established field bindweed. Results from two years work indicate that Treflan is the most effective preemergence herbicide on field bindweed. Thus, we continued these studies in 2012, with field experiments in two different production areas and with slight modifications of the treatments

References: Mullen, R.J., Caprile, J., Viss, T.C., Whiteley, R.W. and Rivara, C.J. 1999. Recent research development in tomato weed management. Acta Hort. (ISHS) 487:165-170

Objective: Evaluate registered herbicides and herbicide combinations for field bindweed management in processing tomatoes.

Procedure: Field studies were conducted at UC Davis and at West Side Research and Education Center (WSREC) to assess registered herbicides and herbicide combinations on management of field bindweed in drip irrigated (WSREC) and furrow irrigated (Davis) processing tomatoes. Field sites at each location were heavily infested with field bindweed.

At each location, essentially two trials were conducted. A large split-plot trial was used, with main plots pre-plant and pre-emergent applications of Prowl H2O (pendimethalin), Treflan (trifluralin), Zeus (sulfentrazone), and Matrix (rimsulfuron). Over the top of these, post applications of Matrix or Shark (carfentrazone) for the split plot treatments.

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Adjacent to this trial, other herbicide treatment combinations were tested with a randomized block design, and included sequential POST applications of Matrix or Shark, Matrix + Sandea (halosulfuron), Treflan applied two times, and a Treflan + Dual (metalochlor) combination that is commonly used in tomatoes, as well as untreated controls.

Treatment design was a randomized complete block design, with four replications. The trials included a hand-weeded check plot. Total number of unique treatment combinations = (5 x 3) + 6 = 21. A listing of these treatments with their application dates for WSREC is shown in Tables 1 and 2. UC Davis location (furrow irrigated) At the Davis location, Treflan treatments were applied prior to the final bed shaping, and incorporated (May 22) within one hour of application. The remaining preemergence treatments were surface applied ahead of tomato transplanting on May 23, 2012. Following transplanting, the field was sprinkler irrigated, followed by furrow irrigation for the remainder of the season.

Postemergence Matrix and Shark treatments were applied on June 13, 2012. Visual evaluations of tomato phytotoxicity (any loss of stand, reduced growth, leaf necrosis, and color) were made at regular intervals after treatment. At UC Davis, field bindweed and total weed control (estimates of percent cover) were evaluated at 7, 14, 28, 42 days after treatment and at tomato harvest. Field bindweed control was estimated on June 11, 19, 26, July 13, August 2 and 14 and Field bindweed cover (%) was estimated just ahead of harvest on Sept. 6, 2012. The only other weed present in the Davis plots was redroot pigweed. All redroot pigweed plants were counted and manually removed on July 18, leaving only the field bindweed. Weed-free plots were kept free of all weeds by manually removing them at weekly intervals for the first 10 weeks after tomato planting. Tomato injury was estimated for each treatment on the days of field bindweed evaluation. Tomatoes were hand harvested on September 17, 2012. Tomatoes were harvested from a 10 ft section from the center row of each plot, separated into red, green or rot fruit, and weighed to estimate yield.

WSREC location (drip irrigated) At WSREC, prior to bedding the experimental area, emerged bindweed was sprayed with Roundup at 2 pints/A. After burndown, Treflan, Prowl, and Zeus were applied to the top of finished beds and incorporated into the upper 3” of soil on April 24. Materials were applied with Tee Jet 8003 nozzles at 30 psi in 40 gpa water. The plot area was planted using TSWV resistant variety N6385 on May 2, then sprayed with an over-the-top application of Matrix. The field was then sprinkler irrigated on that day and again one week later before switching to drip irrigation. The drip system was installed on April 18 using Netafim “high flow” (0.36 gph) 5/8” drip line with 12” emitter spacing to a depth of about 9 inches. The system was attached to flow meters so that total water use could be monitored. Nitrogen fertilizer was applied through the drip system on 4 occasions for a total of 120 lbs/A.

Post emergence applications of Matrix and Shark were made on May 11 using the same nozzle set up as for the pre herbicides. Shark was applied using a shielded sprayer as to minimize contact with the tomato crop (Fig 1); matrix was applied over the top with an NIS adjuvant at 0.25% v/v. The second post application for select plots was done on May 30.

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Weed-free plots were kept free of all weeds by manually removing them at bi-weekly intervals during the growing season. Weed and crop ratings were made at 14, 28, 54 days after treatment. Tomatoes were machine harvested from each plot to estimate yields and collect fruit samples for PTAB analysis.

Results: UC Davis – Furrow irrigated Following planting, field bindweed control on June 11 varied among treatments (Table 1). Two preemergence treatments had good field bindweed control on June 11 - Treflan at 2 lbs/a and Matrix at 0.0625 lbs/a (4 oz of product = maximum label rate). On June 19, field bindweed control declined slightly in plots with preemergence treatments only, but improved when a post emergence treatment of Matrix or Shark had been applied. Shark treatments alone or with a prememergence treatment resulted in over 80% field bindweed control on June 19th. POST treatments of Matrix also improved control, but the mechanism of action is slower and thus overall control was not equal to Shark treated plots. By June 26, field bindweed control continued to decline in all plots, but the decline was slower if the plots received a POST treatment of Matrix. On July 13, the plots with the best field bindweed control were those that received two POST treatments of either Matrix or Shark. Preemergence treatment of Treflan or Matrix at the high rates also was still providing 58% or better bindweed control. By Aug 14, field bindweed control in all preemergence treated plots had declined below 45%. Post treatments improved control slightly versus the preemergence treatments applied alone. Field bindweed cover at harvest was greater than 50% with all treatments except the plots treated with the high rate of Matrix Pre, the Treflan PRE plus Matrix POST or the Shark POST 2X treatment. None of the treatments caused any visible tomato injury.

The number of redroot pigweed plants per plot also varied among treatments (Table 1). Both Treflan and Matrix treatments resulted in almost complete pigweed control. Spartan (Zeus) was intermediate in terms of pigweed control, while Prowl provided only partial control at best.

Tomato yield was highest when Treflan was used at 2.0 lb/a (Table 2). These plots had consistently lower weed cover, which may have accounted for the yield response. Red fruit yield was negatively correlated with field bindweed cover at harvest (r2= - 0.462).

WSREC – Drip Irrigated Main and split plot treatment affects are shown in Table 1, and show weed and crop phytotoxicity ratings based on a 0 – 10 scale, where 10 indicates all weeds/phyto. Thus, these results are the inverse of the control ratings used at Davis (e.g., high ratings indicate high weed pressure). Best control of field bindweed was observed with PPI Treflan at 2 pints/A. This treatment had significantly lower field bindweed on the May 30 and June 14 evaluation dates, but this effect was marginal on Aug 9. At that time, the untreated plots had a bindweed score of 7.3 compared to 4.3 for the Treflan treated area. This means that the best PPI treatment provided only about 50% control of the bindweed by the end of the season.

Application of Matrix or Shark as a post treatment provided significant suppression of bindweed as compared to the untreated plots on all evaluation dates (Table 1).

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Matrix performed better than Shark, but again by the end of the season average control was marginal – only about 50%. Best overall bindweed control occurred with the Treflan PPI + Matrix POST or Treflan PPI + Shark POST treatment (Figures 2, 3, 4).

All of the PPI treatments significantly reduced other broadleaf weeds (mainly puncture vine, pigweed, lambsquarters, purslane, and nightshades) as compared to the untreated control at all evaluation dates (Table 1). Unlike with bindweed, the addition of post emergence herbicide did not improve weed control (Figs 2, 3, 4). Grassy weeds were mostly not present at this location, and were only present at the end of the season (Figure 4).

Crop injury was noted in the PPI Prowl, Treflan, and Zeus treatments and in any treatment where Shark was applied. Visible crop injury was gone by the end of the season (Figure 4), however, some Shark and Treflan plots resulted in the complete loss of plants.

The main effect of the additional herbicide treatments are shown in Table 2. The application of Treflan both as a pre-plant and at layby gave best overall bindweed and other broadleaf control of all the treatment combinations tested in this trial. End of the season bindweed rating was 3.8, compared to the untreated at 7.3.

Yields for both trials are shown in Tables 3 and 4. As at UC Davis, best overall yields occurred with Treflan applied PPI and at layby, for a total of 2 lbs/A. Overall, however, yields were very low, averaging less than 20 tons/A for either trial. No significant differences in color, pH, or soluble solids were noted for any of the treatments.

Conclusions: Overall, the Treflan treatment has remained near the top among treatments for the past three years. Doubling the rate of Matrix also appeared to improve field bindweed control. Treating postemergence with Shark or Matrix also reduced field bindweed levels, but bindweed in the crop row could not be treated with the shielded application used with Shark. The combination of a preemergence herbicide and either Matrix or Shark applied postemergence, or applying Treflan both pre and at layby, were the best treatments for field bindweed in these trials. Future work will continue to optimize the best treatments and examine timing to best manage field bindweed.

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Figure 1. Shielded sprayer to apply Shark herbicide at WSREC.

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Figures 2 and 3. Field bindweed, other broadleaf weeds, and crop phytotoxicity ratings for all treatment combinations at WSREC on May 30 and June 14, 2012.

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Figure 4. Weed ratings on August 9, WSREC 2012.

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