Farm & Business 13(1)

Farm & Business 13(1) July 2021

EDITOR-IN-CHIEF

Carlisle A. Pemberton The University of the West Indies (UWI), St. Augustine, The Republic of Trinidad and Tobago.

EDITORIAL ADVISORY BOARD

Compton Bourne UWI, St. Augustine, The Republic of Trinidad & Tobago Carlton G. Davis University of Florida, Gainesville, Florida, USA Vernon Eidman University of Minnesota, St. Paul, USA

EDITORIAL COMMITTEE

Govind Seepersad UWI, St. Augustine, The Republic of Trinidad & Tobago Edward A. Evans UF/IFAS, University of Florida, Homestead, Florida, USA Isabella Francis-Granderson UWI, St. Augustine, The Republic of Trinidad & Tobago

Kishalla Floyd Editorial Associate Afiya De Sormeaux Editorial Associate Savita Maharajh Editorial Assistant Kavita Butkoon Cover Design

ISSN 1019–035X

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

Improving Profitability and Livelihood of Rice Farmers by Adopting an Integrated Disease Management (IDM) Approach for Blast and Sheath Blight Disease in Guyana

Rajendra Persaud1*, Mahendra Persaud1, Nizam Hassan1, Oudho Homenauth2 and Duraisamy Saravanakumar3

1Guyana Rice Development Board, Rice Research Station, Burma, Mahaicony, East Coast Demerara, Guyana. 2National Agricultural Research and Extension Institute (NAREI), Mon Repos, East Coast Demerara, Guyana. 3Faculty of Food and Agriculture, The University of the West Indies, St. Augustine, Trinidad and Tobago. *Corresponding author: Rajendra Persaud, [email protected]

Abstract

The profitability of rice production in Guyana has been adversely affected by two major diseases viz. blast (Pyricularia oryzae) and sheath blight (SB) (Rhizoctonia solani). To overcome these threats, it is necessary to develop and adopt an IDM approach. A study was carried out: to identify blast and SB resistant genotypes; to study the efficacy of plant extracts, bioagents and new generation fungicides against these disease. Of 103 rice lines, 11 showed highly resistant to resistant reactions to blast. Genotype FL-127 consistently expressed high blast resistance. Likewise, FG12-56 and GR1631-35-16-1-2-1-1 recorded immune to resistant reactions and 12 other exhibited very resistant to resistant reactions to SB. Plant extracts of Black sage 10%, Bael 15% and Madar plant 5% reduced blast infection in field experiments; likewise extracts of Lemon grass and Thick leaf thyme 15% reduced SB under field conditions. The bioagent, Bacillus cereus OG2L and B. subtilis OG2A significantly reduced blast; while B. cereus OG2L effectively reduced SB. The fungicides, Antracol 70WP and Nativo 75 WG showed superior control against blast; while the same 2 fungicides along with Serenade 1.34 SC showed high control of SB disease. These treatments also showed positive influence in growth and increase in yield of rice.

Keywords: rice disease control; resistant; plant products; bioagents; new generation fungicides.

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

Introduction

Rice provides more that 35% to 75% of the calorie and a high percentage of protein intake for nearly 520 million people living in poverty in Asia (Muthayya et al. 2014, 7; Khush 2005, 1). It accounts for 20% of the global calorie intake (Ugochukwu et al. 2017, 67). In African, Latin American and Caribbean countries, there has been a steady increase in the daily consumption of rice, which fulfills at least a third of the dietary intake of nearly one billion people (Shastry et al. 2000). The cultivation of rice also provides employment for over 200 million households and it is one of the primary sources of income for persons across the countries in the developing world (Muthayya et al. 2014, 7). Of the several factors that destabilize rice yield, diseases are among the most important and account for crop losses of varying levels. More than 70 diseases caused by viruses, bacteria, nematodes, and fungi have been recorded in rice with an estimated yield loss of 20% to 70% (Ou 1985; Mew et al. 1993). In rice production, rice blast and sheath blight cause an estimated annual loss of more than 37% and 25% respectively, worldwide. (Oerke and Dehne, 2004; Oerke, 2006, 35-36). These rice pathogens can attack the rice plant at all the growth stages, from the nursery to harvest. The disease incidence also varies with the different geographical area and from season to season (Ou 1985). In Guyana, the rice industry is one of the most important agricultural industries and generates more than US$ 220 million annually, which amounts to approximately 10% of the country’s export earnings (GRDB, 2020). It is also one of the largest users of agriculture lands in Guyana with an area of around 206,428 ha being harvested in 2019, with a total production of around 1,050,000 tonnes and an estimated yield of approximately 50,865 kg/ha in 2019 (FAOSTAT 2021). The rice industry has about 12,000 farmers and supports at least 10% of Guyanese population directly or indirectly. It also contributes to more than 20% of the country’s agricultural GDP (GRDB 2020). In Guyana, rice is grown mainly within five regions of the country. In the different geographical regions, the crop suffers from many disease. Among them, rice blast and sheath blight are two of the most important disease affecting the rice industry (GRDB 2020). These diseases threaten the sustainable production and cause great economic yield losses in Guyana. Blast disease caused by the fungal pathogen (Teleomorph: Magnaporthe grisea; M. oryzae; Anamorph: Pyricularia grisea; P. oryzae) is one of the most serious constraints to rice production at the global level. It is one of the most devastating diseases in at least 85 countries worldwide (Ou 1985). The disease has been reported to destroy sufficient rice that can fulfill the dietary needs for over 60 million persons on an annual basis (Roy-Barman and Chattoo 2005, 930). The blast fungus, P. oryzae often overcomes the resistance conferred by major R-genes after a few years of intensive agricultural use due to the rapid genetic evolution of the fungal pathogen. The host plant resistance has played a key role in sustainable rice production and productivity in many parts of the world, therefore it is considered as an important tool in the management of blast disease (Fahad et al. 2014; Vasudevan et al. 2014, 1). Likewise, Sheath blight disease (Teleomorph: Thanatephorus cucumeris (A.B.Frank) Donk.; Anamorph: Rhizoctonia solani) is considered to be an important disease next to blast in most of the Asian countries (Roy 1993; Srinivasachary, Willocquet, and Savary 2011, 1; Bhuvaneswari and Raju 2012, 57). It was reported from different rice growing regions of the world and has also become a severe concern for rice production especially in intensive production

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021 systems. The yield losses range from 1% to 50.0% due to sheath blight disease (Ou 1973). Under severe disease conditions, yield losses are reported to be as high as 90% (Ou 1973; Tang et al. 2007, 219; Gaihre, Raj, and Nose 2013, 133). The levels of severity and losses to the crop depend on environmental conditions, the plant growth stage at infection and the rice varieties grown. The soil-borne nature of the pathogen and long survival of its sclerotia make the control of this disease difficult. However, the employment of host resistance against sheath blight has little scope as no commercial rice cultivar has been found to possess donor level resistance (Roy 1993; Mew et al. 2004, 105; Pinson, Capdevielle, and Oard 2005, 503; Liu et al. 2013, 113; Yadav et al. 2015, 1). Similarly, a large number of plant extracts, biocontrol agents have been reported against blast and sheath blight disease, yet no attempt has ever been made in Guyana to develop these as alternative management strategies for their control. In addition, there has been a dependency on a particular fungicide for the control of blast and sheath blight disease. This could lead to a number of problems such as pathogen resistance, over use and failure to give adequate disease control. Therefore, there is a need to identify a new generation of fungicides that can be used in the event that an epidemic or a disastrous disease situation should arise. In view of the foregoing, this research was put together to come up with an integrated disease management (IDM) to manage the blast and sheath blight disease with the aim to identify blast resistant germplasm; SB resistant and slow blighting genotypes and to study the efficacy of plant extracts, bioagents and new generation fungicides against blast and SB disease.

Materials and Methods

Isolation purification, and aggressiveness test of the Pyricularia oryzae and Rhizoctonia solani

The leaves expressing typical symptoms of blast disease were collected from the rice fields of GRDB, RRS, Burma for isolation of the pathogen. Likewise, plant samples expressing typical symptoms of sheath blight disease were collected from the susceptible rice cultivars raised in the fields GRDB, RRS, Burma and nearby farmer’s fields during the spring season, 2015 The isolation of P. oryzae was done as described by Ghazanfar, Habib, and Sahi (2009, 41); while the isolation of R. solani was done similarly as described by Kazempour (2014, 89) with slight modifications. The infected rice plant parts were cut into small pieces (0.5-1.0 cm) and surface sterilized with 2% sodium hypochlorite for two minutes. The cut pieces were then washed three times with sterilized water and placed on petri plates containing PDA. These PDA plates were incubated at 27+2ºC for 5 days. The pathogen was identified by studying the colony characteristics of the isolates on PDA plates by following the method described in a technical bulletin on seed borne disease and seed health testing of rice (Agrawal et al. 1989). The pathogenicity of isolates was confirmed by following Koch’s postulates. Aggressiveness test of the isolates was performed. The most aggressive isolate was identified based on the disease severity in test plants. The agar slants and petri plates of pure culture of the most aggressive isolate of both P. oryzae and R. solani were prepared and stored at 4ºC for further use.

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

Germplasm tested for blast and sheath blight disease resistant screening

A total of hundred and three (103) and one hundred and one (101) germplasm lines were screened against blast and sheath blight disease, respectively. These entries were obtained from the rice crop germplasm collections at GRDB, RRS, Burma. Fifty entries were from the Observation Yield Trials (OYT), thirty six from two Advanced Yield Trials (AYT) and the remaining germplasm lines represented the most popular cultivars grown in Guyana along with the susceptible check variety, Rustic.

Location and nursery preparation for blast resistance screening

The experiment was conducted at Canje, Black Bush Polder and Onverwagt back of Guyana during the first (spring) and second (autumn) season, 2015 and autumn, 2016. The confirmatory study with selected germplasm lines which recorded highly resistant to resistant (HR –R) and susceptible to highly susceptible (S-HS) was carried out in spring season, 2017. The evaluation for blast resistance was performed under upland conditions employing the Upland Blast Nursery (UBN) technique (Ou 1985; Ghazanfar, Habib, and Sahi 2009, 42) with a slight modification to the design. The nursery beds of 1 metre width were prepared to raise the seedlings. Grooves were drawn across the width of the beds at 10 cm distance apart and two lines boarding the two end of the furrow. The susceptible variety (Rustic) was sown in the outer bordering rows and in two rows across the full length of the bed after every five grooves. The seeds of 103 test rice lines were carefully sown in the grooves separately in the center of the beds without touching the two outer border lines. The bed was covered with wood shavings to prevent movement of seeds, which may be caused by watering, rainfall or birds. Watering was done over sown nursery beds with sprinkler type water cans to ensure that rice seeds were settled and fixed. The watering continued daily for the first 7 days, thereafter 2 to 3 times per week throughout the experiment. The standard crop production practices were followed. The foliar application of nitrogenous fertilizer was done at 0.2% at every 5 to 7 days interval.

Inoculation of UBN with P. oryzae

A mixture of naturally existing blast strains collected from diseased plantlets of blast susceptible variety (Rustic) from the locality (Canje, Black Bush Polder and Onverwagt Back) and fields surrounding the disease nurseries were used as a source of inoculum. The infected leaves with blast symptoms were prepared by chopping into small pieces and spread over the entire nursery, especially between the susceptible check rows, when the seedlings in the nursery were at 5, 10, and 15 days old. The inoculum with the most aggressive isolate extracted from the disease leaves of P. oryzae were prepared in the laboratory. The conidial suspension was adjusted to 1×106 conidia per ml and sprayed three times per week on the entire nursery. In addition, the seedlings were sprayed with water early in the morning within 8 to 9 am and afternoon after 4:30 pm every day to extend the leaf wetness period and maintain the humidity.

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

Scoring for leaf blast

The UBN was monitored regularly for growth and occurrence of disease in seedlings. The evaluation and recording of data were done at 21 to 35 days after sowing when the susceptible check reached a score of 8 to 9. The disease scoring was performed based on the Standard Evaluation System (SES) described by International Network for Genetic Evaluation of Rice (INGER), (IRRI 1996; IRRI 2013).

Table i. Disease rating scale used for screening of blast disease in nursery seedlings (IRRI 1996; IRRI 2013) Grade Disease severity Host response 0 No lesion observed Highly Resistant 1 Small brown specks of pin point size Resistant 2 Small roundish to slightly elongated, necrotic gray spots, about 1-2 Moderately Resistant mm in diameter, with a distinct brown margin. Lesions are mostly found on the lower leaves 3 Lesion type same as in 2, but significant number of lesions on the Moderately Resistant upper leaves 4 Typical susceptible blast lesions, 3 mm or longer infecting less than Moderately 4% of leaf area Susceptible 5 Typical susceptible blast lesions infecting 4-10% of the leaf area Moderately Susceptible 6 Typical susceptible blast lesions of 3 mm or longer infecting 11-25% Susceptible of the leaf area 7 Typical susceptible blast lesions infecting 26-50% of the leaf area Susceptible

8 Typical susceptible blast lesions of 3 mm or longer infecting 51-75% Highly Susceptible of the leaf area many leaves are dead 9 Typical susceptible blast lesions infecting more than 75% leaf area Highly Susceptible affected

Location and conditions used for screening rice germplasm against sheath blight

The field experiments were conducted under low land irrigated conditions at Onverwagt back during spring and autumn seasons of 2015 and spring of 2016. In this experiment, the genotypes were evaluated against natural infection of sheath blight disease. The experiment was also conducted under semi-controlled screen house conditions at the GRDB, RRS, Burma during the spring of 2015 and autumn of 2016. In this study, the rice genotypes were also evaluated against the artificial inoculation of sheath blight pathogen.

Field evaluation of genotypes against sheath blight under field conditions

The fields were prepared at Onverwagt back as per the standard recommendations of GRDB for rice cultivation. Each genotype was direct sown in 2 meter row with 2 rows for each entry with a row to row spacing of 20 cm. The susceptible check cv. Rustic was sown in double row after every ten test entries and as border crop surrounding the outer areas. The standard crop production practices were followed. Weed control was done manually with in experimental area. Fertilizers were applied at a rate of N 120 P50 K0 kg/ha at the recommended timing. The trials

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021 were monitored regularly. The observations recorded from the maximum tillering to flowering stages. The percent disease severity was calculated and performance rating was derived as per the Standard Evaluation System (SES) of IRRI (1988) (Table ii)

Table ii. Percent disease severity and performance rating for sheath blight disease Scale Severity for incidence Expended code 0 - Immune 1 Less than 1% Very resistant 3 1-5% Resistant 5 5-25% Intermediate between resistant and susceptible 7 25-50% Susceptible 9 More than 50% Very susceptible

Screen house evaluation of genotypes against sheath blight under artificial inoculated conditions

The seedlings of the 101 genotypes were prepared using standard seed beds procedure within the seedling nursery at RRS, Burma. At 21 days after sowing (DAS) the seedlings of 101 genotypes including susceptible check were carefully uprooted and transplanted in concrete bins (1.5 x 1.5 M) filled with soils at screen house, GRDB, RRS, Burma during the autumn season, 2015 and spring season, 2016. Each genotype was planted in 1.4 meter row with a plant to plant spacing of 20 cm and replicated two times. At 25 days after transplanting, the primary tillers of three hills were selected and inoculated with fresh sclerotia of 7-9 days old culture of R. solani. The inoculation was done by gently placing single sclerotium in the second leaf sheath from top or into the lowest leaf axis of the leaf sheath just 5 to 8 cm above surface level. After inoculation the entire experimental area sprayed with water periodically for seven days in order to maintain the humidity. The disease development was recorded at 7, 14, 21, 28 and 35 days after inoculation (DAI). The Percent Disease Severity and the Area Under Disease Progress Curve (AUDPC) value were calculated. The AUDPC was computed using the following formula (Prescott et al. 1986)

k AUDPC = ∑ 1/2 (Si + Si -1) x d i =1 Where, Si = Disease severity at ith day k = Number of successive evaluation of disease d = interval between I and i-1 evaluation of disease

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

AMMI analysis to understand genotype and environment interactions for both blast and sheath blight resistance screening

The AMMI model was applied for blast resistance screening, with additive effects for the 103 rice genotype (G) and seven testing seasons (Environments = E) over three locations and multiplicative term for genotype‐by‐environment (G x E) interactions. Likewise, the additive effects for the 101 rice genotypes (G) and five testing environments (E) over two locations for sheath blight resistance and multiplicative term for genotype by environment (G x E) interactions were analyzed in this study. The disease severity data from seven and five locations, respectively were structured to suit the AMMI analysis. The AMMI statistical model structure and computational methods were employed as described in Zobel et al. (1988); Nayak et al. (2008) Gauch (2013); Mohamed (2013); Mukherjee et al. (2013) and Sharifi et al. (2017). The ANOVA was generated using the computer software program MATMODEL version 3.0 (Gauch 2007). The AMMI biplot and PC analysis were carried out by using software program developed by IRRI referred to as Plant Breeding Tools Version 1.4 (PBTools 2014). As the data contains zero for immune lines, 0.05 have been included for all the individual observation to derive the results directly from the biplot graph generated. The normal additive analysis of variance analysis (ANOVA) were utilized to partition the variation into G main effects and E main effects and genotype by environment (G x E). The principal component analysis (PCA) was applied to partition the G x E interaction into several principal components.

Collection and preparation of plant extracts

Fresh and healthy parts of eleven plants (Table iii) were collected from surrounding areas of the Rice Research Station, Burma in region number 5 (Mahaica-Abary), Guyana and carefully transferred to the Laboratory of Plant Pathology Department, RRS, Burma.

Table iii. Plants used for extraction in this study S.N. Common name* Scientific name Plant parts used 1 Neem Azadirachta indica Leaf & stem 2 Tulsi Ocimum basalicum Leaf & stem 3 Lemon grass Cymbopogan flexousus Leaf 4 Thick leaf thyme Thymus vulgaris Leaf & stem 5 Aloe Aloe vera Plant 6 Marigold Tagetes patula Leaf & stem 7 Black sage Cordia curassavica Leaf, stem & fruit 8 Bael Aegle marmelos Leaf & stem 9 Chives Allium fistulosum Plant 10 Clove Syzygium aromaticum Dry flower 11 Madar plant Calotropis gigantean(C. procera) Leaf, stem & flower *All eleven plant extracts were tested at 5%, 10% and 15% concentration against blast and sheath blight pathogen (Table iii).

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

The plant samples were washed with running tap water and then rinsed two times with sterile distilled water and left to air dry for 2 to 3 hours. The selected plant parts were then cut into small pieces (1-2 cm). One hundred gram of cut pieces of plant tissue were then ground with one hundred milliliters of sterile distilled water (1:1 W/V) with mortar and pestle and then filtered through a double layered white muslin cloth into a beaker. The filtrate was collected and stored in a sterile conical flask at 250C to 280C for further study (Devi and Chhetry 2013). This served as 100% stock solution of the plant extract.

Evaluation of plant extracts against P. oryzae and R. solani in vitro

The Poisoned food technique (Grower and Moore 1962) was employed to assess the efficacy of plant extracts against R. solani. Eleven plant extracts were prepared at 5%, 10% and 15% concentrations in PDA. Varying amounts of each plant extract were dispensed and thoroughly mixed in slightly warm PDA medium in requisite quantity, to give a final concentration of 5%, 10% and 15%. A volume of 15 ml medium was poured in petri plate for each treatment and replicated three times. After solidification of the medium, 5 mm disc of 7 day-old culture of P. oryzae and R. solani was placed at center of each set of petri plates. The plates were incubated at 28+2ºC in BOD incubator and observed for radial growth at 9 days after inoculation. The control was maintained by inoculating the pathogen on PDA plates without addition of plant extracts. The radial growth of mycelium in plates amended with different concentrations of plant extracts was measured and compared with the radial growth of control plates.

Screening of new generation fungicides against P. oryzae and R. solani in vitro

The new generation fungicides listed in Table iv evaluated for their efficacy against P. oryzae and R. solani under in vitro using poisoned food technique (Grower and Moore 1962). Three rates of fungicides were prepared and amended in PDA medium as indicated in Table iv. The PDA plates amended with various concentrations of fungicides were inoculated with P. oryzae and R. solani and incubated at 27+2ºC for 9 days. The radial mycelial growth was observed in fungicide amended plates. The PDA plates without amendment of fungicides served as control. Percent inhibition of mycelial growth in treatment over control was calculated as per formula described by Vincent (1947):

퐼 = 100 [ (퐶 − 푇)/퐶]

Where, I = % inhibition over control C = Mycelial growth in control T = Mycelial growth in treatment

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

Table iv. New generation fungicides and rates used in the study Trt Chemicals Active ingredients *Rates/ ac T1 500 g T2 Antracol 70WP Propineb 1,000 g T3 1,500 g T4 250 g T5 Nativo 75 WG Trifloxystrobin+ Tebuconazole 350 g T6 450 g T7 200 ml T8 Silvacur Combi 30 EC Tebuconazol+Triadimenol 500 m T9 800 ml T10 400 ml Biological-Fungicide (Bacillus subtilis T11 Serenade 1.34 SC 800 ml Strain QST 713) T12 1,200 ml T13 150 ml Organic Fungicides (Cinnamon Oil 8%, T14 Cyclops 200 ml Clove Oil 2%) T15 250 ml T16 Fugione Isoprothiolane 300 ml T17 Control Distilled water - *All rates were determined based on the label claims.

Screening of bioagents against P. oryzae and R. solani using dual culture test

Three biocontrol isolates (Table v) were obtained from the Rhizobacterial culture collection of Plant Pathology Laboratory, Department of Food Production, The University of the West Indies, St. Augustine (Thomas and Saravanakumar 2015). The biocontrol isolates were tested against P. oryzae and R. solani by dual culture methods as described in Morton and Stroube (1955) and Saravanakumar et al. (2007). PDA medium of 15 ml was poured in petri plate (9.0 cm) and allowed to solidify. A 5 mm disc of P. oryzae of 9 days old culture while a single sclerotium of 7 days old culture of the R. solani was placed at one side of the petri plate. The biocontrol isolates were streaked at perpendicular to P. oryzae and R. solani at a distance of 4 cm and incubated at 272ºC for 9 days. The percent inhibition of P. oryzae and R. solani with each bacterial isolate was calculated. Three replicated plates were maintained for each isolate. Plates streaked with sterilized water in place of bacterial isolates served as control. The percent inhibition of P. oryzae and R. solani was expressed for each isolate in comparison to the control plates as per formula given above. The dual culture test was also conducted with the King’s medium B (KMB) and inhibition observed.

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

Table v. Rhizobacterial strains used in the current study S.N. Bioagents 1 Bacillus cereus strain OG2L 2 Bacillus subtilis strain OG2A 3 Azotobacter sp. SAG19

Evaluation of plant extracts, bioagents and new generation fungicides against rice blast and sheath blight disease under field conditions

The plant extracts, bioagents and new generation fungicides showed high efficacy against P. oryzae (Table vi) and R. solani pathogen under in vitro studies (Table vii) were selected for the evaluation against blast and sheath blight disease in separate field trials. For the blast disease experiment, two field trials were conducted during the spring and autumn seasons of 2016 at Plant Pathology Experimental Site, Onverwagt Back in Guyana. Likewise, for the sheath blight screening experiment, two separate field trials were established; one at Onverwagt Back and other at Burma back in Guyana during spring season, 2016. The highly susceptible cultivar ‘Rustic’ was used in this both study. Randomized Block Design (RBD) was employed with three replications per treatment. The crop was raised by direct seeded method at a rate of 180 lbs/ac with an individual plot size of 3 m X 5 m (15 m2). Standard agronomic practices were followed throughout the cropping period. The treatments were applied as foliar spray two times at maximum tillering stage (18 to 25 days after sown) at an interval of 7 days starting from 5-7 days after leaf blast disease appearance as indicated in Table vi. Likewise, at maximum tillering stage (30 DAS), five plants in each plot with typical symptoms of sheath blight were randomly selected and tagged. The tagged tillers were assessed for the initial disease severity by measuring the lesion length and total sheath length. Also, as indicated in Table vii, the treatments were applied at 30 and 37 DAS by thoroughly mixing the specific solution of bioagents, plant extracts and new generation fungicides. The spray was done with the help of CP3 sprayer. The distilled water was sprayed in control plots.

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

Table vi. Plant extracts, biocontrol agents and new generation fungicides screened against blast disease under field condition Trt. Treatment Scientific name / a.i. Rate/acre

T1 Marigold Tagetes patula 5% T2 Black sage Cordia curassavica 10% T3 Bael Aegle marmelos 15% T4 Chives Allium fistulosum 10% T5 Madar plant Calotropis gigantean (C. procera) 5% T6 B. cereus OG2L Bacillus cereus 2 g/L T7 B. subtilis OG2A Bacillus subtilis 2 g/L T8 Azotobacter SAG 19 Azotobacter sp 2 g/L T9 Antracol 70WP Propineb 500 g/ac. T10 Nativo 75 WG Trifloxystrobin, Tebuconazole 250 g/ac. T11 Silvacur Combi 30 EC Tebuconazol, Triadimenol 200 ml/ac. T12 Serenade 1.34 SC Biological Fungicide (Bacillus subtilis cepa QST 400 ml/ac. 713) T13 Cyclops Organic Fungicides (Cinnamon Oil 8%, Clove Oil 150 ml/ac. 2%) T14 Fugione Isoprothiolane 300 ml/ac. T15 Control Distill Water -

Table vii. Plant extracts, bioagents and new generation fungicides used against sheath blight disease under pot culture and field studies Trt. Common names Scientific name / a.i. Rate/ acre

T1 Lemon grass Cymbopogan flexousus 15 % T2 Thick leaf thyme Thymus vulgaris 15% T3 Marigold Tagetes patula 15% T4 Clove Syzygium aromaticum 15% T5 B. cereus OG2L Bacillus cereus 1 g/L T6 B. subtilis OG2L Bacillus subtilis 2 g/L T7 Antracol 70WP Propineb 500 g/ac T8 Nativo 75 WG Trifloxystrobin, Tebuconazole 250 g/ac T9 Silvacur Combi 30 EC Tebuconazol, Triadimenol 200 ml/ac Serenade 1.34 SC Biological Fungicide (Baciillus subtalis cepa QST 400 ml/ac T10 713) Cyclops Organic Fungicides (Cinnamon Oil 8%, Clove Oil 150 ml/ac T11 2%) T12 Fugione (Check) Isoprothiolane 300 ml/ac T13 Control (Check) Distilled Water -

Assessment of disease severity and yield

The blast lesion length and disease intensity were recorded by randomly tagging five plants per plot. These observations were recorded at two times i.e. before the 1st spray and 7 days after 2nd spray. The Percent Disease Severity was calculated based on the 0-9 scale of INGER, IRRI (2002) using the following formula:

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

푃푒푟푐푒푛푡 퐷𝑖푠푒푎푠푒 푆푒푣푒푟𝑖푡푦 (푃퐷푆) = 100 [(퐴푣푒푟푎푔푒 표푓 푡ℎ푒 푑𝑖푠푒푎푠푒 푠푐표푟푒)/9]

Also, percent change in disease severity (PDS), growth parameters, yield parameters over control were calculated using the following formula:

Percent Change = 100 x [(T-C)/C]

Where: C = Value in Control T = Value in Treatment

Likewise, the sheath blight disease development was assessed after 7 days of application of first treatment at 7 days interval up to 35 days. At harvesting, the impact of various treatments on growth parameters were assessed by measuring the plant height and counting the number of tillers per square meter. The yield parameters were assessed by measuring panicle length, counting the number of filled and unfilled grains and recording 1000 grain weight of 20 panicles randomly harvested from each experimental unit. The grain yield was assessed after harvest from sample area of 3 m X 5 m by threshing and recording the weight and moisture from each plots.

Statistical analysis

The data obtained from various laboratory and field experiments were analyzed using the appropriate Complete Randomized Design, Randomized Block Design statistical methods. The ANOVA and statistical significance were obtained using the Statistix 8.0 analytical software and graphs were derived using Microsoft excel software, 2013.

Results

Identification of blast resistant genotypes

One hundred and three rice genotypes were evaluated during 2015, 2016 and 2017 in this study (Table 1). These entries were tested against blast in Canje, Black Bush Polder and Onverwagt back of Guyana (Table 1). In both spring and autumn seasons of 2015; autumn season of 2016 and spring season of 2017, the germplasm FL-127 consistently showed highly resistant reaction (Table 1). Two entries, FG12-08 and FG12-273 were resistant across all environments and eight entries recorded blast reaction status between highly resistant and resistant (FG12-32, FG12-82, FG12-114, FG12-279, GR1493-6-9-1-3-2-2-2-2, G07-13-1, FG05-259 and G04-08). The reaction of twelve entries (FG12-05, FG12-16, FG12-148, FG12-281, GR1440-52-23-4-1-1- 1-1-2-1-2, GR1447-5-3-2-1-2-1-2-1, GR1624-28-23-1-2-1-1, GR1629-33-66-2-2-1-1, G07 -118, G11-102, FG12-23 and G06-123) were consistently moderately resistant in all seasons and locations tested; while another forty two entries (FG12-06, FG12-14, FG12-19, FG12-21, FG12- 27, FG12-32, FG12-33, FG12-41, FG12-78, FG12-98, FG12-101, FG12-270, FG12-277, GR1412-24-32-1-1-1-3-1-2-2-1-1, GR1412-24-32-1-1-1-3-1-2-2-1-1, GR1493-6-9-1-3-1-2-2-2,

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

GR1493-6-9-1-3-2-1-1-1, GR1600-4-41-1-1-2-1, GR1601-5-2-2-1-2-2, GR1617-21-11-1-4-1-2, GR1631-35-16-1-2-1-1, GR1636-40-47-2-1-1-1, GR1637-41-23-1-1-1-2, FG10-26, FG10-54, FG10-103, FL-121, G11-08, G11-09, G11-28, G11-101, FG12-29, GR 1516-29-16-2-3-1-1-1-1, GR 1568-32-3-2-2-2-1, GR 1580-43-23-1-1-1-2, GR 1584-47-8-2-2-1-1, GR 1585-48-9-2-1-1-1, FG07-35, FG06-98, G98-30-3, G98-22-4 and BR-444) recorded highly resistant to moderately resistant (score 0 to 3) (Table 1). On the other hand, twelve entries (GR14-14, GR 1562-25-16-2-1-2-1, GR 1562-25-26-1- 1-2-1, GR 1562-25-26-1-1-2-1, GR 1573-36-9-2-2-1-1, GR 1573-36-9-2-2-2-2, GP18, G98-135, G98-196, F7-10, DIWANI) recorded moderately susceptible to highly susceptible reaction to blast disease (score 4 to 9) across the environment studied. However, GP18 and the check (rustic) consistently showed highly susceptible reactions in all seasons at the three locations tested (Table 1). Also, twenty one entries out of the 103 entries recorded susceptible and above susceptible blast disease score (score > 6) at least once or more than once in over one or more locations and/or seasons over the study period. The rest of entries showed unstable and fluctuating reactions over the seasons and different locations ranged from resistance to highly susceptible (score 1 to 9). Out of 103 genotype evaluated, high percent of genotype recorded resistant (22%) to moderately resistant (51%) reaction and mean blast disease score (Figure 1). The high resistance was expressed in 8% of genotype. The moderate susceptibility, susceptibility and high susceptibility recorded in 11%, 4% and 4% genotype, respectively (Figure 1).

4% 4% 8% 11% 22%

51%

HR R MR MS S HS

HR = Highly Resistant, R = Resistant, MR = Moderately Resistant, MS = Moderately Susceptible, S = Susceptible, HS = Highly Susceptible Figure 1: Overall percent blast disease reaction of the 103 genotype tested over the seven environments in an Upland Blast Nursery (UBN)

In all the different season and locations, excellent germination and establishment were recorded in all the Upland Blast Nurseries (UBN). The disease pressure was also considered to

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021 be good, since the susceptible check (Rustic) consistently recorded highly susceptible blast disease reaction (Table 1).

AMMI1 Biplot display

The blast disease reaction scores of genotype appeared to range from zero (0) to nine (9), with a greater proportion of the genotype showing a more stable blast disease resistant status as evident by the clustering of the genotype towards the origin and lesser proportion showed higher level of blast disease susceptibility reaction status. The susceptible check, G 103 (Rustic) recorded stable susceptible reactions over all test environment (Figure 2). Genotype or environment appeared almost on the perpendicular (broken) lines having similar means. The genotype viz., G 42 (GR1621-25-19-1-2-1-1), G 72 (GR 1562-25-26-1-1-2-1), G 102 (IR 22), G 49 (GR1639-43-62-2-2-1-1), G 81 (GR 1580-43-2-1-1-2-1), G 22 (FG12-248), G 89 (FG07-35 ), G 77 (GR 1568-32-3-2-2-2-1), G 84 (GR 1584-47-8-2-1-2-1) was clearly identified from the biplot as having similar means (Figure 2). On the other hand, those genotype falling almost on a horizontal line have similar interaction pattern. In this study, few genotype [G 103 (Rustic), G 88 (GP18), G 97 (G98-196), G 101 (DIWANI), G 79 (GR 1573-36-9-2-2-2-2), G 14 (FG12-61), G 27 (FG12-281), G 8 (FG12-21), G 9 (FG12-27), G 66 (FG12-29), G 53 (FG10-26)] were clearly observed from the biplot for similar interaction pattern (Figure 2). Also, genotype or environment on the right side of the midpoint on the perpendicular (broken) lines have higher mean blast disease scores than those on the left side. As a result, it is quite evidence from the biplot that the genotype, G 103 (Rustic), G 88 (GP18), G 101 (Diwani), G 97 (G98-196), G 79 (GR 1573-36-9-2-2-2-2), G 50 (GR14-14), G 93(G98-135), G 7 (FG12-19), G 72 (GR 1562-25-26-1-1-2-1), G 42 (GR1621-25-19-1-2-1-1), G 70 (GR 1561-24-23-2-2-1-1), G 78 (GR 1573-36-9-2-2-1-1), G 1 (FG12-02), G 95 (G98-24-1), G 49 (GR1639-43-62-2-2-1-1), G 81 (GR 1580-43-2-1-1-2-1), G 28 (GR1401-13-47-4-1-3-1-1-1-1-1), G 14 (FG12-61) show high level of stable susceptibility. In contrast, G 52 (G07-13-1), G 9 (FG12-27), G 8 (FG12-21), G 89 (FG07-35), G 77 (GR 1568-32-3-2-2-2-1) showed lesser susceptibility and greater stable blast disease resistant reactions (Figure 2). Even though environment influence was observed to be tiny, E4 (Canje, Autumn 2015) and E1 (Canje, Spring 2015) were on the right hand side of the midpoint of the main effect axis suggesting that these environments were slightly more favorable for blast screening; while E 2 (Black Bush Polder, Spring 2015) and E7 (Onverwagt Back, Autumn 2016) were slightly less favorable; and the other remaining 3 environments viz. E6 (Canje, Autumn 2016), E3 (Black Bush Polder, Autumn crop, 2015) and E5 (Onverwagt Back, Autumn 2015) were intermediary between the two (Figure 2). Likewise, genotype or environment with IPCA1 scores of zero or near zero (either positive or negative) have small interactions and show greater stability and adoption over the test environment, while with a large IPCA1 scores have high interaction effect and reflect more specific stability and adoptions to specific environments. In this present case, E7 (Onverwagt Back, Autumn 2016) followed by E5 (Onverwagt Back, Autumn 2015) observed with low IPCA1 scores and showed small interactions (Table 1), while the opposite effect were recorded for E4 (Canje, Autumn 2015) followed by E2 (Black Bush Polder, Spring 2015), which showed greater interaction effects; while intermediate interaction effect were observed from the remaining environment, viz.

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

E1 (Canje, Spring 2015), E6 (Canje, Autumn 2016) and E3 (Black Bush Polder, Autumn 2015) (Table 1; Figure 2).

G= Genotype; E1 - Canje (Spring 2015); E2 - Black Bush Polder (Spring 2015); E3 - Black Bush Polder (Autumn 2015); E4 - Canje (Autumn 2015); E5 - Onverwagt Back (Autumn crop, 2015); E6 - Canje (Autumn 2016); E7 - Onverwagt Back (Autumn 2016)

Figure 2: AMMI1 Biplot display for mean blast disease reaction and IPCA 1 scores of the 103 genotype (G) tested across seven environments (E)

Similarly, a significantly larger proportion of genotype recorded low IPCA1 scores and show small interactions, which was one of the reason for the appearance of the clustering together of the genotype on the biplot (Figure 2); while a considerably lesser proportion recorded higher IPCA1 scores. Genotype G 42 (GR1621-25-19-1-2-1-1) and G 72 (GR 1562-25-26-1-1-2-1) recorded the highest IPCA1 score of 1.49 and 1.33, respectively; followed by few other genotype viz. G 89 (FG07-35), G 81 (GR 1580-43-2-1-1-2-1), G 77 (GR 1568-32-3-2-2-2-1), G 70 (GR 1561-24-23-2-2-1-1), G 49 (GR1639-43-62-2-2-1-1), G 22 (FG12-248), G 102 (IR 22) that recorded IPCA 1 score above 0.6 (either positive or negative). This implied that high interaction effect of specific genotype and reflected more specific stability and adoptions to specific environments (Table 1).

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

Identification of resistant, slow blighting rice genotypes for sheath blight

The reactions of these genotype over the three seasons under field conditions and the two seasons under artificial inoculated conditions are presented in Table 2. Over the five test environment, two genotype viz., FG12-56 and GR1631-35-16-1-2-1-1 consistently recorded immune to resistant (score 0 to 3); five genotype viz. GR1440-52-23-4-1-1-1-1-2-1-2, GR1602- 6-41-1-1-2-1, IR-94, G11-08 and G98-135 expressed very resistant to resistant reaction (score 1 to 3) and seven genotype viz. FG12-02, FG12-14, FG12-41, FG12-270, G11-103, FG07-35 (GRDB-12) and BR-444 recorded with consistently resistant sheath blight disease reaction (score 3) (Table 2). On the other hand, genotype GR 1568-31-9-1-1-2-1 and the check cv. Rustic consistently expressed susceptible reactions (score 7) over both conditions and seasons tested (Table 2). Susceptible reaction of score 7 was consistently observed for cv. Rustic in all environments. This served as a bench mark for reliability of the reactions of the test entries. Also the conditions that prevailed at Onverwagt back during the two cropping seasons were highly favourable for natural development of sheath blight disease.

Efficacy of plant extracts against P. oryzae and R. solani under in vitro

The results of evaluation of three concentrations of plant extracts against P. oryzae and R. solani presented in Table 3. The blast pathogen recorded significantly lower mycelial growth in PDA plates amended with 5% extracts of Marigold (11.67 mm) and Clove (12.67 mm) compared to control (90.00 mm). Likewise at 10% concentration, extracts of Black sage and Chive recorded lower mycelial growth (12.33 mm and 12.67 mm, respectively) when compared to other plant extracts and control. At 15% concentration, extracts of Bael exhibited high inhibition to mycelial growth (80.37%) over the control (Table 3). Similarly, the results from the evaluation of plant extracts against R. solani under in vitro condition showed that extracts of lemon grass, thick leaf thyme and clove recorded significantly similar and lowest mycelial growth (5.00 mm each, respectively) and highest percent inhibition (94.44% each, respectively) at 15% concentration. The plant extracts of marigold also significantly reduced the mycelial growth (6.66 mm) of R. solani over the control (Table 3). However, in both P. oryzae and R. solani screening trials the results indicated that each concentration of plant extracts had positive effect on the inhibition of mycelial growth of P. oryzae and R. solani. Therefore, the plants extracts with the lower mycelial growth and high percentage inhibition at the lowest concentration were selected from the in vitro study for further evaluation under field conditions against P. oryzae and R. solani (Table 3).

Efficacy of new generation fungicides against P. oryzae and R. solani under in vitro

All of the new generation fungicides tested at three different rates (Table 4) under in vitro exhibited high inhibition to the mycelial growth of P. oryzae and R. solani. Therefore, the lowest rates for each fungicide were selected for further evaluation under field conditions.

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

In vitro antagonistic potential of bioagents against P. oryzae and R. solani using dual culture test

The Bacillus isolate, B. cereus OG2L, B. subtilis OG2A and Azotobacter SAG19 exhibited more than 50% inhibition to mycelial growth of P. oryzae over control in dual culture assay. The statistical analysis revealed that there were no significant difference between the three strains of bioagents used in the study. However, all three biocontrol isolates significantly inhibited the mycelial growth when compared to control (Table 4). Likewise, when the 3 isolates were evaluated against R. solani in vitro, B. cereus OG2L showed significantly high percent inhibition to R. solani (43.33%) restricting the mycelial growth to 51.00 mm against control (90.00 mm). However, the other two isolates, B. subtilis OG2A and Azotobacter SAG19 did not show inhibition to R. solani as that of B. cereus OG2L (Table 4). Therefore, B. cereus OG2L was selected for further testing against sheath blight disease under field conditions.

Efficacy of plant extracts, bioagents and new generation fungicides against blast disease in field trials

The results of application of plant extracts, bioagents and new generation fungicides against blast disease in field trial I (Table 5) conducted in spring 2016 recorded significantly lowest lesion length and percent disease severity in Bael extract (16.60 mm; 46.67%), B. subtilis OG2A (17.73 mm; 51.85%) and Antracol 70WP (18.55 mm; 48.89%) compared to untreated control (53.60 mm; 80.00%). The application of B. cereus OG2L (18.73 mm; 48.89%), Black sage (18.87 mm; 48.15%) and Madar plant (18.87 mm; 48.89%), Nativo 75 WG (19.00 mm; 48.15%), along with positive check Fugione (22.40 mm; 46.67%) and Serenade 1.34 SC (25.40 mm; 51.85%) also recorded significantly low lesion length and disease severity compared to untreated control. In addition to untreated control, the higher lesion length and disease severity were observed in the application of Marigold (42.80 mm; 60.74%), chives (46.00 mm; 71.11%), Azotobacter SAG 19 (45.67 mm; 71.85%) and Silvacur Combi 30 EC (44.93 mm; 71.85%). These treatments were statistically different from untreated control in reducing lesion length and disease severity (Table 5). The field trial II conducted during autumn, 2016 showed the application of Black sage (19.00 mm; 56.29%), Bael extract (18.07 mm; 57.78%), Madar plant (20.84 mm; 70.37%), B. cereus OG2L (18.13 mm; 54.81%), B. subtilis OG2A (18.60 mm; 55.56%), Antracol 70WP (19.27 mm; 59.26%), Nativo 75 WG (17.73 mm; 60.00%), Serenade 1.34 (17.33 mm; 59.26%) and positive check Fugione (20.60 mm; 57.04%) recorded significantly low lesion length and disease severity compared to other treatments (Table 5). The disease assessment before the application of treatments at both trials indicated that the disease severity and lesion length were distributed uniformly over experimental units.

Assessment of reduction in disease severity of field trial I and II

The calculation of percent reduction in disease severity (Figure 3) has indicated that application of plant extracts, biocontrol agents and new generation fungicides demonstrated

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021 varying percentage of disease reduction over untreated control. During autumn 2016, application of plants extracts of Black sage, Bael and Madar plant; biocontrol agents B. cereus OG2L and B. subtilis OG2A; new generation fungicides, Antracol 70WP, Nativo 75 WG, Serenade 1.34 SC and Fugione observed with 41.78 to 48.15% reduction in disease severity over untreated control. In spring 2016, the same treatments also showed high percent reduction in disease severity varying from 32.75 to 38.54% (Figure 3). 0

-10

-20

-30

over control (T15)control over -40

-50 Percent decrease in mean disease mean severity decrease percent in Percent -60 T1 T2 T3 T4 T5 T6 T7 T8 T9 T10 T11 T12 T13 T14 Spring,2016 -30.279 -46.351 -48.152 -14.734 -45.437 -45.408 -41.77 -14.142 -45.437 -46.351 -13.961 -41.78 -39.911 -48.139 Autumn,2016 -17.418 -37.340 -35.554 -18.498 -34.617 -39.272 -38.549 -16.244 -33.578 -32.758 -14.083 -33.856 -16.216 -36.670 Treatments

T1- Marigold; T2- Black stage; T3- Bael extract; T4- Chives; T5- Madar plant; T6 B. cereus OG2L; T7- B. subtilis OG2A; T8- Azotobacter SAG 19; T9- Antracol 70WP; T10- Nativo 75 WG; T11-Silvacur Combi 30 EC; T12- Serenade 1.34 SC; T13- Cyclops; T14- Fugione (Check); T15- untreated control

Figure 3: Percentage decrease in mean percent disease severity over the negative control (T15) treatment

Efficacy of plant extracts, bioagents and new generation fungicides against P. oryzae on growth and yield parameters of field trials

Plant height and number of tillers

The greater plant height was recorded in B. subtilis OG2A (82.17 cm) treated plots while high number of tillers per square meter observed in application of Nativo 75 WG (314.67 No./ m2). The shorter plant height and less tiller per square meter was recorded in Azotobacter SAG 19 (75.67 cm and 241.22 No./ m2, respectively). The untreated plots recorded low plant height (75.77 cm) and tiller per square meter (270.67 No./ m2) (Table 6). On the other hand, no significant differences in plant height and tillers per meter square were observed in autumn, 2016 (Table 7).

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

The panicle length

The high panicle length was recorded in plots treated with B. subtilis OG2A (23.74 cm) followed by Antracol 70WP (23.44 cm), Serenade 1.34 SC (23.17 cm) and Nativo 75 WG (23.14 cm). The statistical analysis revealed that there were no significant among these four treatments. The low panicle length was recorded in untreated control plots (19.43 cm), followed by Cyclops (19.65 cm), Marigold (19.82 cm) and Chives (20.21 cm) treated plots in field trial conducted in spring, 2016 (Table 4.9). In autumn 2016, the plots treated with B. subtilis OG2A (21.710 cm), Nativo 75 WG (21.643 cm), Serenade 1.34 SC (21.29 cm) recorded the high panicle length. The shortest panicle length was recorded in untreated control (18.88 cm), followed by Silvacur Combi 30 EC (19.16 cm), Cyclops (19.36 cm) and Azotobacter SAG 19 (19.42 cm) (Table 7).

Grain filling potential

The observation on number of filled grains per panicle recorded significantly high filled grains in plots treated with Bael extract (64.37 No. of filled grains/ panicle) in spring 2016 and B. subtilis OG2A (68.43 No. of filled grains/ panicle) in autumn, 2016. The low number of filled grains per panicle was recorded in untreated control (19.43; 18.88 No. of filled grains/ panicle) during both season trials. Also statistically similar and higher number of filled grains per panicle were observed in Black sage, Bael extract, B. cereus OG2L; B. subtilis OG2A, Serenade 1.34 SC and Fugione (the positive check) treatments as compared to the untreated control (Table 6; Table 7). The significantly low number of unfilled grains per panicles was observed in treatment, B. cereus OG2L (8.40 No./ panicle) followed by B. subtilis OG2A (8.97 No./ panicle), Fugione (9.50 No./ panicle), Black sage (10.10 No./ panicle) and Serenade 1.34 SC (10.40 No./panicle) in spring, 2016 (Table 4.9). During autumn 2016 field trial, statistically similar and low number of unfilled grains per panicle were recorded in plots treated with B. cereus OG2L (9.73 No./ panicle) followed by Black sage (10.23 No./ panicle), Serenade 1.34 SC (10.53 No./ panicle), B. subtilis OG2A (10.67 No./ panicle) and Fugione (11.27 No./ panicle) (Table 7).

Grain weight and yield

B. cereus OG2L, Serenade 1.34 SC and Black sage treated plots recorded significantly high 1000-grain weight over the two cropping seasons as compared to untreated control. In addition to these treatments, Nativo 75 WG and Fugione (the positive check) treated plots also recorded statistically better 1000-grain weight as compared to Cyclops, Silvacur Combi 30, Chives and untreated control (Table 6). Almost similar trends for 1000-grain weight were noted in autumn, 2016 field trial (Table 7). In spring 2016 field trial, significantly high grain yield was recorded from plots treated with B. cereus OG2L (5139.10 kg/ ha), Nativo 75 WG (4964.50 kg/ ha), Fugione (4954.70 kg/ ha), Bael extract (4913.10 kg/ ha), Black sage (4870.50 kg/ ha) and Antracol 70WP (4868.60 kg/ ha) compared to other treatments and untreated control (4166.90 kg/ ha). It was also noted in the study that the application of Chives (3756.80 kg/ ha) recorded less grain yield than untreated control (4166.90 kg/ ha) (Table 6). A similar trend was observed for grain yield for the autumn 2016. The grain yield recorded from the plots treated with Madar plant, Bael extract, Black sage,

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

B. cereus OG2L, B. subtilis OG2A, Nativo 75 WG, Antracol 70WP, and Fugione did not show significance among each other (Table 7). Over two seasons, the application of B. cereus OG2L and Nativo 75 WG showed high percent increase in grain yield ranging from 19.14 to 23.33%. The application of Black stage, Bael extract, Madar plant, B. subtilis OG2A, Antracol 70WP and Fugione consistently showed an increase in grain yield by greater that 15% (Figure 4). The treatments Marigold, Chives, Azotobacter SAG 19, Silvacur Combi 30 EC, Cyclops and untreated control consistently recorded lower yields (Table 7) and higher levels of disease severity (Table 5).

25.000

20.000

15.000

10.000

5.000 over (T15) over control 0.000

-5.000

Percent increase or decrease in mean grain yield (kg/ha) grain yield mean in or decrease increase Percent -10.000 T1 T2 T3 T4 T5 T6 T7 T8 T9 T10 T11 T12 T13 T14 Spring,2016 10.35 16.88 17.90 -9.84 15.97 23.33 15.89 -0.01 16.84 19.14 3.401 16.30 11.11 18.90 Autumn,2016 9.536 17.29 18.00 9.501 19.91 22.74 20.42 7.649 18.52 21.99 7.174 11.40 4.608 16.83 Treatments

T1- Marigold; T2- Black stage; T3- Bael extract; T4- Chives; T5- Madar plant; T6- B. cereus OG2L; T7- B. subtilis OG2A; T8- Azotobacter SAG 19; T9 - Antracol 70WP; T10-Nativo 75 WG; T11-Silvacur Combi 30 EC; T12- Serenade 1.34 SC; T13- Cyclops; T14- Fugione (Check); T15- untreated control

Figure 4: Percentage increase or decrease in mean grain weight (kg/ha.) over the control (T15) treatment

Efficacy of plant extracts, bioagents and new generation fungicides against sheath blight in field trial I and II

Among the plants extracts, the application of extracts of lemon grass and thick leaf thyme recorded low disease severity with an AUDPC value of 173.20; 139.04 and 161.85; 133.71 in trial

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

I and II respectively. Similarly, the bioagent B. cereus OG2L at 2 g/l recorded low disease severity with AUDPC of 170.39; 138.23 in trial I and II respectively. Among new generation fungicides, Antracol 70WP, Nativo 75 WP, Serenade 1.34 SC recorded low disease severity with an AUDPC of 179.34, 144.10; 147.19, 132.32; 170.36, 141.08 in trial I and II respectively. The untreated control plots recorded the high disease incidence with an AUDPC of 548.09; 419.19 in trial I and II respectively. The analysis of disease severity data showed the significant disease control by extracts of lemon grass and thick leaf thyme; bioagent B. cereus OG2L at 2g/L; new generation fungicides, Antracol 70WP, Nativo 75 WP, Serenade 1.34 SC compared to untreated control in trial I and II (Table 8 & 9).

Efficacy of plant extracts, bioagents and new generation fungicides against R. solani on growth and yield parameters in two field trials

Plant height and number of tillers

A significantly higher plant height was recorded in the application of biocontrol agent, B. cereus OG2L at 129 g/ ha in both field trials, as 93.91cm and 85.70cm, respectively (Table 10 and 11). The trial I at Onverwagt location, all treatments were statistically similar in terms of recording higher plant height with the exception of marigold (85.88cm) and untreated control (85.94cm), which registered significantly lower plant height. In the trial II at Burma back, B. cereus OG2L at 129 g/ ha (85.70cm) and Antracol 70 WP (82.42cm) recorded the higher plant height, while the other treatments showed statistically similar plant height to untreated control (73.55 cm) (10 and 11). There was no statistically significant difference between treatments for number of tillers per square meter. However, high number of tillers per square meter observed in plots treated with Serenade 1.34 SC in both field trails, as 318.67 tillers/m2 and 317.33 tillers/m2. This was followed by the positive check, Fugione as 317.33 tillers/m2 and 314.67 tillers/m2 in trial I and trial II, respectively (Table 10 and 11).

The panicle length, filled and unfilled grains

The statistically longer panicle length in trial I and II were recorded in plots treated with B. cereus OG2L at 2 g/l (22.79 cm; 23.32 cm), followed by Serenade 1.34 SC (23.44 cm; 22.80 cm) compared to untreated control (18.83 cm and 19.43 cm), respectively (Table 10 and 11). The significantly high number of filled grains per panicle recorded in both trials in plots treated with B. cereus OG2L at 129 g/ ha (53.47; 54.70), followed by Serenade 1.34 SC (53.70; 55.47) as compared to other treatments and untreated control (39.30; 38.37). The application of Lemon grass, Thick leaf thyme, Antracol 70WP, Fugione and Nativo 75 WG also recorded high number of filled grains. It was interesting to observe significantly low number of unfilled grains in B. cereus OG2L at 2 g/l (10.23/panicle) and Serenade 1.34 SC (11.53/panicle) treatments. Inversely, higher number of unfilled grains per panicle recorded in untreated control in both field trials (23.43; 20.23/panicle). The plots treated with Cyclops, Silvacur Combi 30, Marigold, Antracol 70WP and Clove also observed with high number of unfilled grains per panicle (Table 10 and 11).

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

Grain weight and yield

In trial I at Onverwagt back in spring 2016, application of B. cereus OG2L at 2 g/l (31.93 g), Serenade 1.34 SC (31.52 g) and Lemon grass (31.16 g) recorded significantly high 1000 grain weight followed by Thick leaf thyme (30.95) and the positive check Fugione (30.90 g) as compared to control treatment (28.25 g) (Table 10). In trial II at Burma back in spring 2016, the almost similar trend was observed with high 1000 grain weight as in Trial I. B. cereus OG2L at 2 g/L (32.36 g), followed by Serenade 1.34 SC (31.23 g), B. cereus OG2L at 1 g/l (31.50 g), Lemon Grass (31.24 g) and Thick leaf thyme (30.90 g) recorded high grain weight compared to untreated control (27.14 g) (Table 11). In Trial I, significantly high grain weight was recorded in plots treated with Nativo 75 WG (6409.70 kg/ha), followed by Lemon grass (6392.50 kg/ha), Serenade 1.34 SC (6391.30 kg/ha), B. cereus OG2L at 2 g/ l (6388.50 kg/ha), Fugione (6322.30 kg/ha) and Thick leaf thyme (6272.40 kg/ha) compared to other treatments and untreated control. At the same time, the plots treated with new generation fungicides, Antracol 70WP, Silvacur Combi 30 EC and Cyclops and the lower rate of the bioagent, B. cereus OG2L at 1 g/l also recorded statistically high grain weight as compared to the untreated control (Table 10). It was also observed that plots treated with Marigold and Clove were statistically similar to untreated control despite their high grain yield (Table 10). Almost similar trend was observed for grain yield in trial II. The plots treated with Serenade 1.34 SC (6946.80 kg/ha), followed by B. cereus OG2L at 129 g/ ha (6563.10 kg/ha), Thick leaf thyme (6314.00 kg/ha), Nativo 75 WG (6301.40 kg/ha), Fugione (6264.70 kg/ha) and Lemon grass (6099.50 kg/ha) recorded significantly high grain weight compared to untreated control (5106.70 kg/ha) (Table 11).

Discussion

Rice blast and sheath blight diseases have become a serious problem over the years and has been reported to cause significant yield losses in various parts of the world (Ou 1985, Khush and Jena 2009, Sharma et al. 2012, Brooks, 2007; Webster and Gunnell, 1992; Pramesh et al., 2016). This present research identified a rice genotype (FL-127) as highly resistant and two genotypes (FG12-08 and FG12-273) as resistant. Similarly eight genotypes recorded blast reaction status ranging from highly resistant to resistant. These new advanced germplasms were identified from different genetic backgrounds and possess donor level resistance to the blast disease. These germplasms could be used in rice breeding program as source materials for isolation of novel rice blast resistance genes or for further development and release as blast resistant varieties. On the other hand, highly susceptible reaction (score 8 and 9) was consistently observed in Rustic in all experimental trials. This served as a bench mark for the reliability of the reactions of the test entries. Similar finding were reported by Pasha et al. (2013) where IRBLZ-FU/RL, CT18232-5-9-1-2-6-3, CT18233-15-6-6-4-8-1, CT18235-3-9-1-2-3-4, IR33225-45-3-1-1 and IR04A325 genotypes were identified as moderately resistant to Iran-47 rice blast isolate and other genotypes had resistant reaction. Likewise, in West Africa, some of the improved resistant donors identified were ITA 12, ITA 239, ITA 302, ITA 324, ITA 414, ITA 416, Tox 3118-47-1-1-2-3, Tox

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

3226-5-2-2-2, TAC 84-4, IR 36, IR 72, WIAT 3, WAB 56-50, WAB 56-104, IAC 257, LAC 23, IRAT 10, and Moroberekan (Singh et al. 2000). Similarly, Persaud (2002) found twelve genotypes viz., WAB 56-50, B6144-F-MR-6-0-0, Moroberekan, IR42221-145-2-3-2, 5173, Bala, RR166-645, RR345-2, IR71677-106-1-5, IR71693-197-4-1, IR64 and RI207-257-5-274-1, possess high level of resistance to blast, at a blast “hot spot”, Ambikapur, in Chhattisgarh State of India during Kharif 2002. During the period from 2003 to 2005, Persaud (2006) identified eight strains viz., IR42221- 145-2-3-2, 5173, B6441-F-MR-6-0-0, VL16,C101 A51, G9502, BR 240 and F7 10 that showed stable resistant reactions over the years. Also Arshad et al. (2008) evaluated 40 germplasms during 2005-2006 against the blast disease and reported the resistance of four germplasms (99513, KSK-10, Kala Shah Kaku and DM-2-25-9-02). In as separate investigation carried out by Ravikumar et al. (2014) evaluated 91 advanced breeding lines for leaf blast resistance and found AE258, AE279, AE280, E408 and the resistant check NLR 145 showed highly resistant reaction. Also, a known major rice breeding goal for many rice cultivating countries is the development of high yielding cultivars combined with resistance to sheath blight. The use of resistance is known to be the most environmentally friendly and economical way of managing the sheath blight disease (Liu et al. 2009, 1078). Extensive research has been done over the years to identify sources of resistance in rice germplasm (Silva et al. 2012, 63-64; Jia et al. 2012; Dubey et al. 2014). In spite of evaluating “more than 30,000 rice germplasm accessions, no effective source of resistance to the sheath blight pathogen has been identified” (Mew et al. 2004, 105). Further, the screening of various rice germplasm lines for sheath blight resistance were exhaustively done by various researchers and no complete donor level resistance has been found (Liu et al. 2013, 113; Srinivasachary, Willocquet, and Savary 2011, 1; Yadav et al. 2015, 1). However, a number of scientists have demonstrated large variations in the level of resistance to the sheath blight pathogen under field condition. Interestingly, Prasad and Eizenga (2008, 1503) tested 60 wild Oryza spp. germplasm from 15 species under laboratory, greenhouse and field conditions and found seven Oryza spp. accessions (IRGC100898, IRGC104705, IRGC104443, IRGC100223, IRGC100943, IRGC105306 and IRGC105979) from five, Oryza spp viz. O. meridionalis, O. barthii, O. nivara, O. officinalis, and O. sativa as moderately resistant to sheath blight disease. Also, the breeding and development of varieties resistant to sheath blight was explored by using conventional breeding techniques. Rush et al. (2011, 400) had used the modified recurrent selection and backcross breeding methods over a 25 year period and registered 25 germplasm lines as resistant and moderately resistant, with sheath blight rating ranged from 3.3 to 5.2% disease severity. The challenges to develop resistant commercial varieties are ongoing since that only few resistance sources have been identified (Yadav et al. 2015). Many other authors also utilized various advanced molecular techniques to study the whole genome of the rice to identify non-synonymous single nucleotide polymorphism (nsSNPs) and candidate genes for resistance to sheath blight (Silva et al. 2012, 63). The researchers did identify two accessions of O. nivara with a resistant nsSNP alleles; this suggests sources for resistance occur in additional Oryza spp. Liu et al. (2013,113) confirmed quantitative trait loci (QTLs) using 216 recombinant inbred lines and found major ShB-QTL qShB9-2 based on field data. This present investigation revealed similar findings as elaborated above with respect to the variation in resistance of genotypes identified. Out of 101 genotypes

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021 evaluated under field and artificial inoculated conditions, two (FG12-56 and GR1631-35-16-1-2- 1-1) consistently recorded reaction statuses rang from immune to resistant; five (GR1440-52-23- 4-1-1-1-1-2-1-2, GR1602-6-41-1-1-2-1, IR-94, G11-08 and G98-135) very resistant to resistant and seven (FG12-02, FG12-14, FG12-41, FG12-270, G11-103, FG07-35 (GRDB-12) and BR- 444) with resistant reactions over the five test environments. On the other hand, genotype GR 1568-31-9-1-1-2-1 and the check cv. Rustic consistently recorded susceptible reactions over all the experiments. Similar findings were also reported by Persaud (2009), out of the 39 rice varieties tested under natural field conditions 2 genotypes (R-1249-1440-3-1 and R-1240-927-3-1056-1) showed no disease symptom and expressed immune reaction, followed by Shyamala which recorded resistant disease reaction (4.36% disease severity). The highest percentage disease severity was recorded in Badsha Bhog (48.23%) followed by R-1238-692-820-1-1, Purinima, Danteshwari and P-44-BR. Apart from the resistance breeding programme, there is the need for the development of effective management strategies for these two major rice disease has become extremely important. The effectiveness of several plant extracts have extensively been reported by many researchers against several pathogenic fungi. Khoa et al., (2011) found that seed soaking and foliar spraying of extracts of either fresh or dried leaves of Chromolaena odorata reduced 68% in sheath blight disease under controlled and semi- field conditions. The same researchers have also reported the control of bacterial blight (Xanthomonas oryzae pv. oryzae) by 50% using both seed treatment and foliar sprays; brown spot (Bipolaris oryzae) by 57% using seed treatment, blast (P. oryzae) by 45% using foliar spray and. Similarly, extracts of Eucalyptus globules, Calotropis procera and Andrographis paniculata at 2% were reported as significantly effective in reducing stem rot of paddy (Sclerotium oryzae) (Venkateswarlu, 2013). Yadav and Thrimurty (2006) also reported the complete inhibition of mycelial growth of Sarocladium oryzae by leaf extracts of Mentha viridis (M. spicata). Several studies had reported the inhibitory effect and disease control mechanism of different plant extracts against R. solani (Ghangaonkar, 2007; Kagale et al., 2011; Mogle, 2013). In the present investigation, eleven aqueous plant extracts were evaluated under in vitro and field conditions for their efficacy against rice blast (P. oryzae) and sheath blight pathogen (R. solani). Five of the plant extracts viz., Marigold at 5%, Black sage at 10%, Bael extract at15%, Chives at 10% and Madar plant at 5% significantly inhibited the mycelial growth of blast fungus, P.oryzae in vitro; While Four plant extracts viz., Lemon grass, Thick leaf thyme, Marigold and Clove at 15% expressed high inhibition to mycelial growth of R. solani. Application of three plant extracts viz. Black sage at 10%, Bael extract at 15% and Madar plant at 5% provided excellent control of the blast disease; likewise the application of Lemon grass and Thick leaf thyme extract at 15% demonstrated significant control of the sheath blight disease. From this present study, it is evident that these extracts possess antimicrobial activities against the blast and sheath blight pathogen. Handique and Singh (1990) reported similar finding, where Lemongrass oil has showed antimicrobial activity against R. solani, Sclerotium rolfsii, and Sclerotinia sclerotiorum. More specifically, the lemongrass oil showed 67% and 100% reduction in the growth of R. solani at 100 and 1000 ppm respectively. It was reported that the traces of phytochemicals flavonoids, terpenoids and phenolic compounds in the lemon grass could be responsible for the antifungal activities (Abu-seif et al., 2009). Therefore, the current study also

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021 agree that the existence of antifungal compounds in the lemon grass could be responsible for reduction in sheath blight disease. Similarly, essential oils of Thymus vulgaris showed effective control of R. solani (Khaledi et al., 2015; Arraiza et al., 2009; Zambonelli et al., 2004). The characterization of T. vulgaris plants demonstrated the presence of antifungal compounds viz., carvacerol, thymol, p-cymene, γ- terpinene, 1, 8-cineole, geranial and β-caryophyllene (Arraiza et al., 2009; Zambonelli et al., 2004; Horváth et al., 2006). These compounds kill the fungus by altering the mitochondria, endoplasmic reticulum and crinkling of the plasmalemma, swelling of the cytoplasm and accumulation of lipid bodies of the fungus (Zambonelli et al., 2004). Therefore, it is assumed in the current study that the antifungal compounds in the extracts of Thick leaf thyme could reduce the sheath blight disease in rice. Besides disease control, the extracts of Lemon grass and Thick leaf thyme increased the growth parameters and grain yields compared to untreated control. This finding is in agreement with the findings of Harish et al., (2008). Where the efficacy of fifty plant extracts were investigated against rice brown spot disease (Bipolaris oryzae. In glasshouse and field trial, N. oleander 52 and 53% reduction in the disease incidence, respectively and showed an increase in yield by 15%. In addition to the plant extracts, the current study also demonstrated the efficacy of two isolates, B. cereus OG2L and B. subtilis OG2A each at 2 g/L against the blast disease and B. cereus OG2L against sheath blight disease. A number of microbial antagonists have been developed as an alternative strategy for the control of many plant diseases including the blast and sheath blight (Mew and Rosales, 1986; Gnanamanickam and Mew, 1990; Tan and Mew, 2001; Manikandan et al., 2010; Shrestha et al., 2016). The antagonism, competition, lysis and induction of defense enzymes were regarded as mechanisms of biological control of plants diseases (Saravanakumar et al., 2007; Saravanakumar et al., 2008; Saravanakumar et al., 2009; Karthiba et al., 2010). Therefore, it is proved in the current study that the antagonistic activities of the bioagents, induction of defense enzymes and growth promotion could played a major role in the reduction of disease severity and increase of yield in rice. It is also interesting to note that the use of biocontrol agents considered as valid approach and explored with new strains of bioagents isolated from the soil rhizosphere. Hence, the bioagent identified in the current study could formulate the viable strategy for the management of leaf blast and sheath blight disease in rice. Likewise, several researchers have tested numerous fungicides and found all or few as effective in the control of various fungal diseases affecting the cultivation of rice. The evaluation of new generation fungicides revealed the high efficacy of Tilt 25 EC (Propiconazole) against sheath blight (R. solani), sheath rot (Fusarium moniliforme) and brown spot (Drechslera oryzae) of rice under laboratory and field conditions (Lore et al., 2007). At the same time, the application of traditionally old fungicides such as Dithane Z-78 at 0.25% (Mancozeb) and Kitazine (Organophosphorus) 48EC at 0.2% were found to be least effective against the three diseases. Similarly, the application of new generation fungicides Tilt, Bavistin & Antracol found to be effective against sheath rot in rice (Thapak et al., 2003). Recently, it was reported that application of combination of fungicides viz., RIL-068/F1 48 WG (Kresoxim methyl 40% + Hexaconazole 8% WG), and Fluxapyroxad + Epoxiconazlle 62.5 g/l EC (Adexar w/v EC) were effective against sheath blight disease (Prasanna and Veerabhadraswamy, 2014).

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

In this current study, though five fungicides (Antracol 70WP - Propineb; Nativo 75 WG - Trifloxystrobin + Tebuconazole; Silvacur Combi 30 EC - Tebuconazol + Triadimenol; Serenade 1.34 SC - Bacillus subtilis cepa QST 713; Cyclops - Cinnamon Oil 8%+Clove Oil 2%) exhibited high inhibition to the mycelial growth of P. oryzae and R. solani, only two fungicides viz. Antracol 70WP at 500 g/ac, Nativo 75 WG at 250 g/ac demonstrated high efficacy against the blast disease; likewise the same two fungicides (Antracol 70WP at 500 g/ac, Nativo 75 WG at 250 g/ac ) along with Serenade 1.34 SC at 400ml/ac demonstrated effective control against sheath blight disease under field conditions. The review of mode of action of different chemical compounds present in the new generation fungicides answer the reasons for their effective control of these two diseases. The combination of strobilurin and azole compounds in Nativo 75 WG could affect the quinones and sterol biosynthesis in the fungal pathogens. At the same time, though the combination of Tebuconazol + Triadimenol present in Silvacur Combi 30 EC, both the compounds display the same of mode of action i.e. sterol biosynthesis. This single mode of action could explain the display of less efficacy by Silvacur Combi 30 EC when compared to Nativo 75 WG. Besides disease control, these fungicides also increased the grain yield in the current study compared to untreated control. Therefore, this findings is in agreement with reports of Dutta et al., (2012); Jagadeeshwar et al., (2014); Hegde (2015); Pramesh et al., (2016); and Mushineni et al., (2017) who also evaluated several new generation fungicides (including Nativo 75 WG) and reported that the new generation fungicides such as Metaminostrobin 20 SC, Tebuconazole, Nativo 75 WG (Trifloxystrobin 25% + Tebuconazole 50%), Azoxystrobin 23% SC, and captan 70% + heaxaconazole (5%) 5 WP, showed effective control of various rice (including blast and sheath blight) disease as well as an higher increased in the grain yield as compared to the untreated control. Therefore, the first recommendation in this integrated disease management approach is to utilize the resistant and tolerant cultivars identified. In event where the resistant cultivar is not available, the control effects of the plant products and bioagents compared favorably with that of the new generation fungicide. Therefore, these botanicals and bioagent identified can be used as the second options in the management of the blast sheath blight disease, since are expected to be more environmentally friendly and sustainable alternative substitutes in the event that these new generation fungicide are not available.

References

Abu-Seif, F. A., Abdel-Fattah, S.M., Sreia, Y.H.A., Ramadan, M.M., 2009. Antifungal Properties of Some Medicinal Plants against Undesirable and Mycotoxin-Producing Fungi. Mansoura University Journal of Agricultural Sciences. 34, 1745-1756. Agrawal, P. C., C. N. Mortensen, and S. B. Mathur, 1989: Seed Borne Diseases and Seed Health Testing of Rice. In Technical Bulletin No.3- Phytopathological paper No. 30, edited by CAB Int., 7. Kew, Surrey, UK: CAB Int. Mycological Ins. Arraiza, M. P., Andrés, M.P., Arrabal, C., López, J. V., 2009. Seasonal Variation of Essential Oil Yield and Composition of Thyme (Thymus vulgaris L.) Grown in Castilla-La Mancha (Central Spain). Journal of Essential Oil Research. 21, 360-362.

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

Arshad, H. M. I., J. A. Khan, and F. F. Jamil, 2008: Screening Of Rice Germplam against Blast and Brown Spot Disease. Pak. J. Phytopath. 2, 52-57. Bhuvaneswari, V., and S. Krishnam Raju. 2012. “Efficacy of New Combination Fungicide against Rice Sheath Blight Caused by Rhizoctonia solani (Kuhn).” Journal of Rice Research 5 (1&2): 57-60. Brooks, S.A., 2007. Sensitivity to a phytotoxin from Rhizoctonia solani Correlates with Sheath Blight Susceptibility in Rice. Phytopathology. 97, 1207-1212. Devi, O. J., Chhetry, G. K. N., 2013. Evaluation of Antifungal Properties of Certain Plants against Drechslera oryzae causing Brown Leaf Spot of Rice in Manipur Valley. International Journal of Scientific and Research Publications. 3, 1-3. Dubey, A. K., R. T. P. Pandian, H. Rajasekara, M. Kumari, and U. D. Singh. 2014. “Evaluation of Rice Genotypes for their Reaction to Sheath Blight Disease.” Annals of Agri-Bio Research 19 (4): 737-740. Dutta, D., Saha, S., Ray, D.P., Bag, M.K., 2012. Effect of Different Active Fungicides Molecules on the Management of Rice Blast Disease. Intl. J. Agric. Env. Biotech. 5, 247-251. Fahad, Shah, Lixiao Nie, Faheem Ahmed Khan, Yutiao Chen, Saddam Hussain, Chao Wu, Dongliang Xiong, et al. 2014. “Disease Resistance in Rice and the Role of Molecular Breeding in Protecting Rice Crops against Diseases.” Biotechnol. Lett. doi: 10.1007/s.10529-014-1510-9. FAOSTAT. 2021. “Food and Agricultural Organization of the United Nations Statistics”. Accessed on 26 April, 2021. http://www.fao.org/faostat/en/#data/GR Gaihre, Yuba Raj, and Akihiro Nose. 2013. “High Yielding Capabilities and Genetic Variation in Crossing of Sheath Blight Disease Resistant Rice Line.” Field Crops Research 149:133– 140. Accessed 12th October, 2017. http://dx.doi.org/10.1016/ j.fcr.2013.04.009. Gauch, H. G. Jr., 2007: MATMODEL (Version 3.0), Open source software for AMMI and Related Analyses. Crop and Soil Sciences, Cornell University, Ithaca, NY 14853. Accessed 10th January, 2017. http://www.css.cornell.edu/ staff/gauch/ matmodel.html. Gauch, H. G. Jr., 2013: Review and Interpretation: A Simple Protocol for AMMI Analysis of Yield Trials. Crop Science 53, 1860–1869. Ghazanfar, M. U., A. Habib, and S. T. Sahi, 2009: Screening of Rice Germplasm against Pyricularia oryzae the cause of Rice Blast Disease. Pak. J. Phytopathol. 21, 41-44. Ghangaonkar, N. M., 2007. Efficacy of Plant Extracts on the Post-Harvest Fungal Pathogens of Onion Bulbs. Bioinfolet 4, 291-294. Gnanamanickam, S. S., Mew, T. W., 1990. Biological Control of Rice Diseases (Blast and Sheath Blight) With Bacterial Antagonists: An Alternative Strategy for Disease Management. In Pest Management in Rice. Edited by B. T. Grayson, M. B. Green, and L. G. Copping, 87- 110. Elsevier Applied Science, London. Grover, R. K., Moore J. D., 1962. Toximetric Studies of Fungicides against the Brown Rot Organism, Sclerotium fructicola and Sclerotium laxa. Phytopathology. 52, 876-880. Guyana Rice Development Board (GRDB), 2020: Technical Annual Report, GRDB. Accessed on 26 April, 2021. http://www.grdb.gy/ Handique, A. K., Singh, H. B., 1990. Antifungal Action of Lemongrass Oil on Some Soil-Borne Plant Pathogens. Indian Perfumer. 34, 232-234.

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

Harish, S., Saravanakumar, D., Radjacommare, R., Ebenezar, E. G., & Seetharaman, K., 2008. Use of Plant Extracts and Biocontrol Agents for the Management of Brown Spot Disease in Rice. BioControl. 53, 555-557. Hegde, G.M., 2015. Efficacy of Tebuconazole 25% WG against Blast and Sheath Blight Diseases of Rice in Central Western Ghats of Uttar Kannada District.” ORYZA-An International Journal on Rice. 52, 222-226. Horváth, G., Szabó, L.G., Héthelyi, É., & Lemberkovics, É., 2006. Essential Oil Composition of Three Cultivated Thymus Chemotypes from Hungary. Journal of Essential Oil Research. 18, 315-317. IRRI, 1996: Standard Evaluation System (SES) for Rice. 4th ed. International Rice Research Institute (IRRI), Manila, Phillipine: INGER Genetic Resources Center. IRRI, 2013: Standard Evaluation System (SES) for Rice. 5th ed. IRRI, Manila, Phillipine: INGER Genetic Resources Center. IRRI. 1988. Standard Evaluation System (SES) for Rice. IRRI, Manila, Phillipine: INGER Genetic Resources Center. IRRI. 2002. Standard Evaluation System (SES) for Rice. IRRI, Manila, Philippine: INGER Genetic Resources Center. Jagadeeshwar, R., Varma, N.R.G., Reddy, P.R.R., Raju, C.S., Vanisree, S., Reddy B.G., Dayakar, S. 2014. Screening of New Fungicides against Location Specific Diseases of Rice Occurring in Southern Telangana zone of Andhra Pradesh. The J.Res. Angrau. 42, 18-21. Jia, Limeng, Wengui Yan, Chengsong Zhu, Hesham A. Agrama, Aaron Jackson, Kathleen Yeater, Xiaobai Li, et al. 2012. “Allelic Analysis of Sheath Blight Resistance with Association Mapping in Rice.” PLoS One 7 (3): e32703. Accessed November 10, 2017. https://doi.org/10.1371/journal .pone. 0032703. Kagale, S., Marimuthu, T., Kagale, J., Thayumanavan, B., and Samiyappan, R., 2011. Induction of Systemic Resistance in Rice by Leaf Extracts of Zizyphus jujuba and Ipomoea carnea against Rhizoctonia solani. Plant Signal Behavior. 6, 919-23. Karthiba, L., Saveetha, K., Suresh, S., Raguchander, T., Saravanakumar, D., Samiyappan, R., 2010. PGPR and Entomopathogenic Fungus Bioformulation for the Synchronous Management of Leaffolder Pest and Sheath Blight Disease of Rice. Pest Management Science. 66, 555-564. Kazempour, N. M., 2004. Biological Control of Rhizoctonia solani, the Causal Agent of Sheath Blight by Antagonistics Bacteria in Green House and Field Condition. Plant Pathology Journal. 3, 88-96. Khaledi, N., Taheri, P., Tarighi, S., 2015. Antifungal Activity of Various Essential Oils against Rhizoctonia solani and Macrophomina phaseolina as Major Bean Pathogens. Journal of Applied Microbiology. 118, 704-717. Khoa, Nguyễn Đắc, Phan Thị Hồng Thúy, Trần Thị Thu Thủy, David B. Collinge, and Hans Jørgen Lyngs Jørgensen. 2011. "Disease-Reducing Effect of Chromolaena odorata Extract on Sheath Blight and Other Rice Diseases." Phytopathology 101(2): 231-240. doi:10.1094/ PHYTO-04-10-0113. Khush, G. S., and K. K. Jena, 2009: Current Status and Future Prospects for Research on Blast Resistance in Rice (Oryza sativa L.), In Advances in Genetics, Genomics and Control of Rice

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

Blast Disease, edited by G. L. Wangand B. Valent (Dordrecht: Springer).1-10. doi:10.1007/978- 1-4020-9500-9-1. Khush, Gurdev S. 2005. “What it will take to Feed 5.0 Billion Rice Consumers in 2030.” Plant Molecular Biology 59:1-6. doi:10.1007/s11103-005-2159-5. Liu, G., Y. Jia, A. McClung, J. H. Oard, F. N. Lee, and J. C. Correll. 2013. “Confirming QTLs and finding Additional Loci Responsible for Resistance to Rice Sheath Blight Disease.” Plant Disease 97:113-117. Accessed November 11, 2017. https://doi.org/10.1094/PDIS-05-12- 0466-RE Lore. J.S., Thind, T.S., Hunjan, M.S., Goel, R.K. 2007. Performance of different fungicides against multiple diseases of rice. Indian Phytopathology 60, 296-301. Manikandan, R., Saravanakumar, D., Rajendran, L., Raguchander, T., Samiyappan, R., 2010. Standardization of Liquid Formulation of Pseudomonas fluorescens Pf1 for its Efficacy against Fusarium Wilt of Tomato. Biological control. 54, 83-89. Mew T. W., Leung, H., Savary, S., Vera Cruz, C. M., Leach, J. E., 2004. Looking Ahead In Rice Disease Research and Management. Critical Reviews in Plant Sciences. 23, 103-127. Mew, T. W., & Rosales, A. M., 1986. Bacterization of Rice Plants for Control of Sheath Blight Caused by Rhizoctonia solani. Phytopathology. 76, 1260-1264. Mew, T. W., A. M. Alvarez, J. E. Leach, and Jean Swings. 1993. “Focus on Bacterial Blight of Rice.” Plant disease 77 (1): 5-12. Mogle, U. P., 2013. Effect of Leaf Extracts against the Post Harvest Fungal Pathogens of Cowpea. Bioscience Discovery. 4, 39-42. Mohamed, Naheif E. M. 2013. “Genotype by Environment Interactions for Grain Yield in Bread Wheat (Triticum aestivum L.).” Journal of Plant Breeding and Crop Science. 5 (7):150- 157. doi: 10.5897/JPBCS2013.0390. Morton, D. J., Stroube, W. H., 1955. Antagonistic and Stimulatory Effect of Soil Microorganism upon Sclerotium rolfsii. Phytopathology. 45, 417-420. Mukherjee, A. K., N. K. Mohapatra, L. K. Bose, N. N. Jambhulkar, and P. Nayak, 2013: Additive Main Effects and Multiplicative Interaction (AMMI) Analysis of G x E interactions in Rice-Blast Pathosystem to Identify Stable Resistant Genotypes. Glob. J. Crop, Soil Sci. Plant Breed. 1, 103-118. doi: 10.5897/ AJAR12.2118. Mushineni, A., Khalko, S., Jha, S., Bhattacharya, P. M., Roy, A., 2017. Effect of New Generation Chemicals in Changing Host Physiological Traits to Manage Sheath Blight Disease Caused by Rhizoctonia solani Kuhn in Rice. International Journal of Current Microbiology and Applied Sciences. 6, 351-357. Muthayya, Sumithra, Jonathan D. Sugimoto, Scott Montgomery, and Glen F. Maberly. 2014. “An Overview of Global Rice Production, Supply, Trade, and Consumption.” Annals New York Academy of Sciences 1324:7-14. doi: 10.1111/nyas.12540. Nayak, D., L. K. Bose, S. Singh, and P. Nayak, 2008: Additive Main Effects and Multiplicative Interaction Analysis of Host-Pathogen Relationship in Rice Bacterial-Blight Pathosystem. Plant Pathol. J. 24, 337-351. Oerke, E-C. 2006. “Crop losses to pests.” Journal of Agricultural Science 144 (1): 31-43. doi:10.1017/S0021859605005708.

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

Oerke, E-C., and H. W. Dehne. 2004. “Safe Guarding Production-Losses in Major Crops and the Role of Crop Protection.” Crop Protection 23 (4): 275-285. doi:10.1016/j.cropro.2003.10.001. Ou, S. H, 1985: Rice diseases, 2nd ed. Commonwealth Mycological Institute, Kew, Surrey, England. C.A.B. International, Farnham Royal, Slough. Ou, S. H., 1973. A Hand Book of Rice in Tropics. The International Rice Research Institute (IRRI), Los Banos, Laguna, Philippines. pp. 53. Pasha, A., N. Babaeian-Jelodar, N. Bagheri, G. Nematzadeh, 2013: Evaluation of Rice Genotypes for Resistance to Blast Isolates Iran-47 in Greenhouse. International Journal of Agriculture: Research and Review 3, 934-940. Accessed 06th November, 2017. http://www. ecisi.com. PBTools (Version 1.4), 2014: Biometrics and Breeding Informatics, PBGB Division, International Rice Research Institute, Los Baños, Laguna. Accessed from IRRI web site 15th January, 2017. http://bbi.irri.org/ products. Persaud, M., 2002: Genetics of Blast Resistance and Isolation of Resistance Donors in some Rice (Oryza sativa L.) Cultivars. Master’s thesis. The Indira Ghandhi Agricultural University, Raipur (C.G), India. Persaud, M., 2006: Identification and Genetic Analysis of Genes Conferring Resistance to Blast (Pyricularia grisea (av.) in Rice (Oryza sativa L.) Cultivars. Ph.D thesis. The Indira Ghandhi Agricultural University, Raipur (C.G), India. Persaud, Rajendra. 2009. “Studies on Plant Resistance against Sheath Blight of Rice Caused by Rhizoctonia solani Kühn.” Master’s thesis. The Indira Ghandhi Agricultural University, Raipur (C.G), India. Pinson, S. R. M., Capdevielle, F. M., Oard, J. H., 2005. Confirming QTLs and Finding Additional Loci Conditioning Sheath Blight Resistance in Rice Using Recombinant Inbred Lines. Crop Science. 45, 503-510. Pramesh, D., Maruti, K. M. Mallikarjun, M. K., Guruprasad, G. S., Mahantashivayogayya, K., Reddy, B. G. M., Chethana, B. S., 2016. Bio-efficacy of a Combination Fungicide against Blast and Sheath Blight Diseases of Paddy. Journal of Experimental Agriculture International. 14, 1-8. Prasad, B., and G. C. Eizenga. 2008. “Rice Sheath Blight Disease Resistance Identified in Oryza spp. Accessions.” Plant Disease 92:1503-1509. doi:10 .1094/PDIS-92-11-1503. Prasanna, Kumar, M. K., and A. L. Veerabhadraswamy. 2014. “Appraise a Combination of Fungicides against Blast and Sheath Blight Diseases of Paddy (Oryza sativa L.)." Journal of Experimental Biology and Agricultural Sciences 2 (1): 49-57. Prescott, J. M., Burnett, P. A., Saari, E. E., Ransom, J., Bowman, J., De Milliano, W., Singh, R.S., Geleta, A.B., 1986. Wheat Diseases and Pests, a Guide for Field Identification. CIMMYT, Mexico D.F. Mexico. Ravikumar, B. N. V. S. R., K. K. Rao, N. Chamundeswari, V. Bhuvaneswari, P. Nagakumari, P. V. R. Rao, M. G. Rani, P. V. Satyanarayana, Y. Suryanarayana, M. Bharatalakshmi, and A. V. Reddy, 2014: Screening of Advanced Breeding Lines for Seedling Blast Resistance in Rice (Oryza sativa L.) Using Microsatellite markers. Current Biotica 8, 125-131. Roy, A. K., 1993. Sheath Blight of Rice in India. Indian Phytopathology, 46, 197-205. Roy-Barman S, Chattoo BB. 2005. Rice Blast Fungus Sequenced. Current Sci. 89: 930–931.

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

Rush, M. C., D. E. Groth, and X. Sha. 2011. “Registration of 25 Sheath Blight Disease Resistant Germplasm Lines of Rice with Good Agronomic Traits.” Journal of Plant Registrations 5 (3): 400-402. doi: 10.3198 /jpr2010.10. 0601crg. Saravanakumar, D., Ciavorella, A., Spadaro, D., Garibaldi, A., Gullino, M. L., 2008. Metschnikowia pulcherrima strain MACH1 outcompetes Botrytis cinerea, Alternaria alternata and Penicillium expansum in Apples through Iron Depletion. Postharvest Biology and Technology. 49, 121-128. Saravanakumar, D., Lavanya, N., Muthumeena, K., Raguchander, T., Samiyappan, R., 2009. Fluorescent pseudomonad Mixtures Mediate Disease Resistance in Rice Plants against Sheath Rot (Sarocladium oryzae) disease. Biocontrol, 54, 273. Saravanakumar, D., Vijayakumar, C., Kumar, N., Samiyappan, R., 2007. PGPR- Induced Defense Responses in the Tea Plant against Blister Blight Disease. Crop Protection. 26, 556-565. Sharifi, Peyman, Hashem Aminpanah, Rahman Erfani, Ali Mohaddesi, Abouzar Abbasian. 2017. “Evaluation of Genotype × Environment Interaction in Rice Based on AMMI Model in Iran.” Rice Science 24 (3): 173-180. Accessed December, 2017. http://dx.doi.org/10.1016/j.rsci.2017.02.001. Sharma, T. R., A. K. Rai, S. K. Gupta, J. Vijayan, B. N. Devanna, and S. Ray, 2012: Rice Blast Management through Host-Plant Resistance: Retrospect and Prospects. Agric. Res. 1, 37-52. doi:10.1007/s40003-011-0003-5. Shastry, S. V., D. V. Tran, V. N. Naguyen, and J. S. Nanda. 2000. “Sustainable Integrated Rice Production.” In Rice Breeding and Genetics: Research Priorities and Challenges, edited by J. S. Nanda, 53-72. New Delhi: Oxford and IBH Pub. Shrestha, B. K., Karki, H. S., Groth, D. E., Jungkhun, N., Ham, J. H., 2016. Biological control activities of rice-associated Bacillus sp. strains against sheath blight and bacterial panicle blight of rice. PloS one. 11, e0146764. Silva, James, Brian ScheZer, Yamid Sanabria, Christian De Guzman, Dominique Galam, Andrew Farmer, Jimmy Woodward, Gregory May, and James Oard. 2012. “Identification of Candidate Genes in Rice for Resistance to Sheath Blight Disease by Whole Genome Sequencing.” Theoretical and. Applied Genetics 124:63-74. doi:10.1007/s00122-011- 1687-4. Singh, B. N., M. P., Jones, S. N. Fomba, Y. Sere, A. A. Sy, K. Akator, P. Naninbeyie, and S. W. Ahn, 2000: Breeding for Blast Resistance in West Africa. In Advance in rice blast research: Proceeding of 2nd International Rice Blast Conference. 2000, edited by D. Tharreau, M. H. Lebrun, N. J. Talbot, and J. L. Notteghem, 112-128. Netherlands: Klwer Academic Press. Srinivasachary, Laetitia Willocquet, and Serge Savary. 2011. “Resistance to Rice Sheath Blight (Rhizoctonia solani Kühn) [(teleomorph: Thanatephorus cucumeris (A.B. Frank) Donk.] Disease: Current Status and Perspectives.” Euphytica 178 (1): 1-22. Accessed November 10, 2017. https://doi.org/10.1007/s10681-010-0296-7. Tan, W., Mew, T. W., 2001. Bacterial Antagonists against Rhizoctonia solani AG1 in Irrigated Rice Ecosystems. In Exploiting Biodiversity for Sustainable Pest Management, edited by T. W. Mew, E. Borromeo, and B. Hardy, 113-131. International Rice Research Institute, Manila, Philippines.

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

Tang, Qiyyna, Shaobing Peng, Ralond J, Buresh, Yingbin Zou, Nancy P. Castilla, and Twng W. Mew. 2007. “Rice Varietal Difference in Sheath Blight Development and Its Association with Yield Loss at Different Levels of N Fertilization.” Field Crop Research 102:219-227. Thapak, S. K., Thrimurty, V. S., Dantre, R.K., 2003. Sheath Rot Management in Rice with Fungicides and Biopesticides. International Rice Research Notes, 28, 41. Thomas, A., Saravanakumar, D., 2015. Antagonistic Activity of Rhizobacteria against Bacterial Wilt of Tomato Plants in the Caribbean.” In 8th International IPM Symposium, IPM: Solutions for a Changing World,” at Salt Lake City, USA from March 23-26, 2015. Ugochukwu, G. C., F. U. Eneh, I. O. Igwilo, and C. H. Aloh. 2017. “Comparative Study on the Heavy Metal Content of Domestic Rice (Oryza sativa L.) Brands Common in Awka, Nigeria.” IOSR Journal of Environmental Science, Toxicology and Food Technology 11 (8): 67-70. doi: 10.9790/2402-1108026770. Vasudevan, K., C. M. Vera Cruz, W. Gruissem, and N. K. Bhullar, 2014: Large Scale Germplasm Screening for Identification of Novel Rice Blast Resistance Sources. Front. Plant Sci. 505, 1- 9. doi: 10.3389/fpls.2014.00505. Venkateswarlu, N., Vijaya T., Suresh B. D., Chandra mouli, K., Pragathi, D., Anitha, D. Sreeramulu, A., 2013. In vitro Inhibitory Effects of Medicinal Plants Extracts on Sclerotium oryzae- A Fungi causing Stem Rot Disease in Paddy. Int. J. Pharm. Bio. Sci. 3, 147-151. Vincent, S. M., 1947. Distortion of Fungal Hypha in Presence of Certain Inhibitors. Nature. 159, 850-854. Webster, R. K., Gunnell, P. S., 1992. Compendium of Rice Diseases. American Phytopathological Society, St. Paul, MN. Yadav, Shailesh, Ghanta Anuradha, Ravi Ranjan Kumar, Lakshminaryana Reddy Vemireddy, Ravuru Sudhakar, Krishnaveni Donempudi, Durgarani Venkata, et al. 2015. “Identification of QTLs and Possible Candidate Genes Conferring Sheath Blight Resistance in Rice (Oryza sativa L.).” SpringerPlus 4 (175): 1-12. doi:10.1186/40064-015-0954-2. Yadav, V. K., Thrimurty, V. S., 2006. Fungitoxicity of Medicinal Plant Extracts against Sarocladium oryzae causing Sheath Rot in Rice. Indian Journal of Plant Protection. 34, 263-264. Zambonelli, A., D'Aulerio, A. Z., Severi, A., Benvenuti, S., Maggi, L., & Bianchi A. (2004). Chemical Composition and Fungicidal Activity of Commercial Essential Oils of Thymus vulgaris L. Journal of Essential Oil Research, 16, 69-74. Zobel, R. W., M. J. Wright, and H. G. Gauch, Jr., 1988: Statistical Analysis of Yield Trial. Agronomy Journal 80, 388-393.

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021 Appendix

Table 1. Details of entries and reaction of genotypes screened to identify source of rice blast resistance

c Genotypes / Parentage Blast disease score PC1 PC2 Designation Sp., 2015 Aut., 2015 Aut., 2016 *Sp. 2017 Canj. BBP BBP Canj. Onvt. Canj. Onvg. Onvg. 1 FG12-02 FLAR /NA 4 4 4 6 4 3 3 nt. 0.26 -0.31 2 FG12-05 FLAR /NA 3 2 2 2 2 2 2 nt. -0.11 0.18 3 FG12-06 FLAR /NA 3 2 1 2 2 2 2 nt. -0.02 0.33 4 FG12-08 FLAR /NA 1 1 1 1 1 1 1 1 -0.20 -0.03 5 FG12-14 FLAR/NA 1 1 2 2 2 2 0 nt. -0.14 -0.36 6 FG12-16 FLAR /NA 3 2 2 2 2 2 2 nt. -0.11 0.18 7 FG12-19 FLAR /NA 2 2 2 3 1 2 1 nt. -0.04 -0.14 8 FG12-21 FLAR /NA 2 1 1 3 0 2 0 nt. 0.14 -0.04 9 FG12-27 FLAR /NA 1 1 0 2 2 1 0 nt. 0.13 -0.06 10 FG12-32 FLAR /NA 1 1 0 1 1 1 0 1 -0.09 0.10 11 FG12-33 FLAR /NA 3 2 2 2 1 2 0 nt. -0.12 0.14 12 FG12-41 FLAR /NA 3 2 2 3 0 2 0 nt. 0.02 0.06 13 FG12-56 FLAR /NA 3 2 3 4 3 2 0 nt. 0.23 -0.33 14 FG12-61 FLAR /NA 4 4 2 4 3 2 3 nt. 0.13 0.26 15 FG12-78 FLAR /NA 2 1 2 3 0 2 2 nt. 0.03 -0.13 16 FG12-82 FLAR /NA 1 1 1 1 1 1 0 1 -0.18 -0.06

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

Table 1. (Continued) S.N. Genotypes / Parentage Blast disease score PC1 PC2 Designation Sp., 2015 Aut., 2015 Aut., 2016 *Sp. 2017 Canj. BBP BBP Canj. Canj. BBP BBP Canj. 17 FG12-98 FLAR /NA 2 1 3 2 1 2 1 nt. -0.19 -0.24 18 FG12-101 FLAR /NA 3 2 2 2 2 2 1 nt. -0.10 0.14 19 FG12-114 FLAR /NA 1 1 1 1 1 1 0 1 -0.18 -0.06 20 FG12-148 FLAR /NA 2 2 3 2 2 2 2 nt. -0.29 -0.18 21 FG12-201 FLAR /NA 4 2 2 2 2 2 2 nt. -0.02 0.38 22 FG12-248 FLAR /NA 3 1 1 5 3 2 3 nt. 0.67 -0.09 23 FG12-270 FLAR /NA 3 1 1 3 1 3 3 nt. 0.14 0.24 24 FG12-273 FLAR /NA 1 1 1 1 1 1 1 1 -0.20 -0.03 25 FG12-277 FLAR /NA 2 1 0 0 1 1 0 nt. -0.19 0.42 26 FG12-279 FLAR /NA 1 1 0 1 1 1 0 0 -0.09 0.10 27 FG12-281 FLAR /NA 3 2 3 3 3 2 3 nt. 0.01 -0.10 28 GR1401-13-47-4-1-3- FG05-254/G98-196 3 2 3 6 3 4 3 nt. 0.38 -0.43 1-1-1-1-1 29 GR1412-24-32-1-1-1- FG06/25/G98-22-4 2 1 2 2 1 2 2 nt. -0.12 -0.05 3-1-2-2-1-1 30 GR1412-24-32-1-1-1- FG06/25/G98-22-4 1 1 1 0 2 0 2 nt. -0.26 0.08 3-1-2-2-1-1 31 GR1422-34-4-1-2-2-2- FG06-100/G98-135 2 1 2 2 4 2 1 nt. 0.02 -0.20 1-2-2-1 32 GR1440-52-23-4-1-1- FLO3199-2p-20-1pm/G04- 2 2 2 2 2 2 2 nt. -0.20 -0.03 1-1-2-1-2 19//G04-19/G98-30-3 33 GR1447-5-3-2-1-2-1-2- G98-30-3/FG07-182 2 2 3 2 2 3 2 nt. -0.37 -0.17 1 34 GR1447-5-3-2-2-2-1-1- G98-30-3/FG07-182 4 3 2 5 4 4 3 nt. 0.30 0.07 1 35 GR1493-6-9-1-3-1-2-2- FG07-124/G98-135 2 1 1 2 1 2 2 nt. -0.03 0.11 2 36 GR1493-6-9-1-3-2-1-1- FG07-124/G98-135 3 2 2 2 2 2 1 nt. -0.10 0.14 1 72

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

Table 1. (Continued) S.N. Genotypes / Parentage Blast disease score PC1 PC2 Designation Sp., 2015 Aut., 2015 Aut., 2016 *Sp. 2017 Canj. BBP BBP Canj. Canj. BBP BBP Canj. 37 GR1493-6-9-1-3-2-2-2- FG07-124/G98-135 1 0 1 1 0 1 0 1 -0.10 -0.09 2 38 GR1600-4-41-1-1-2-1 FG05-142/G08-112 2 2 1 0 1 2 0 nt. -0.48 0.34 39 GR1601-5-2-2-1-2-2 G04-8/FG07-35 1 2 1 1 2 2 0 nt. -0.35 -0.02 40 GR1602-6-41-1-1-2-1 FG07-35/G07-13 4 2 2 2 2 2 2 nt. -0.02 0.38 41 GR1617-21-11-1-4-1-2 FG07-90/G08-108 3 2 1 2 3 3 2 nt. -0.06 0.31 42 GR1621-25-19-1-2-1-1 FG07-124/G07-2 7 1 1 7 6 2 4 nt. 1.49 0.41 43 GR1624-28-23-1-2-1-1 FG07-124/G08-112 3 2 3 2 3 2 3 nt. -0.17 0.02 44 GR1629-33-66-2-2-1-1 FG07-125/G08-112 3 2 2 2 3 2 2 nt. -0.07 0.14 45 GR1631-35-16-1-2-1-1 FG07-126/G07-13 1 1 1 0 2 2 1 nt. -0.42 0.07 46 GR1636-40-47-2-1-1-1 FG07-127/G07-13 3 2 2 2 2 3 1 nt. -0.18 0.16 47 GR1637-41-23-1-1-1-2 FG07-127/G08-108 3 2 3 3 2 2 1 nt. -0.01 -0.13 48 GR1638-42-33-2-3-1-1 FG07-127/G08-112 3 2 2 4 3 3 2 nt. 0.21 -0.09 49 GR1639-43-62-2-2-1-1 G04-8/FG07-127 4 3 3 7 4 2 2 nt. 0.75 -0.39 50 GR14-14 NA 6 5 4 8 5 4 6 nt. 0.60 0.00 51 G07-118 NA 2 2 3 3 3 3 2 nt. -0.15 -0.33 52 G07-13-1 NA 1 0 1 1 1 1 1 1 -0.08 -0.09 53 FG10-26 NA 1 1 2 0 2 1 1 nt. -0.43 -0.10 54 FG10-54 NA 1 1 2 3 2 2 1 nt. 0.03 -0.44 55 FG10-103 NA 1 1 1 0 1 3 1 0 -0.55 0.12 56 FL-121 NA 2 2 2 2 2 2 1 nt. -0.18 -0.06 57 FL-127 NA 0 0 0 0 0 0 0 0 -0.20 -0.03 58 IR-94 NA 1 1 1 1 1 1 0 5 -0.18 -0.06 59 G11-08 Diwani/G04-8 2 2 2 2 1 2 1 nt. -0.22 -0.02 60 G11-09 Diwani/G04-8 3 1 2 0 1 2 0 nt. -0.37 0.32

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

Table 1. (Continued) S.N. Genotypes / Parentage Blast disease score PC1 PC2 Designation Sp., 2015 Aut., 2015 Aut., 2016 *Sp. 2017 Canj. BBP BBP Canj. Canj. BBP BBP Canj. 61 G11-28 Diwani/FLO4648-6p-9-1-3pm 3 2 2 3 1 2 1 nt. 0.04 0.06 62 G11-101 Diwani/FLO4648-6p-9-1-3pm 2 1 2 2 2 2 2 nt. -0.08 -0.09 63 G11-102 Diwani/FLO4648-6p-9-1-3pm 3 2 2 3 2 2 3 nt. 0.06 0.09 64 G11-103 Diwani/FLO4648-6p-9-1-3pm 2 1 2 5 2 2 2 nt. 0.47 -0.44 65 FG12-23 NA 3 2 3 3 2 2 2 nt. -0.02 -0.10 66 FG12-29 NA 1 0 2 2 1 2 0 nt. -0.06 -0.38 67 FG12-49 NA 4 1 1 2 3 2 2 nt. 0.23 0.44 68 FG12-259 NA 3 2 2 4 3 2 3 nt. 0.28 -0.06 69 GR 1516-29-16-2-3-1- G98-135/GR1082/G04-8 3 1 2 2 2 2 3 nt. 0.00 0.15 1-1-1 70 GR 1561-24-23-2-2-1- GR1107-10-2-1-2/G98-196 4 4 3 8 4 4 3 nt. 0.63 -0.38 1 71 GR 1562-25-16-2-1-2- GR1107-10-2-1-2/G98-135 8 6 5 8 5 4 5 nt. 0.58 0.27 1 72 GR 1562-25-26-1-1-2- GR1107-10-2-1-2/G98-135 9 ng 4 7 6 4 5 nt. 1.33 0.35 1 73 GR 1562-25-26-1-1-2- GR1107-10-2-1-2/G98-135 9 6 4 7 7 5 5 nt. 0.57 0.69 1 74 GR 1568-31-9-1-1-1-1 GR1107-10-2-1-2/FG07-174 4 4 3 2 2 2 3 nt. -0.36 0.38 75 GR 1568-31-9-1-1-2-1 GR1107-10-2-1-2/FG07-174 4 3 2 2 2 3 2 nt. -0.23 0.46 76 GR 1568-32-3-2-2-1-1 GR1107-10-2-1-2/FG07-174 4 3 2 2 1 3 3 nt. -0.28 0.53 77 GR 1568-32-3-2-2-2-1 GR1107-10-2-1-2/FG07-174 1 1 3 0 3 3 0 nt. -0.64 -0.30 78 GR 1573-36-9-2-2-1-1 Adron 102/G98-135 4 4 4 7 5 4 4 nt. 0.39 -0.42 79 GR 1573-36-9-2-2-2-2 Adron 102/G98-135 8 4 8 6 5 5 4 nt. 0.11 -0.10 80 GR 1575-38-9-1-2-1-1 Adron 102/GRDB 10 3 2 9 4 2 2 3 nt. -0.39 -1.12 81 GR 1580-43-2-1-1-2-1 ADRON/FG07-182 4 ng 4 5 7 3 3 nt. 0.68 -0.55 82 GR 1580-43-23-1-1-1- ADRON/FG07-182 2 2 2 1 1 3 1 nt. -0.49 0.11 2 74

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

Table 1. (Continued) S.N. Genotypes / Parentage Blast disease score PC1 PC2 Designation Sp., 2015 Aut., 2015 Aut., 2016 *Sp. 2017 Canj. BBP BBP Canj. Canj. BBP BBP Canj. 83 GR 1583-46-16-3-1-2- GR1117-12-2-3-4-3-2- 2 1 3 4 1 3 2 nt. 0.07 -0.43 1 1/FG07-88 84 GR 1584-47-8-2-1-2-1 GR1117-12-2-3-4-3-2- 3 5 2 1 4 2 3 nt. -0.58 0.44 1/FG07-90 85 GR 1584-47-8-2-2-1-1 GR1117-12-2-3-4-3-2- 3 2 1 2 2 3 3 nt. -0.12 0.38 1/FG07-90 86 GR 1585-48-9-2-1-1-1 GR1117-12-2-3-4-3-2- 2 3 2 1 1 2 3 nt. -0.55 0.23 1/FG07-124 87 G06-123 (GRDB-14) CT10344-7-8-2P-2- 3 3 2 2 2 2 3 nt. -0.24 0.27 2/CNTBR82074-210-1-2- 3//FL03186-1P-4-2P-4P 88 GP18 (GRDB 13) G98-30-3/Basmatti 385 8 8 8 9 8 7 8 6 0.07 -0.16 89 FG07-35 (GRDB-12) ORYZICA LLANOS4/P 1274- 1 2 2 0 0 2 0 nt. -0.70 0.01 6-8M-1-3M-1 90 FG06-98 (GRDB-11) CT10166-16-1-2P-1-3/LV200- 2 1 2 3 1 2 1 nt. 0.08 -0.20 1-1-1-M//FL03188-7P-5-4P-M 91 FG05-259 (GRDB-10) CT8163-9-4-4/FEDEARROZ 0 1 1 1 1 1 0 0 -0.27 -0.26 50//FL00593-6P-7-1P-M 92 G04-08 (GRDB-9) CT10494-1-4/G98-30-3 0 0 0 0 0 0 0 1 -0.20 -0.03 93 G98-135 Rustic//G 95-63/Rustic 6 5 5 8 5 5 5 7 0.43 -0.18 94 G98-30-3 G95-63/Rustic//Rustic 1 2 1 1 1 2 1 nt. -0.40 0.05 95 G98-24-1 Rustic//G95-63/Rustic 6 4 2 5 4 3 2 nt. 0.45 0.49 96 G98-22-4 Rustic//G95-63/Rustic 3 1 3 2 1 1 2 nt. -0.03 -0.02 97 G98-196 BR 83/Rustic 7 7 7 8 8 7 7 7 0.03 -0.18 98 F7-10 IR 52280-13-2/CT8222-4-4- 4 4 8 9 9 4 5 nt. 0.53 -1.40 8P-M 99 BR-444 IR 43/CT 7839. 3 1 3 2 2 3 2 nt. -0.17 -0.03 100 BR-240 Diwani/CT 8008-3-3-1-P-M ng ng ng ng 2 2 2 nt. -0.31 0.00

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

Table 1. (Continued) S.N. Genotypes / Parentage Blast disease score PC1 PC2 Designation Sp., 2015 Aut., 2015 Aut., 2016 *Sp. 2017 Canj. BBP BBP Canj. Canj. BBP BBP Canj. 101 DIWANI NA- (Introduction from 7 6 7 9 6 7 7 5 0.25 -0.29 Suriname) 102 IR 22 NA 9 1 1 3 2 2 2 nt. 0.81 1.37 103 RUSTIC (Ch.) Precoz de Machiquos/D55- 9 8 8 9 8 8 9 8 0.06 0.09 37///Zenith/Nira//D85- 42/4/Century Panta 231/Slo- 17 1 E1 Environment 1 - Canje (Spring crop, 2015) 1.22 2.35 2 E2 Environment 2 - Black Bush Polder (Spring crop, 2015) -1.66 0.71 3 E3 Environment 3 - Black Bush Polder (Autumn crop, 2015) -1.26 -1.82 4 E4 Environment 4 - Canje (Autumn crop, 2015) 2.52 -1.38 5 E5 Environment 5 - Onverwagt Back (Autumn crop, 2015) 0.56 -0.44 6 E6 Environment 6 - Canje (Autumn crop, 2016) -1.21 0.17 7 E7 Environment 7 - Onverwagt Back (Autumn crop, 2016) -0.16 0.41 Notes: FLAR- Latin American Fund for Irrigated Rice (Selected from 2013 nursery), NA- Not Available at this time, S.N. 1 to 50 = Entries form the Observational Yield Trial (OYT), S.N. 51 to 68 = Entries from the Advance Yield Trial (AYT), S.N. 87 to 103= Popular Cultivars (cv.) and / or varieties, Ch.- Check. Sp. = Spring season; Aut. =Autumn season; BBP= Black Bush Polder; Canj. = Canje, Gangaram; Onvgt. = Onverwagt back; Score 0 = HR (Highly Resistant); Score 1= R (Resistant); Score 2 and 3 = MR (Moderately Resistant); Score 4 and 5= MS (Moderately susceptible); Score 6 and 7 = S (Susceptible); Scores 8 and 9= HS (Highly Susceptible); ng. =No Germination; nt. = not tested; PC = principal-component analysis; E = Environment; * = Confirmation of rice blast resistance reaction status of selected genotypes screened during 2015 and 2016.Only genotypes identified with consistent blast reactions status ranged between Highly Resistant (HR) to Resistant (R) and Highly Susceptible (HS) to Susceptible (S) were selected and tested to confirm the rice blast disease reaction status during spring crop, 2017

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

Table 2. Showing the details of the entries and the reaction of genotypes screened to identify slow blighting lines to sheath blight (R. solani) under field and screen house conditions

**Disease reactions/ scores

Artificial inoculated screen house condition Natural field condition S.N. Genotypes /Designation Aut.,2015 Sp.,2016 Sp.,2015 Aut.,2015 Sp.,2016 1 FG12-02 3 3 3 3 3 2 FG12-05 5 5 3 5 3 3 FG12-06 5 5 3 5 3 4 FG12-08 3 3 5 5 5 5 FG12-14 3 3 3 3 3 6 FG12-16 5 5 3 5 5 7 FG12-19 5 5 5 5 5 8 FG12-21 5 5 3 5 3 9 FG12-27 5 5 5 5 5 10 FG12-32 5 5 3 5 3 11 FG12-33 5 5 3 5 5 12 FG12-41 3 3 3 3 3 13 FG12-56 3 3 0 1 1 14 FG12-61 5 5 3 5 3 15 FG12-78 5 3 3 5 3 16 FG12-82 5 5 5 5 5 17 FG12-98 5 3 3 5 3 18 FG12-101 5 5 3 3 3 19 FG12-114 5 5 5 5 5 20 FG12-148 5 5 3 5 5 21 FG12-201 5 5 3 5 5 22 FG12-248 5 5 3 5 5 77

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

23 FG12-270 3 3 3 3 3 24 FG12-273 5 5 5 5 5 25 FG12-277 5 5 3 5 5 26 FG12-279 3 5 5 5 5 27 FG12-281 5 5 3 3 3 28 GR1401-13-47-4-1-3-1-1-1-1-1 5 5 5 5 5 29 GR1412-24-32-1-1-1-3-1-2-2-1-1 5 5 3 5 5 30 GR1412-24-32-1-1-1-3-1-2-2-1-1 5 5 5 5 5 31 GR1422-34-4-1-2-2-2-1-2-2-1 5 5 3 3 3 32 GR1440-52-23-4-1-1-1-1-2-1-2 3 3 1 1 1 33 GR1447-5-3-2-1-2-1-2-1 3 5 3 5 5 34 GR1447-5-3-2-2-2-1-1-1 9 3 5 3 5 35 GR1493-6-9-1-3-1-2-2-2 5 3 3 5 3 36 GR1493-6-9-1-3-2-1-1-1 5 5 3 3 3 37 GR1493-6-9-1-3-2-2-2-2 5 5 3 3 3 38 GR1600-4-41-1-1-2-1 5 5 5 5 5 39 GR1601-5-2-2-1-2-2 5 3 5 5 3 40 GR1602-6-41-1-1-2-1 3 3 1 1 1 41 GR1617-21-11-1-4-1-2 5 5 3 5 5 42 GR1621-25-19-1-2-1-1 5 5 3 5 3 43 GR1624-28-23-1-2-1-1 5 5 3 5 3 44 GR1629-33-66-2-2-1-1 5 5 5 5 5 45 GR1631-35-16-1-2-1-1 3 3 0 1 1 46 GR1636-40-47-2-1-1-1 5 5 5 3 3 47 GR1637-41-23-1-1-1-2 5 5 5 5 5 48 GR1638-42-33-2-3-1-1 5 5 3 3 3 49 GR1639-43-62-2-2-1-1 5 3 5 5 5 50 Seeraj 5 5 5 5 5 51 G07-118 5 5 3 5 3 78

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

52 G07-13-1 5 3 3 5 3 53 FG10-26 3 3 5 5 5 53 FG10-103 5 3 3 5 3 54 FG10-54 3 5 5 3 3 56 FL-121 5 3 5 5 5 57 FL-127 5 5 3 5 3 58 IR-94 3 3 1 3 3 59 G11-08 3 3 3 1 3 60 G11-09 5 5 3 3 3 61 G11-28 5 5 3 3 3 62 G11-101 5 3 3 5 3 63 G11-102 5 5 3 5 5 64 G11-103 3 3 3 3 3 65 FG12-23 5 5 3 5 3 66 FG12-29 5 5 3 5 5 67 FG12-49 5 3 3 5 3 68 FG12-259 5 3 3 5 3 69 GR 1516-29-16-2-3-1-1-1-1 5 3 5 5 5 70 GR 1561-24-23-2-2-1-1 5 3 5 5 5 71 GR 1562-25-16-2-1-2-1 5 3 5 5 5 72 GR 1562-25-26-1-1-2-1 5 3 5 5 5 73 GR 1562-25-26-1-1-2-1 3 3 5 5 5 74 GR 1568-31-9-1-1-1-1 5 5 3 5 5 75 GR 1568-31-9-1-1-2-1 7 7 7 7 7 76 GR 1568-32-3-2-2-1-1 5 3 5 3 5 77 GR 1568-32-3-2-2-2-1 3 3 3 5 3 78 GR 1573-36-9-2-2-1-1 5 5 5 3 3 79 GR 1573-36-9-2-2-2-2 5 5 3 5 5 80 GR 1575-38-9-1-2-1-1 5 5 5 5 5 79

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

81 GR 1580-43-2-1-1-2-1 5 3 5 5 3 82 GR 1580-43-23-1-1-1-2 3 5 3 3 3 83 GR 1583-46-16-3-1-2-1 3 5 5 5 5 84 GR 1584-47-8-2-1-2-1 3 5 5 5 3 85 GR 1584-47-8-2-2-1-1 5 5 5 5 3 86 GR 1585-48-9-2-1-1-1 5 5 5 5 5 87 G06-123 (GRDB-14) 5 5 3 5 3 88 GP18 (Aromatic or GRDB 13) 5 5 5 5 5 89 FG07-35 (GRDB-12) 3 3 3 3 3 90 FG05-259 (GRDB-10) 3 3 5 5 5 91 G04-08 (GRDB-9) 5 3 5 5 5 92 G98-135 3 3 1 3 1 93 G98-30-3 5 5 5 5 5 94 G98-24-1 5 5 3 5 3 95 G98-22-4 5 5 5 5 3 96 G98-196 5 3 5 5 3 97 F7-10 5 5 3 5 3 98 BR-444 3 3 3 3 3 99 DIWANI 5 5 3 5 3 100 IR 22 5 5 3 5 3 101 RUSTIC (Ch.) 7 7 7 7 7

Notes: FLAR- Latin American Fund for Irrigated Rice (Selected from 2013 nursery), NA- Not Available at this time, Aut.,= Autumn season; Sp.,= Spring Season; Ch.- Check., **= Average percentage disease severity from 3 replications; 0= Immune (Im); 1=Very resistant (VR); 3= Resistant(R); 5= Intermediate between susceptible and resistant (I); 7=Susceptible (S); 9=Very susceptible (VS)

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021 Table 3. Effect of plant extracts against P. oryzae and R. solani under in vitro condition

Plant extracts Plant extracts (% W/V) Mycelial growth (mm) of P. oryzae Mycelial growth (mm) of R. solani 5% 10% 15% 5% 10% 15% Neem (Azadirachta indica) 42.67C 40.33C 37.33D 73.33BC 36.67CD 21.00D Tulsi (Ocimum basalicum) 30.33E 28.67DE 30.67E 65.00C 46.67C 35.00C Lemon grass (Cymbopogan flexousus) 27.67EF 24.67EF 28.67E 23.00E 23.33DE 5.00F Thick leaf thyme (Thymus vulgaris) 26.33F 23.67EF 22.67F 18.33E 14.33E 5.00F Aloe (Aloe vera) 81.33B 77.00B 80.33B 79.00AB 39.67C 35.00C Marigold (Tagetes patula) 11.67H 17.00G 18.33G 17.33E 14.00E 6.667F Black sage (Cordia curassavica) 20.67G 12.33G 12.33H 41.67D 34.67CD 13.33E Bael (Aegle marmelos) 22.00G 18.33FG 17.67G 39.33D 43.33C 31.67C Chives (Allium fistulosum) 21.33G 12.67G 16.67G 90.00A 90.00A 90.00A Clove (Syzygium aromaticum) 35.33D 33.33D 54.33C 21.67E 18.33E 5.00F Madar plant (Calotropis gigantean (C. 12.67H 14.33G 16.67G 90.00A 65.67B 81.67B procera)) Control 90.00A 90.00A 90.00A 90.00A 90.00A 90.00A SEm ± 1.72 3.21 2.08 6.65 7.00 2.23 CD (P = 0.05) 3.55 6.62 4.29 13.73 14.45 4.60 CV (%) 5.99 12.01 7.17 15.08 19.91 7.81 Means values in columns followed by same superscript letter(s) are not differ significantly at 95% confidence interval according to Fisher’s Least Significant Difference (LSD) procedure.

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

Table 4. Effects of Bioagents on P. oryzae and R. solani under in vitro condition

Treatment P. oryzae R. solani Mycelial growth % inhibition of Mycelial growth % inhibition of (mm) mycelial growth (mm) mycelial growth Azotobacter SAG19 36.33B 50.58A 74.67A 17.04B B. cereus OG2L 33.67B 52.65A 51.00B 43.33A B. subtilis OG2A 35.00B 50.14A 75.33A 16.30B Control 76.00A - 90.00A - SE m ± 9.91 17.01 8.36 9.29 LSD (P = 0.05) 22.84 39.23 19.29 21.43 CV (%) 26.81 54.33 14.08 59.38 Means values in columns followed by same superscript letter(s) are not differ significantly at 95% confidence interval according to Fisher’s Least Significant Difference (LSD) procedure.

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

Table 5. Effect of plant extracts, bioagents and new generation fungicides against blast disease under field conditions Treatment Dose Trial I - Spring, 2016 Trial II - Autumn, 2016 1Lesion Length *Disease Severity (%) 1Lesion Length *Disease Severity (%) (mm) (mm) 2Before 3After 2Before 3After 2Before 3After 2Before 3After

Marigold 5% 16.80AB 42.80B 48.89 (51.17)ABC 60.74 (65.29)C 7.67A 21.80AB 53.33 (56.27)A 71.11 (79.24)B Black sage 10% 14.00AB 18.87EF 46.67 (48.55)BC 48.15 (50.24)D 7.67A 19.00B 54.82 (58.02)A 56.29 (60.14)D Bael extract 15% 15.60AB 16.60F 51.11 (53.70)AB 46.67 (48.55)D 7.87A 18.07B 55.55 (58.95)A 57.78 (61.84)D Chives 10% 13.67AB 46.00B 48.15 (50.24)ABC 71.11 (79.84)B 8.40A 21.87AB 53.33 (56.27)A 70.37 (78.21)BC Madar plant 5% 15.93AB 18.87EF 51.85 (54.59)A 48.89 (51.09)D 9.60A 20.87B 52.59 (55.52)A 58.52 (62.74)D B. cereus OG2L 2 g/L 15.73AB 18.73EF 51.85 (54.54)A 48.89 (51.12)D 9.53A 18.13B 53.33 (56.27)A 54.81 (58.27)D B. subtilis OG2A 2 g/L 14.47AB 17.73F 48.15 (50.24)ABC 51.85 (54.53)D 8.93A 18.60B 54.08 (57.15)A 55.56 (58.97)D Azotobacter SAG19 2 g/L 14.00AB 45.67B 50.37 (52.82)ABC 71.85 (80.40)B 8.07A 21.93AB 53.33 (56.27)A 71.85 (80.37)B Antracol 70WP 500 g/ac. 15.07AB 18.53F 52.59 (55.44)A 48.89 (51.09)D 9.00A 19.27B 54.81 (58.08)A 59.26 (63.74)CD Nativo 75 WG 250 g/ac. 14.73AB 19.00EF 50.37 (52.79)ABC 48.15 (50.24)D 7.93A 17.73B 57.04 (60.72)A 60.00 (64.53)CD Silvacur Combi 30 200 13.27B 44.93B 46.67 (48.55)BC 71.853 8.40A 21.53AB 57.04 (60.72)A 73.33 EC ml/ac. (80.57)B (82.44)AB Serenade 1.34 SC 400 17.40A 25.40CD 51.11 (53.68)AB 51.85 (54.52)D 8.00A 17.33B 53.33 (56.27)A 59.26 (63.47)D ml/ac. Cyclops 150 13.07B 27.67C 45.93 (47.72)C 53.33 8.73A 22.47AB 53.33 (56.27)A 71.85 (80.40)B ml/ac. (56.27)CD Fugione 300 16.20AB 22.40DE 51.85 (54.62)A 46.67 (48.56)D 8.00A 20.60B 57.04 (60.70)A 57.04 (60.77)D ml/ac. Control Water 16.00AB 53.60A 52.59 (55.44)A 80.00 (93.64)A 8.40A 26.80A 53.33 (56.42)A 81.48 (95.96)A SEm ± 1.90 1.81 2.85 4.61 1.89 2.61 3.53 7.16 CD (P = 0.05) 3.89 3.71 5.84 9.44 3.87 5.35 7.24 14.67 CV (%) 15.44 7.62 6.68 9.25 27.50 15.67 7.52 12.52 Figure in parenthesis show Arcsine transformation; Above data are mean of three replications; 1Average from five tag plants per each replications; 2Data collected before first treatment applied; 3Data collected 7 days after second treatment applied. Means values in columns followed by same superscript letter(s) are not differ significantly at 95% confidence interval according to Fisher’s Least Significant Difference (LSD) procedure.

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

Table 6. Effects of plant extract, bioagents and new generation fungicides against blast disease (P. oryzae) on growth, yield parameters and yield during spring 2016 (Trial I)

Treatments Dosage 1Plant Tiller/ m2 2Panicle No. of grains/ panicle 1000- grain Kg/ha height (cm) length (cm) weight Filled Unfilled (grams) Marigold 5% 80.87ABC 270.67ABCD 19.82EF 44.83EF 12.13DEFG 30.22BC 4598.20DE Black stage 10% 76.93ABC 256.00CD 22.19CD 60.47AB 10.10FGH 31.50A 4870.50ABCD Bael extract 15% 80.27ABC 301.33ABC 22.11D 64.37A 13.80CD 31.26AB 4913.10ABC Chives 10% 81.80A 264.00BCD 20.21E 43.53EF 18.80A 29.59CD 3756.80G Madar plant 5% 81.07ABC 286.67ABCD 22.55BCD 56.83BC 12.83CDE 31.32AB 4832.70BCD B. cereus OG2L 2 g/L 78.20ABC 268.00ABCD 22.44CD 63.63A 8.40H 31.82A 5139.10A B. subtilis OG2A 2 g/L 82.17A 294.67ABC 23.74A 63.10A 8.97H 31.31AB 4829.20BCD Azotobacter SAG 19 2 g/L 75.67C 241.33D 20.13E 46.43E 16.77AB 29.74CD 4166.10F Antracol 70WP 500 g/ac. 78.50ABC 265.33BCD 23.44A 52.40D 12.23DEF 31.20AB 4868.60ABCD Nativo 75WG 250 g/ac. 78.33ABC 314.67A 23.14AB 54.90CD 12.20DEF 30.65ABC 4964.50AB Silvacur Combi 30 200 78.20ABC 270.67ABCD 22.75BC 44.43EF 14.73BCD 29.61CD 4308.60EF EC ml/ac. Serenade 1.34 SC 400 81.23AB 278.67ABCD 23.17AB 63.13A 10.40EFGH 31.61A 4846.40BCD ml/ac. Cyclops 150 80.80ABC 274.67ABCD 19.65EF 43.90EF 15.13BC 28.87D 4630.20CD ml/ac. Fugione 300 80.50ABC 310.67AB 22.41CD 61.20A 9.50GH 31.31AB 4954.70AB ml/ac. Control 75.77BC 270.67ABCD 19.43F 41.37F 18.90A 29.64CD 4166.90F SEm ± 2.69 23.54 0.31 2.03 1.32 0.61 141.75 CD (P = 0.05) 5.50 48.23 0.62 4.16 2.70 1.26 290.35 CV (%) 4.15 10.38 1.71 4.63 12.42 2.45 3.73 Above data is mean of three replications; 1Average from ten plants per each replications; 2Average from ten panicle per each replications. Means values in columns followed by same superscript letter(s) are not differ significantly at 95% confidence interval according to Fisher’s Least Significant Difference (LSD) procedure.

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

Table 7. Effects of plant extract, bioagents and new generation fungicides against blast disease (P. oryzae) on growth and yield parameters during autumn 2016 (Trial II)

1Plant No. of grains/ panicle 1000- grain 2Panicle Treatments Dosage height Tiller/ m2 weight Kg/ha length (cm) (cm) Filled Unfilled (grams) Marigold 5% 73.47A 305.33A 20.44ABC 44.93GH 12.73CDE 30.54C 4696.80C Black sage 10% 75.20A 305.33A 20.64ABC 60.40BCD 10.23EF 31.22ABC 5029.60AB Bael extract 15% 73.60A 352.00A 19.94ABC 62.00BC 13.07CD 31.15ABC 5059.90AB Chives 10% 75.47A 333.33A 19.58ABC 43.73GH 16.00B 29.71D 4695.30C Madar plant 5% 73.07A 289.33A 20.38ABC 53.73EF 12.87CD 31.23ABC 5141.60A B. cereus OG2L 2 g/L 75.60A 302.67A 20.63ABC 63.90ABC 9.73F 31.72A 5263.00A B. subtilis OG2A 2 g/L 74.47A 364.00A 21.71A 68.43A 10.67DEF 30.90BC 5163.60A Azotobacter SAG 19 2 g/L 72.73A 294.67A 19.42ABC 48.40FG 15.10BC 29.65D 4615.90C Antracol 70WP 500 g/ac. 72.93A 305.33A 21.02ABC 58.33CDE 12.60CDE 31.02ABC 5082.10A Nativo 75WG 250 g/ac. 70.80A 362.67A 21.64A 55.67DE 13.03CD 30.91BC 5231.10A Silvacur Combi 30 200 EC ml/ac. 72.47A 330.67A 19.16BC 46.60GH 16.13B 29.03DE 4595.50C 400 Serenade 1.34 SC ml/ac. 74.27A 330.67A 21.29AB 64.43AB 10.53DEF 31.27AB 4776.70BC 150 Cyclops ml/ac. 72.20A 304.00A 19.36ABC 42.73GH 14.37BC 29.41DE 4485.50CD 300 Fugione ml/ac. 71.13A 314.67A 20.67ABC 62.43BC 11.27DEF 31.11ABC 5009.90AB Control Water 75.07A 293.33A 18.88C 41.13H 19.83A 28.81E 4287.90D SEm ± 3.02 36.54 1.165 2.89 1.25 0.36 143.15 CD (P = 0.05) 6.18 74.86 2.39 5.93 2.55 0.73 293.22 CV (%) 5.03 14.02 7.02 6.51 11.54 1.43 3.60 Above data is mean of three replications; 1Average from ten plants per each replications; 2Average from ten panicle per each replications. Means values in columns followed by same superscript letter(s) are not differ significantly at 95% confidence interval according to Fisher’s Least Significant Difference (LSD) procedure.

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

Table 8. Effects of plant extract, bioagents and new generation fungicides against sheath blight (R. solani) disease of rice under field condition during spring 2016 at Onverwagt back (Trial I) Treatment Rate *Disease Severity (%)

+Initial ++7 DAT 14DAT 21 DAT 28 DAT 35 DAT AUDPC Value

Lemon Grass 15% 12.18 3.39 a(1.84)F 3.83 a(1.95)E 5.60 6.82 8.04 b(8.05)C 173.20D a(1.45)A a(2.36)C a(2.61)C Thick leaf Thyme 15% 2.23 (1.46)A 3.07 3.69 (1.92)E 5.33 (2.31)C 6.28 (2.51)C 7.28 (7.28)C 161.85D (1.75)FG Marigold 15% 2.41 (1.55)A 4.68 6.15 (2.48)D 10.46 13.30(3.64)B 14.87(14.92)B 302.56C (2.16)DE (3.21)B Clove 15% 2.40 (1.52)A 6.71 7.55 (2.74)C 12.98 13.52(3.67)B 16.94(17.03)B 353.01B (2.59)BC (3.60)B B.cereus Strain:OG2L 1 g/L 2.39(1.54)A 6.45(2.54)BC 8.24(2.87)BC 10.04(3.17)B 13.20(3.63)B 16.01(16.08)B 329.88BC B.cereus Strain:OG2L 2 g/L 2.28(1.50)A 3.20(1.78)FG 4.01(2.00)E 5.37(2.31)C 6.28(2.51)C 8.68(8.69)C 170.39D Antracol 70WP 500 g/ac 2.22 (1.48)A 3.85 4.20 (2.05)E 5.97 (2.44)C 6.60 (2.57)C 7.79 (7.79)C 179.34D (1.94)EF Nativo 75WG 250 g/ac 2.34 (1.52)A 2.45 (1.56)G 3.52 (1.87)E 4.33 (2.05)C 5.94 (2.44)C 7.21 (7.22)C 147.19D

Silvacur Combi 30EC 200 ml/ac 2.21(1.49)A 5.59(2.36)CD 8.52(2.92)BC 13.56(3.65)B 13.58(3.68)B 14.92(14.97)B 348.76B

Serenade 1.34 SC 400 ml/ac 2.28(1.49)A 3.09(1.75)FG 3.82(1.95)E 5.53(2.35)C 6.93(2.63)C 7.66(7.67)C 170.36D

CYCLOPS 150 ml/ac 2.65(1.62)A 7.40(2.72)AB 9.28(3.04)B 14.15(3.72)B 11.43(3.37)B 15.71(15.78)B 360.12B

Fugione 300 ml/ac 2.30(1.51)A 3.81(1.95)EF 3.86(1.96)E 5.37(2.32)C 6.86(2.62)C 8.05(8.06)C 175.45D

Control Water 2.46(1.56)A 8.75(2.96)A 11.13(3.33)A 19.18(4.37)A 22.42(4.72)A 31.16(31.69)A 548.09A

SEm ± 0.21 0.13 0.09 0.28 0.17 1.0328 15.935

CD (P = 0.05) 0.43 0.27 0.19 0.57 0.34 2.1316 32.889

CV (%) 16.77 7.55 4.72 11.65 6.49 9.95 7.42 aFigure in parenthesis show Square root transformation; bFigure in parenthesis is Arcsine transformation; * Average of three replications; 1Average from five tag plants per each replications ;+ = First treatment applied; ++= Second treatment applied. Means values in columns followed by same superscript letter(s) are not differ significantly at 95% confidence interval according to Fisher’s Least Significant Difference (LSD) procedure.

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

Table 9. Effects of plant extract, bioagents and new generation fungicides against sheath blight (R. solani) disease of rice under field condition during spring 2016 at Burma back (Trial II) Treatment Rate *Disease Severity (%) +Initial ++7 DAT 14DAT 21 DAT 28 DAT 35 DAT AUDPC Value

Lemon grass 15% 13.05 a(1.74)A 3.23a(1.79)DE 3.59a(1.89)C 4.34a(2.08)E 4.76a(2.18)CD 4.85a(2.20)C 139.04D

Thick leaf thyme 15% 3.02 (1.73)A 3.03 (1.74)DE 3.51 (1.87)C 3.99 (2.00)E 4.70 (2.17)CD 4.71 (2.17)C 133.71D

Marigold 15% 3.39 (1.84)A 5.81 (2.41)C 8.43 (2.90)B 8.60 (2.93)D 10.00 (3.16)B 11.20 (3.34)B 280.92C Clove 15% 3.60 (1.89)A 6.49 (2.54)BC 8.73 (2.95)B 9.18 (3.03)BCD 10.36 (3.22)B 11.70 (3.42)B 296.81BC B.cereus Strain:OG2L 1 g/L 3.36(1.83)A 6.24(2.48)C 8.21(2.86)B 9.51(3.08)BC 9.52(3.08)B 11.03(3.32)B 284.69BC B.cereus Strain:OG2L 2 g/L 3.35(1.83)A 2.783(1.667)E 3.54(1.88)C 4.06(2.01)E 5.14(2.26)C 5.09(2.25)C 138.23D Antracol 70WP 500 g/ac 3.29 (1.81)A 3.54 (1.88)DE 3.69 (1.92)C 4.33 (2.09)E 4.74 (2.18)CD 5.27 (2.29)C 144.10D

Nativo 75WG 250 g/ac 3.04 (1.74)A 3.09 (1.75)DE 3.48 (1.87)C 4.29 (2.07)E 4.43 (2.11)D 4.20 (2.04)C 132.32D

Silvacur Combi 30EC 200 ml/ac 3.08(1.75)A 7.56(2.74)AB 8.76(2.96)B 8.97(2.99)CD 9.94(3.15)B 11.08(3.32)B 296.21BC

Serenade 1.34 SC 400 ml/ac 3.19 (1.76)A 3.74 (1.92)D 3.46 (1.86)C 4.36 (2.09)E 4.61 (2.15)CD 4.79 (2.18)C 141.08D

CYCLOPS 150 ml/ac 3.17 (1.77)A 6.74 (2.58)BC 8.65 (2.94)B 10.04 (3.17)B 10.26 (3.20)B 11.18 (3.34)B 300.00B

Fugione 300 ml/ac 3.09 (1.76)A 3.43 (1.85)DE 3.77 (1.94)C 4.57 (2.14)E 4.57 (2.14)CD 4.03 (1.97)C 139.17D

Control Water 3.04 (1.75)A 8.86 (2.98)A 10.71 (3.27)A 13.42 (3.66)A 15.15 (3.89)A 20.43 (4.51)A 419.19A SEm ± 0.13 0.12 0.09 0.07 0.07 0.21 9.10 CD (P = 0.05) 0.26 0.25 0.18 0.15 0.14 0.43 18.78 CV (%) 8.76 6.68 4.55 3.36 3.16 9.01 5.09 aFigure in parenthesis show Square root transformation; * Average of three replications; 1Average from five tag plants per each replications ;+ = First treatment applied; ++= Second treatment applied. Means values in columns followed by same superscript letter(s) are not differ significantly at 95% confidence interval according to Fisher’s Least Significant Difference (LSD) procedure

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021 Table 10. Effects of plant extract, bioagents and new generation fungicides against sheath blight (R. solani) disease of rice on growth, yield parameters and grain weight under field condition during spring 2016 at Onverwagt Back (Trial I)

Treatment Rate *Growth Parameters *Yield parameters *Grain yield 1Plant Tillers 2Panicle Av. No. of grains/ 1000- grain 140lbs./ac kg/ha height /M2 Length panicle weight (grams) (cm) (cm) Filled Unfilled Lemon grass 15% 92.82AB 309.33A 21.83BC 49.47AB 12.13EF 31.158ABC 40.63A 6392.50A Thick leaf thyme 15% 93.177AB 280.00A 21.97BC 49.57AB 12.47EF 30.95BCD 39.87ABC 6272.40ABC Marigold 15% 85.88B 268.00A 20.30D 43.27DEF 16.87BCD 30.42CDEF 37.76DEF 5941.30DEF Clove 15% 90.57AB 274.67A 20.14D 40.93EF 15.23CDE 29.82EF 37.48EF 5896.80EF B. cereus OG2L 1 g/L 89.75AB 285.33A 21.74BC 47.87BC 11.97EF 29.99EF 38.56CDE 6066.50CDE B. cereus OG2L 2 g/L 93.91A 290.67A 22.790A 53.47A 10.23F 31.93A 40.60A 6388.50A Antracol70WP 500 g/ac 90.77AB 284.00A 21.64BC 46.03BCD 15.93BCDE 30.27DEF 38.95BCD 6128.30BCD Nativo75WG 250 g/ac 86.52AB 306.67A 21.38C 44.90CDE 13.17DEF 30.52CDE 40.74A 6409.70A Silvacur Combi 200 ml/ac 91.13AB 293.33A 20.26D 40.23F 18.77BC 29.63F 38.86BCD 6114.90BCD 30EC Serenade1.34SC 400 ml/ac 89.92AB 318.67A 22.31AB 53.70A 10.43F 31.52AB 40.62A 6391.30A CYCLOPS 150 ml/ac 90.31AB 289.33A 20.38D 43.57CDEF 19.70AB 30.30DEF 38.67CDE 6083.90CDE Fugione 300 ml/ac 92.56AB 317.33A 21.84BC 46.50BCD 11.97EF 30.90BCD 40.18AB 6322.30AB Control Water 85.94B 294.67A 18.83E 39.30F 23.43A 28.25G 36.83F 5794.50F SEm ± 3.68 40.84 0.36 2.167 1.99 0.41 0.66 103.31 CD (P = 0.05) 7.60 84.28 0.743 4.47 4.10 0.84 1.36 213.22 CV (%) 4.99 17.06 2.08 5.76 16.46 1.63 2.05 2.05 * = average of three replication; 1= Average from ten plants per each replications; 2=Average from ten panicle per each replications. Means values in columns followed by same superscript letter(s) are not differ significantly at 95% confidence interval according to Fisher’s Least Significant Difference (LSD) procedure.

Persaud, Persaud, Hassan, Homenauth & Saravanakumar Farm & Business 13(1) June 2021

Table 11. Effects of plant extract, bioagents and new generation fungicides against sheath blight (R. solani) disease of rice on growth, yield parameters and grain weight under field condition during spring 2016 at Burma Back (Trial II) Treatment Rate *Growth *Yield parameters 1000- grain *Grain yield Parameters weight 1Plant height Tillers 2Panicle Av. No. of grains/ (grams) 140lbs./ kg/ha (cm) /M2 Length (cm) panicle ac Filled Unfilled Lemon grass 15% 75.57BC 312.00A 22.18ABCDE 54.07AB 12.27EF 31.24AB 38.77ABC 6099.50AB C Thick leaf thyme 15% 76.40BC 285.33A 22.52ABCD 51.40ABC 11.63F 30.94ABC 40.13ABC 6314.00AB C Marigold 15% 80.24ABC 268.00A 20.78F 47.60BCD 16.00BCDE 29.08CD 37.45ABC 5893.20AB C Clove 15% 75.22BC 269.33A 21.567CDEF 42.77DEF 19.37AB 28.81DE 34.20BC 5381.80BC B. cereus OG2L 1 g/L 80.40ABC 286.67A 21.90CDEF 47.53BCD 12.87DEF 31.50AB 34.61BC 5444.80BC B. cereus OG2L 2 g/L 85.70A 301.33A 23.32A 54.70A 11.53F 32.36A 41.71AB 6563.10AB Antracol 70WP 500 g/ac 82.42AB 288.00A 21.53DEF 46.23CDE 19.50AB 30.30BCD 37.29ABC 5866.90AB C Nativo 75WG 250 g/ac 79.22ABC 294.67A 22.09BCDE 48.70ABCD 13.40DEF 30.25BCD 40.05ABC 6301.40AB C Silvacur Combi 200 78.60ABC 278.67A 21.21EF 40.27EF 18.30ABC 28.71DE 35.03BC 5511.10BC 30EC ml/ac Serenade 1.34 SC 400 80.85ABC 317.33A 22.80ABC 55.47A 14.37CDEF 31.23AB 44.15A 6946.80A ml/ac CYCLOPS 150 78.64ABC 284.00A 19.27G 40.70EF 16.73ABCD 28.76DE 36.13BC 5685.40BC ml/ac Fugione 300 82.37ABC 314.67A 23.23AB 47.63BCD 13.03DEF 31.142AB 39.82ABC 6264.70AB ml/ac C Control Water 73.55C 294.67A 19.43G 38.37F 20.23A 27.14E 32.46C 5106.70C SEm ± 4.28 35.12 0.60 3.29 1.93 0.91 3.72 585.12 CD (P = 0.05) 8.83 72.49 1.24 6.78 3.99 1.87 7.68 1207.60 CV (%) 6.62 14.74 3.38 8.50 15.46 3.68 12.04 12.04 * = average of three replication; 1= Average from ten plants per each replications; 2=Average from ten panicle per each replications. Means values in columns followed by same superscript letter(s) are not differ significantly at 95% confidence interval according to Fisher’s Least Significant Difference (LSD) procedure.