(Arachis Hypogaea L.) Varieties Under Kharif Season and Find out Interaction Effect Between Sowing Windows and Varieties in Kharif Season

GSJ: Volume 9, Issue 1, January 2021 ISSN 2320-9186 659

GSJ: Volume 9, Issue 1, January 2021, Online: ISSN 2320-9186 www.globalscientificjournal.com

Extracting suitable suitable sowing window for groundnut (arachis hypogaea l.) Varieties under kharif season and find out interaction effect between sowing windows and varieties in kharif season. Mahesh Swamia*, Dr. J. D.Jadhavb, Dr. V. A. Sthoolc, Dr.S.V. Bagaded, Dr.V.T. Jadhave, Dr. D.K. Kathmalef

Department Of Agriculture Meteorology

College Of Agriculture, Pune, Mahatma Phule Krishi Vidyapith, Rahuri, Maharashtra, India

Correspondence: [email protected]

Abstract:

The treatments comprised of four varieties viz., V1: JL-776 (Phule Bharati), V2: RHRG- 6083 (Phule Unnati), V3: JL-501 and V4: KDG-160 (Phule Chaitanya) as main plot and four sowing windows viz., S1: 23rd MW (04th to 10th June), S2: 25th MW (18th June to 24th June), S3: 27th MW (02nd to 08th July) and S4: 29th MW (16th to 22nd July) as sub plot treatments. Among all the sowing windows 25th MW (S2) sowing window recorded the highest growth attributes. The leaf spot and rust of groundnut was observed throughout the kharif season 2019, normally 30 days after sowing and then up to the harvesting. The disease intensity was higher mostly in the month of October. Among all sowing windows studied, the average leaf spot and rust intensity level were higher in 25th MW (S2) sowing followed by 29th MW (S4). Sowing of groundnut during 23rd MW (S1) and 25th (S2) recorded lower incidence of thrips, whereas, crop sown during 29thMW (S4) recorded with maximum incidence. Among the varieties, higher incidence was recorded with KDG-160 and minimum was recorded on JL-776 followed by RHRG-6083 and JL-501.Higher GDD and HUE were observed in 25th MW sowing window in variety JL-776 (1809) and (0.74) respectively, as well as the highest HTU and HTUE observed in 25th MW sowing window in variety JL-776 (6911) and (2.64) respectively, while the highest PTU (22640) and PTUE (12.50) were observed under 25th MW sowing window (S2) in variety JL-776. The light use efficiency is also observed maximum during 25th MW sowing window in variety JL-776 (12.56). Key words: Groundnut, Sowing window, interaction, crop, Kharif. .

Introduction:

Groundnut, also known as peanut, is an annual crop and belongs to Fabaceae family. The genus, Arachis contains about 80 species including Arachis monticola. Differing from other flowering plant genera, this genus produces fruits below the ground but flowers, leaves and stems from above ground (Krapovickas and Gregory 1994). Groundnut is grown in areas receiving 600 to 1500mm of rainfall. Sowing, flowering and reproductive phases require an average rainfall distribution of 100, 150 and 400-500mm, respectively. Moisture stress during vegetative period delays flowering, pod setting and results in low yields. High atmospheric humidity stimulates more flowering which results in increased peg setting. Pod development stage is most sensitive to moisture deficit. Phenological development of groundnut responds primarily to heat unit accumulation. Leong and Ong (1983) calculated heat unit requirements for different phenological stages as, leaf production 56 degree day per leaf, branching 103 degree day per branch, time to first flowering 538 degree day, time to first pegging 670 degree day and time to first podding 720 degree day. Pod yield is significantly influenced by day length. Long days promote vegetative growth at the expense of reproductive growth and increased crop growth rate resulting in decreased partitioning of photosynthesis to pods and decreased duration of effective pod filling phase (Nigam et al., 1998).

The choice of a groundnut variety for any particular area depends on matching the variety with the length of the growing season. Groundnut varieties whose growth cycle is longer than the duration of growing season at a particular location either fail to mature or mature at a time when soil is too hard to dig the pods. With these considerations in view the investigation entitled “Extracting suitable suitable sowing window for groundnut (arachis hypogaea l.) Varieties under kharif season and find out interaction effect between sowing windows and varieties in kharif season.” was planned in kharif season of 2019 with following objectives: 1. to find out suitable sowing window for kharif groundnut. 2. To study the interaction effect between sowing windows and varieties in kharif season.

MATERIAL AND METHODS Details of experimental material 3.1.1 Location of the experimental site The field experiment was conducted at Department of Agricultural Meteorology farm, College of Agriculture, Pune during kharif, 2019.The geographical location of the site (Pune) was 18° 32' N, latitude; 73°51' E, longitude and 557.7 m above mean sea level (MSL). The soil is medium black having depth of about 1m. 3.1.2 Soil The topography of the experimental field was uniform and leveled. The composite sample was analyzed for physical and chemical properties of soil and presented in Table 3.1 along with analytical methods used.

Sr. Particulars Results Method adopted Reference No. A. Physical composition

1. Coarse sand (%) 12.39 International pipette Piper (1966) method 2. Fine sand (%) 36.37 International pipette Piper (1966) method 3. Silt (%) 24.54 International pipette Piper (1966) method 4. Clay (%) 26.70 International pipette Piper (1966) method 5. Textural class Sandy clay loam 6. Bulk density (g cc-1) 1.36 Core sampler Richards (1968) B Chemical composition 1 Organic carbon (%) 0.50 Walkley and Black Rapid Allison (1975) titration method 2 Available N (kg ha-1) 156.58 Alkaline KMNO4 Method Subbaiah and Asija (1956) 3 Available P2O5 19.17 0.5 N NaHCO3 Ascorbic Olson and Dean (kg ha-1) acid (1965) -1 4 Available K2O (kg ha ) 315.35 Normal NH4 OAC flame Knudsen et photometer al.,(1982) 5 Soil pH 8.4 Potentiometric Jackson (1973) (1:2.5soil water suspension) 6 Electrical conductivity 0.22 Conductometric Jackson (1973) (dSm-1) C Soil Moisture Content 1 Field capacity (%) 31.44 Pressure plate apparatus Richards (1968) 2 Permanent wilting point (%) 17.12 Pressure plate apparatus Richards (1968

Cropping history of experimental field: The cropping history of experimental field for previous two years is presented in Table 3.3 Table 3.3: Cropping history of experimental field Year Kharif Rabi Summer 2016 Maize Chickpea Fallow 2017 Cotton - Fallow

2018 Pegion pea - Fallow 2019 Present investigation Sorghum Fallow

Seed material: The certified seed of all the groundnut varieties viz., JL-776 (Phule Bharati), RHRG- 6083 (Phule Unnati), JL-501 and KDG-160 (Phule Chaitanya) was procured from the Groundnut Breeder, Agricultural Research Station, and Jalgaon. MPKV, Rahuri as well as from Agricultural Research Station, Kasabe Digraj. Urea and single super phosphate were used as source of N and P and applied as per recommended dose i.e. 25 kg N and 50 kg P. Application of calcium sulphate (gypsum) was carried out as per recommended dose i.e. 250 kg powdered gypsum ha-1. Seed of groundnut was inoculated with Rhizobium culture @ 250 g 10 kg-1 seed. Methods Experimental details: The field trial was conducted with design and randomization. The experiment was conducted in a split-plot design with three replications and sixteen treatment combinations formed considering different varieties and sowing windows. The gross and net plot size was 4.0 x 3.0 m2 and 3.6 x 2.4 m2, respectively. The allocation of treatments was done with random method. Cultural operations Preparatory tillage: During the season, field was ploughed 30 cm deep and subsequently one cross harrowing was done to obtain fine tilts. The debris was collected to clean up the plot. Plan of layout: The factorial field experiment was laid out in split plot design replicated three times. In between two adjacent plots, 1.5 m distance was left in order to avoid drift problem and to move easily around the treatments for recording the observations. Seeds and sowing: The certified seed of all the groundnut variety JL-776, RHRG-6083, JL-501 and KDG-160 was procured from the Groundnut Breeder, Agricultural Research Station, Jalgaon, MPKV, Rahuri and Agricultural Research Station, Kasabe Digraj. Sowing was done as per the treatments by dibbling one kernel at each hill with 30 cm inter-row and 10 cm intra-row distance keeping a seed rate of 100 kg ha-1. . Harvesting and drying: The crop was considered mature when more than 75 per cent of pods from randomly selected plants showed black streaks on inner wall of shell. Out of 8 rows, 6 rows were harvested as net plot leaving one row to avoid sampling error due to border effect. Within the row also, on either 0.5 m was left for border effect. The border rows of the plot were first harvested followed by the plants in the net plot. After uprooting the plants, pods were hand stripped and pod and haulm were sun dried until they attained constant weight. Biometric observations Sampling technique: The various biometric observations were recorded on five randomly selected groundnut plants from each net plot. Bamboo pegs were fixed near these plants for their easy location. The growth observations were recorded at the end of physiological growth stage. The physiological growth stages were determined as suggested by Varaprasad et al. (2010) Initial and final plant count (ha-1): The plant population was calculated by taking actual plant count from each net plot immediately after thinning. Final plant count was recorded before harvest of crop. The number of plants per ha was computed from the number of plants per net plot.

Growth studies Plant height (cm): The plant height was measured from the base of main stem to the base of apical bud of the plant--/ at the end of various physiological growth stages. / Number of branches plant-1: The number of branches plant-1 was counted from each observation plant from branching stage to physiological maturity. Dry matter accumulation plant-1 (g): For determining dry matter accumulation plant-1, one randomly selected plant from each plot was uprooted. It was washed and all the plant parts separated. Post harvest studies Number and weight of pods plant-1: Number of pods of five observational plants was counted and number of pods plant-1 was calculated. The weight of all the pods were taken on electronic balance and mean weight of pods per plant was computed. 100 kernel weight (g): Random sample of 100 kernels was taken from total kernels produced in each net plot, and its weight was recorded. Shelling percentage: 200 g pods from each treatment were shelled and kernel weight was recorded. Shelling percentage obtained by using following formula.

Weight of kernels Shelling % = ------x100 Weight of pods Agro-meteorological Growing Degree Days (GDD): Temperature is a major environmental factor that determines rate of plant development. The temperature required and range of optimum temperature varies with sowing dates and available soil moisture. Thermal response of sowing dates can be quantified by using the heat unit or thermal time concept. Thermal time or growing degree days is calculated according to the equation,

( ) GDD=∑n Tmax+Tmin − T Base 푖=1 2

Where, ∑= Period in days from sowing date till the last date of harvesting

GDD = Growing degree days

0 Tmax. = Daily maximum temperature of day i ( C)

0 Tmin. = Daily minimum temperature of day i ( C) Tb = Base temperature In present study, the base temperature of groundnut was taken as 100C.

Heat Use Efficiency (HUE) Heat use efficiency (HUE) for seed and total dry matter are calculated by the formula: Seed yield / Total dry matter (kg/ha) Heat use efficiency (kg/ha/0C day) = ––––––––––––––––––––––––––––– Accumulated heat units (0C day) Helio Thermal Units (HTU) Heliothermal units for various growth stages are calculated by the formula given by Ritchie and Nesmith, (1991). HTU = GDD x Bright sunshine hours

Heliothermal Use Efficiency (HTUE) Heliothermal use efficiency (HTUE) for seed and total dry matter are calculated by the formula: Seed yield / Total dry matter (kg/ha) Heliothermal use efficiency (kg/ha/0C day) = ––––––––––––––––––––––––––––– Accumulated heat units (0C day)

Photothermal unit (PTU) Photothermal units (PTU), the product of GDD and corresponding day length for that day were computed on daily basis as follows: PTU = GDD × Day Length

Photothermal Use Efficiency (PTUE) Photothermal use efficiency (PTUE) for seed and total dry matter are calculated by the formula: Seed yield / Total dry matter (kg/ha) Photothermal use efficiency (kg/ha/0C day) = ––––––––––––––––––––––––––––– Accumulated heat units (0C day)

Canopy Temperature Infrared thermometer was used for recording canopy temperature. The thermometer was held obliquely so as to view the crop in order to obtain a canopy temperature minimally influenced by the underlying soil. Such measurements were recorded at critical stages of crop. The canopy

temperature was recorded twice daily i.e. at morning hours (07:30 hrs) i.e. Tmin and at afternoon

hours (14:30 hrs) i.e.Tmax.

Light Use Efficiency The PAR is measured by an instrument Line Quantum Sensor. For measuring transmitted radiation (Monteith and Unsworth, 1990), the sensor was in the crop, while for measuring incident radiation. Line Quantum Sensor was kept on open area. Both incident and transmitted radiations were measured at the same windows to reduce the windows variation. Light use efficiency was determined using following equation

Amount of green / dry matter Produced (g m-2) Light use efficiency (kg/ha/0C day) = ––––––––––––––––––––––––– –––––––––––––– Amount of cumulative light absorbed (MJ m-2)

Measurements of the components of PAR

Measurement of incident radiations (PAR): For measurement of incident radiations, Line Quantum Sensor was positioned facing up 1ft. above the top of the canopy and value was recorded for incidence radiation.

Measurement of reflected radiations: For measurement of reflected radiations, Line Quantum Sensor was inverted 1 ft. above the crop canopy and value was recorded for reflected radiation.

Observation on pests:Number of thrips: Count the number of nymphs and adults present in top three open leaves of one plant in the selected spot.

Leaf spot and rust: The five plants in each genotype were randomly selected for recording disease intensity. The disease intensity was in 1-9 scale given by Subrahmanyam et al., (1982)

Evaluation of leaf spot and rust severity: The severity of leaf spot and rust was recorded on three compound leaves of the main stem chosen from bottom, middle and top position of five plants of each genotype with the interval of 7 days, using the scale 1-9 (Subramanyam et al., 1995). The first observation was recorded on appearance of disease. Per cent disease intensity (PDI) of leaf and rust was worked out using following formula: (McKinney 1923)

Sum of total rating PDI = x100 Total plants observed x maximum grade

GSJ: Volume 9, Issue 1, January 2021 ISSN 2320-9186 667 Statistical analysis and interpretation of data Data obtained on various variables were analyzed by „Analysis of Variance‟ method (Anse and Sukhatme, 1967). Standard error of mean (S.Em. +) was worked out for each factor. Whenever, results were significant, the critical differences (C.D.) at5 per cent of significance were worked out. The data are appropriately presented in tables and suitably depicted by graphical illustrations. RESULTS AND DISCUSSION Initial and Final Plant Count: Data regarding initial and final plant count of groundnut as influenced by various treatments presented in Table 4.1. The mean initial plant count of groundnut was 327549 ha-1and final plant count of groundnut was 323532 ha-1 were recorded. Effect of Sowing Windows: The initial and final plant count ha-1 of groundnut did not differ significantly due to sowing windows. This indicated that the yield differences in the present investigation were not influenced due to the differences in plant stand but due to effect of different treatments (Table 4.1). None of the interaction effects between groundnut varieties and sowing windows was found significant in respect of initial and final plant stand. Table 4.1: Initial and final plant count at harvest as influenced by different treatments

Plant population (per ha) Treatments Initial Per cent At harvest Per cent Sowing window (S) 23th MW 327656 98.30 323919 97.18 25th MW 328376 98.51 324305 97.29 27th MW 327876 98.36 323850 97.16 29th MW 326290 98.14 322055 97.07 S.E. m ± 591 - 669 - C.D. at 5% NS - NS - Interaction (S X V) S.Em ± 1182 - 1339 - C.D. at 5% NS - NS - General mean 327549 98.33 323532 97.17

Plant Height (cm): The data pertaining to mean plant height (cm) as influenced periodically by different treatments are graphically depicted in Fig. 4.1 GSJ© 2021 the mean plant height increased as the crop advanced in age. www.globalscientificjournal.comThe mean plant height increased from 14 DAS (1.76 cm) to harvest (30.26 cm).

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25 14 DAS 20 28 DAS

15 42 DAS

10 56 DAS 5 70 DAS

0 Varieties Sowing windows At Harvest Effect of sowing windows: 84 DAS The mean plant height was significantly influenced throughout the crop growth period by different sowing windows.The maximum plant height Fig. 4.1 Plant height (cm) of groundnut as influenced periodically by (32.30cm) was recorded in 25th MW (S2) sowing window and it was at par with 27th MW sowing window (30.97cm) i.e. (S3) this was followed by different treatments 23rd MW (S1) sowing window (29.67 cm) and 29th MW (S4) sowing window (28.10cm). It can be concluded that plant height in the second sowing window (S2) was significantly superior as compared to rest of the sowing windows during the crop growth period. It might be due to suitable weather conditions of different weather parameters during crop growing period. Reduced plant height with delay in sowing may be due to quick changes in photoperiod, which accelerated development towards reproductive stage and hence less time was available for vegetative growth. These results are similar to those reported by Gosh and Das Gupta (1975). Effect of interaction: The plant height (cm) at all the stages of crop growth was significantly influenced by interaction between varieties and sowing windows. 25th MW sowing window (S2) recorded higher plant height (36.58 cm) in variety JL-776 (V1) which was followed by variety RHRG-6083 (V2) (33.68), JL-501 (V3) (30.01 cm) and KDG-160 (V4) (28.94). Number of branches plant-1 The data in respect to number of branches plant-1 of groundnut as affected by different treatments are graphically depicted in Fig. 4.2. The mean number of branches plant-1 was progressively increased with advancement of the age of the crop, 10.30 at harvest.

4 28 DAS

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Effect of sowing windows: The maximum number of branches plant-1 of groundnut (11.37cm) was recorded in 25th MW (S2) sowing window and it was at par with 27th MW sowing window (10.64cm) i.e. (S3) which was followed by 23rd MW sowing window (10.04cm) and 29th MW sowing window (9.15cm). Effect of interaction: 25th MW sowing window (S2) recorded higher number of branches plant-1 of groundnut (13.01 cm) in var. JL-776 (V1) which was followed by var. RHRG-6083 (V2) (11.67 cm), JL-501 (V3) (10.62 cm) and KDG-160 (V4) (10.18 cm). Total dry matter accumulation plant-1 (g): The accumulation of dry matter plant-1 (g) is probably the best index of growth put forth by the crop. Relevant data to this character recorded at various stages are graphically depicted in Fig. 4.3. During the crop growing period, increase in dry matter weight was continuous with the advancement in the crop age up to harvest of crop. The rate of increase was rapid during flowering and reproductive period. The mean dry matter of groundnut plant-1 at harvest was 29.05g Effect of sowing windows: The maximum dry matter accumulation plant-1 (32.81g) was recorded in 25th MW (S2) sowing window and it was at par with 27th MW sowing window (S3) (29.73g), this was followed by 23rd MW sowing window(S1) (27.64g) and 29th MW sowing window (S4) (26.00g). The dry matter accumulation plant-1 of groundnut was increased very fast in between 14 to 56 DAS which might be due to active vegetative growth phase of the plant and at slow rate beyond 56 DAS as the plant enter from initial vegetative phase to reproductive phase. The dry matter accumulation plant-1 of groundnut in the sowing window (S2) was significantly superior as compared to rest of the sowing windows during the crop growth period. It might be due to suitable weather conditions of different weather parameters during crop growing period. Reduced dry matter accumulation plant-1 of groundnut with delay in sowing may be due to quick changes in photoperiod, which accelerated development towards reproductive stage and hence less time was available for vegetative growth. From all the observations it is observed that the sowing window 25th MW i.e. treatment S2 was significantly superior over all the other sowing window treatments. This decreased growth period might have reduced dry matter production with late sowing. The similar results were recorded by Gopalkrishnan et al. (1967) at the time of sowing of groundnut in kharif season. They indicated July 7 as the optimum date of sowing and observed the highest net assimilation ratio and photosynthesis ratio at this sowing date. Also, similar results were reported by Firmpong (2004). Effect of interaction:

GSJ: Volume 9, Issue 1, January 2021 ISSN 2320-9186 670 The dry matter accumulation plant-1 of groundnut at all the stages of crop growth was significantly influenced by interaction between varieties and sowing windows 25th MW sowing window (S2) recorded higher dry matter accumulation plant-1 of groundnut (41.06g) in variety JL-776 (V1) which was followed by variety RHRG-6083 (V2) (31.06g), JL-501 (V3) (30.06 g) and KDG-160 (V4) (29.06 g) Days to 50 per cent Flowering and Maturity: Data regarding mean days to 50 per cent flowering and maturity of groundnut as influenced significantly by the different treatments are graphically depicted in figure 4.4. The mean days to 50 per cent flowering were 33.34. The mean days to maturity were 108.66.

10 8 14 DAS

6 28 DAS

4 42 DAS

2 56 DAS

0 Effect of sowing windows: 70 DAS The days to 50 per cent flowering (35.37) was observed significantly higher in 25th MW sowing window. This was followed by 27th MW sowing Varieties Sowing windows 84 DAS window at (33.97), 23rd MW sowing window (32.98) and 29th MW sowing window (31.02). The similar results were observed by Gopalkrishnan et al. (1967) at theFig time 4.3 of Dry sowing matter groundnut plant-1 (g) in as Kharif influenced season periodically and indicated by that the sowing groundnut in the second fortnight of June and first fortnight of July gave highest flower production.different Later sowingstreatments reduced flower production.

12 0

GSJ: Volume 9, Issue 1, January 2021 ISSN 2320-9186 671 The days to maturity was significantly influenced by interaction between varieties and sowing windows but days to 50 per cent flowering has non-significant interaction between varieties and sowing windows. Sowing at 25th MW sowing window (S2) recorded maximum days to 50 per cent flowering (39.12) in variety JL-776 (V1). This was followed by variety RHRG-6083 (V2) (36.79), JL-501 (V3) (33.79), and KDG-160 (V4) (31.76). Yield Contributing Characters: The mean yield contributing characters of groundnut varieties viz., number of pods plant-1,weight of pods plant-1, 100 kernel weight (g) and shelling (%)as influenced by the different treatments were recorded at harvest and reported here. Number of pods plant-1: Data on mean number of pods plant-1 of groundnut as influenced significantly by the different treatment and data graphically depicted in fig 4.5. The mean number of pods plant-1 was 36.14. 80

70 No of pods per plant 60 Weight of pods per plant 50 100 kernel weight (g) 40 Shelling (%) 30 20

10 0 Varieties Sowing windows

Effect of sowing windows: The number ofFig. pods 4.5 plantYield- 1Contributing was maximum Characteristics at 25th MW sowing window (42.18) which was at par with 27th MW sowing window (38.59). This was followed by 23rd MW sowing window (33.18). The least number of pods plant-1 of groundnut was observed in 29th MW sowing window (30.59). Effects of interaction: The number of pods plant-1 of groundnut was significantly influenced by interaction between varieties and sowing windows. Sowing at 25th MW sowing window (S2) recorded maximum number of pods plant-1 of groundnut (56.43) in variety JL-776 (V1). This was followed by variety RHRG-6083 (V2) (46.43), JL-501 (V3) (34.76), and KDG-160 (V4) (31.09). Weight of pods plant-1 (g) Data on mean weight of pods plant-1 of groundnut as influenced significantly by the different treatments were recorded and graphically depicted in Fig 4.5.The mean weight of pods plant-1 was 12.60. Effect of sowing windows: GSJ© 2021 www.globalscientificjournal.com

GSJ: Volume 9, Issue 1, January 2021 ISSN 2320-9186 672 Present findings were in agreement with Shantimalliah et al. (1979) who showed that pod yield of groundnut from early sowings was higher, and that groundnut could be sown upto the first fortnight of July without much reduction in yield. Similar results were reported by Lewin et al. (1979). They concluded that the crop sown on second fortnight of June gave the highest yield followed by the crop sown on July 7. Effects of interaction: The weight of pods plant-1 of groundnut was significantly influenced by interaction between varieties and sowing windows. Sowing at 25th MW sowing window (S2) recorded maximum weight of pods plant-1 (15.84) in variety JL-776 (V1). This was followed by variety RHRG-6083 (V2) (14.20), JL-501 (V3) (12.79), and KDG-160 (V4) (11.25). 100 kernel weight (g) Data on mean 100 kernel weight (g) of groundnut as influenced significantly by the different treatments graphically depicted in Fig 4.5. The mean 100 kernel weight (g) was 33.45. Effect of sowing windows: The 100 kernel weight (g) of groundnut was recorded highest at 25th MW sowing window (37.51) which was at par with 27th MW sowing window (34.51). This was followed by 23rd MW sowing window (32.26). The least 100 kernel weight (g) of groundnut was observed in 29th MW sowing window (29.51). Similar results were reported by Mane et al. (2008). Effects of interaction: The 100 kernel weight (g) of groundnut was non-significantly influenced by interaction between varieties and sowing windows. Sowing at 25th MW sowing window (S2) recorded maximum 100 kernel weight (g) of groundnut (41.09) in variety JL-501 (V3). This was followed by variety RHRG-6083 (V2) (38.61), JL-776 (V1) (36.43), and KDG-160 (V4) (33.91). Shelling (%): . Effect of sowing windows: The shelling (%) of groundnut was recorded highest at 25th MW sowing window (70.90) which was at par with 27th MW sowing window (69.58). This was followed by 23rd MW sowing window (68.79). The lower shelling (%) of groundnut was observed in 29th MW sowing window (67.08). Effects of interaction: The shelling (%) of groundnut was not significantly influenced by interaction between varieties and sowing windows. Yield Studies: Data in respect of mean pod yield and haulm yield of groundnut as influenced by different treatments are graphically depicted in Fig 4.6.

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Pod Yield: The mean pod yield of groundnut was 25.12 qha-1 was recorded. Effect of sowing windows: The pod yield of groundnut was influenced significantly due to extended sowing windows. The pod yield was maximum at 25th MW sowing window (27.79 qha-1) and was at par with 27th MW (26.78 qha-1). This was followed by 23rd MW sowing window (23.95 qha-1) and 29th MW sowing window (21.96 qha-1). A sowing window of 25th MW was favorable to maximum pod production because of favorable weather condition. Similar results were reported by Firmpong (2004) and Banik (2009). Effects of interaction: 1The pod yield (q ha-1) was significantly influenced by interaction between varieties and sowing windows. Sowing at 25th MW sowing window (S2) recorded maximum pod yield (30.44 qha-1) in variety JL-776 (V1). This was followed by variety RHRG-6083 (V2) (29.64 qha-1), JL-501 (V3) (28.88 qha-1), and KDG-160 (V4) (22.17 qha-1). There results showed that delay in sowing of groundnut varieties could not able to assimilate the more biomass resulted in reduced pod yield of groundnut. Haulm Yield: Data with respect to mean haulm yield of groundnut as influenced by different treatments are and graphically depicted in Fig. 4.6. The mean haulm yield of groundnut was 34.87qha-1. Effect of sowing windows: The haulm yield of groundnut was influenced significantly due to extended sowing windows. The haulm yield was maximum at 25th MW sowing window (39.11 qha-1), this was at par with 27th MW (36.99 qha-1) sowing window. Effects of interaction: The haulm yield (q ha-1) was significantly influenced by interaction between varieties and sowing windows. Sowing at 25th MW sowing window (S2) recorded maximum haulm yield (44.06 qha-1) in variety JL-776 (V1). This was followed by variety RHRG-6083 (V2) (40.62 qha-1), JL- 501 (V3) (36.43 qha-1) and KDG-160 (V4) (35.31 qha-1). These results showed that delay in sowing of groundnut varieties could not able to assimilate the more biomass resulted in reduced haulm yield of groundnut Population dynamics of thrips on groundnut 4.5.1 Population dynamics of thrips/3 leaves on different groundnut varieties under different sowing window 4.5.1.1 Population dynamics of thrips/3 leaves on different groundnut varieties under sowing window (S1) 23rd MW GSJ© 2021 www.globalscientificjournal.com

GSJ: Volume 9, Issue 1, January 2021 ISSN 2320-9186 674 During the first sowing window 23rd MW (S1) with the varieties JL-776 (V1), RHRG-6083 (V2), JL -501 (V3) and KDG-160 (V4) the mean incidence of thrips/3 leaves was 2.62, 2.15, 2.88 and 2.96 thrips/3 leaves and which were at peak with a 4.34, 4.01, 5.54 and 5.82 thrips/3 leaves respectively. Resulting the peak population of thrips/3 leaves was noticed at 36th MW with sowing window 23rd MW. Population dynamics of thrips/3 leaves on different groundnut varieties under sowing window (S2) 25th MW During the second sowing window 25th MW (S2) of season with the varieties JL-776 (V1), RHRG-6083 (V2), JL-501 (V3) and KDG-160 (V4) recorded the mean incidence of thrips/3 leaves was 2.26, 1.93, 2.69 and 2.97, which were at peak with 3.37, 3.04, 4.11 and 4.39 thrips/3 leaves respectively, resulting the peak incidence of thrips/3 leaves was noticed at the 37th MW for the sowing window 25th MW. 4.5.1.3 Population dynamics of thrips/3 leaves on different groundnut varieties under sowing window (S3) 27th MW During the third sowing window 27th MW (S3) of the season with the varieties JL-776 (V1), RHRG-6083 (V2), JL-501 (V3) and KDG-160 (V4) the mean incidence of thrips/3 leaves were 2.67, 2.22, 2.74 and 3.02 and which was peak with 3.74, 3.41, 3.64 and 3.92 thrips/3 leaves, respectively.. The peak incidence of thrips/3 leaves were noticed at the 37th MW for the sowing window 27th MW. 4.5.1.4 Population dynamics of thrips/3 leaves on different groundnut varieties under sowing window (S4) 29th MW During the fourth sowing window 29th MW (S4) of the season with the varieties JL-776 (V1), RHRG-6083 (V2), JL-501 (V3) and KDG-160 (V4) the mean incidence of thrips/3leaves was 3.61, 3.38, 3.47 and 3.75 which were at peak with a 4.90, 4.57, 6.07 and 6.35 thrips/3 leaves respectively. The peak incidence of thrips/3 leaves were noticed during the 37th MW for the sowing window 29th MW. Similar results were reported by Reddy et al. (1983), Jayanthi et al. (1993), Vijayalaxmi (2010) and Ahir et al. (2012).

Correlation between weather parameter and leaf spot on different groundnut varieties at different sowing windows. The data on correlation between weather parameters and leaf spot disease intensity on different groundnut varieties at different sowing windows are given in Table 4.17. Table 4.17: Correlation between per cent disease intensity of leaf spot of groundnut with weather parameters during kharif 2019

Treatment r’ values

Sowing window Variety Tmax Tmin R H I R H II W S RAIN R D Epan B S S rd S1- 23 MW V1- JL-776 0.468* -0.409 0.384 -0.397 -0.629** -0.056 -0.279 0.122 0.257 th S2- 25 MW V1- JL-776 0.445 -0.667** 0.538* -0.412 -0.701** 0.043 -0.340 0.042 0.294 th S3- 27 MW V1- JL-776 0.366 -0.697** 0.524* -0.366 -0.738** 0.031 -0.210 -0.211 0.170

th S4- 29 MW V1- JL-776 0.437 -0.783** 0.680** -0.549* -0.743** 0.042 -0.112 -0.014 0.348 rd S1- 23 MW V2 - RHRG-6083 0.468* -0.414 0.370 -0.396 -0.624** -0.061 -0.287 0.130 0.264 th S2- 25 MW V2 - RHRG-6083 0.445 -0.660** 0.551** -0.414 -0.716** -0.047 -0.338 0.033 0.280 S - 27th MW V2 - RHRG-6083 0.363 -0.698** 0.520* -0.364 -0.745** 0.025 -0.220 -0.218 0.166 3 GSJ© 2021 www.globalscientificjournal.com

GSJ: Volume 9, Issue 1, January 2021 ISSN 2320-9186 675 th S4- 29 MW V2 - RHRG-6083 0.439 -0.777** 0.668** -0.556** -0.727** 0.065 -0.118 0.001 0.353 rd S1- 23 MW V3- JL-501 0.374 -0.373 0.342 -0.306 -0.572** -0.136 -0.323 0.080 0.200 th S2- 25 MW V3- JL-501 0.397 -0.622** 0.513* -0.344 -0.699** -0.080 -0.375 0.036 0.238 th S3- 27 MW V3- JL-501 0.404 -0.754** 0.519* -0.389 -0.775** -0.043 -0.305 -0.152 0.230 th S4- 29 MW V3- JL-501 0.441 -0.810** 0.684** -0.542* -0.786** -0.005 -0.158 -0.041 0.335 rd S1- 23 MW V4-KDG-160 0.304 -0.360 0.303 -0.241 -0.507* -0.164 -0.346 0.062 0.168 th S2- 25 MW V4-KDG-160 0.406 -0.642** 0.400 -0.334 -0.671** -0.187 -0.496* 0.119 0.317 th S3- 27 MW V4-KDG-160 0.373 -0.756** 0.492* -0.359 -0.761** -0.080 -0.329 -0.158 0.219 th S4- 29 MW V4-KDG-160 0.504* -0.809** 0.675** -0.598** -0.786** 0.063 -0.131 0.010 0.392

Tmax -Maximum temperature Tmin -Minimum temperature RH-I- Morning humidity RH-II- Evening humidity WS- Wind speed RF- Rainfall Epan- Evaporation BSS- Bright sunshine hours * Significant at 0.05% ** significant at 0.01%

Correlation between weather parameter and rust on different groundnut varieties at different sowing windows The data on correlation between weather parameters and rust disease intensity on different groundnut varieties at different sowing windows are given in Table 4.18. Table 4.18 :Correlation between per cent disease intensity of rust of groundnut with weather parameters during kharif 2019

Treatment r’ values

Sowing window Variety Tmax Tmin R H I R H II W S RAIN R D Epan B S S

rd S1- 23 MW V1- JL-776 0.456* -0.389 0.354 -0.375 -0.596** -0.086 -0.297 0.136 0.257

th S2- 25 MW V1- JL-776 0.454* -0.675** 0.525* -0.403 -0.727** -0.066 -0.387 0.064 0.307

th S3- 27 MW V1- JL-776 0.388 -0.714** 0.529* -0.383 -0.741** 0.005 -0.219 -0.183 0.198

th S4- 29 MW V1- JL-776 0.460* -0.782** 0.673** -0.568** -0.741** 0.062 -0.101 -0.007 0.369

rd S1- 23 MW V2 - RHRG-6083 0.436 -0.408 0.379 -0.367 -0.598** -0.105 -0.297 0.107 0.245

th S2- 25 MW V2 - RHRG-6083 0.469* -0.680** 0.507* -0.417 -0.736** -0.087 -0.419 0.087 0.326

GSJ: Volume 9, Issue 1, January 2021 ISSN 2320-9186 676 th S4- 29 MW V2 - RHRG-6083 0.459* -0.782** 0.672** -0.562** -0.746** 0.064 -0.101 -0.025 0.356

rd S1- 23 MW V3- JL-501 0.422 -0.399 0.356 -0.343 -0.578** -0.081 -0.311 0.109 0.251

th S2- 25 MW V3- JL-501 0.467* -0.680** 0.492* -0.410 -0.721** -0.082 -0.422 0.100 0.337

th S3- 27 MW V3- JL-501 0.251 -0.640** 0.420 -0.275 -0.587** -0.035 -0.163 -0.248 0.128

th S4- 29 MW V3- JL-501 0.458* -0.759** 0.645** -0.553** -0.713** 0.017 -0.082 -0.006 0.360

rd S1- 23 MW V4-KDG-160 0.423 -0.399 0.343 -0.345 -0.568** -0.110 -0.319 0.115 0.258

th S2- 25 MW V4-KDG-160 0.491* -0.677** 0.532* -0.436 -0.740** -0.005 -0.366 0.089 0.332

th S3- 27 MW V4-KDG-160 0.254 -0.644** 0.419 -0.274 -0.588** -0.035 -0.162 -0.244 0.132

th S4- 29 MW V4-KDG-160 0.458* -0.760** 0.639** -0.549* -0.713** 0.010 -0.086 -0.009 0.358

RH-I- Morning T -Maximum temperature T -Minimum temperature RH-II- Evening max min humidity humidity

GSJ: Volume 9, Issue 1, January 2021 ISSN 2320-9186 WS- Wind speed RF- Rainfall Epan- Evaporation BSS- Bright sunshine hours 677 * Significant at 0.05% ** significant at 0.01%

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4.6.4.1 Correlation between weather parameter and rust on groundnut variety JL-776 at different sowing windows During first sowing window 23rd MW (S1) with variety JL-776 the per cent disease intensity for one week prior (W-1) was correlated significantly positive with maximum temperature (0.456), morning relative humidity (0.354), evaporation (0.136) and bright sunshine hours (0.257) whereas it was negatively significant with minimum temperature (-0.389), evening relative humidity (-0.375), wind speed (-0.596) and rainfall (-0.086). During second sowing window 25th MW (S2) with variety JL-776 the per cent disease intensity for one week prior (W-1) was correlated significantly positive with maximum temperature (0.454), morning relative humidity (0.525), evaporation (0.064) and bright sunshine hours (0.307) whereas it was negatively significant with minimum temperature (-0.675), evening relative humidity (-0.403), wind speed (-0.727) and rainfall (-0.066). 4.6.4.2 Correlation between weather parameter and rust on groundnut variety RHRG-6083 at different sowing windows During first sowing window 23rd MW (S1) with variety RHRG-6083 the per cent disease intensity for one week prior (W-1) was correlated significantly positive with maximum temperature (0.436), morning relative humidity (0.379), evaporation (0.107) and bright sunshine hours (0.245) whereas it was negatively significant with minimum temperature (-0.408), evening relative humidity (-0.367), wind speed (-0.598) and rainfall (-0.105) During second sowing window 25th MW (S2) with variety RHRG-6083 the per cent disease intensity for one week prior (W-1) was correlated significantly positive with maximum temperature (0.469), morning relative humidity (0.507), evaporation (0.087) and bright sunshine hours (0.326) whereas it was negatively significant with minimum temperature (-0.680), evening relative humidity (-0.417), wind speed (-0.736) and rainfall (-0.087). 4.6.4.3 Correlation between weather parameter and rust on groundnut variety JL-501 at different sowing windows During first sowing window 23rd MW (S1) with variety JL-501 the per cent disease intensity for one week prior (W-1) was correlated significantly positive with maximum temperature (0.422), morning relative humidity (0.356), evaporation (0.109) and bright sunshine hours (0.251) whereas it was negatively significant with minimum temperature (-0.399), evening relative humidity (-0.343), wind speed (-0.578) and rainfall (-0.081). During second sowing window 25th MW (S2) with variety JL-501 the per cent disease intensity for one week prior (W-1) was correlated significantly positive with maximum temperature (0.467), morning relative humidity (0.492), evaporation (0.100) and bright sunshine hours (0.337) whereas it was negatively significant with minimum temperature (-0.680), evening relative humidity (-0.410), wind speed (-0.721) and rainfall (-0.082). During third sowing window 27th MW (S3) with variety JL-501 the per cent disease intensity for one week prior (W-1) was correlated significantly positive with maximum temperature (0.251), morning relative humidity (0.420)and bright sunshine hours (0.128) whereas it was negatively

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significant with minimum temperature (-0.640), evening relative humidity (-0.275), wind speed (-0.587)and evaporation (-0.248) During fourth sowing window 29th MW (S4) with variety JL-501 the per cent disease intensity for one week prior (W-1) was correlated significantly positive with maximum temperature (0.458), morning relative humidity (0.645) and bright sunshine hours (0.360) whereas it was negatively significant with minimum temperature (-0.759), evening relative humidity (-0.553) and wind speed (-0.713). 4.6.4.4 Correlation between weather parameter and rust on groundnut variety KDG-160 at different sowing windows During first sowing window 23rd MW (S1) with variety KDG-160 the per cent disease intensity for one week prior (W-1) was correlated significantly positive with maximum temperature (0.423), morning relative humidity (0.343), evaporation (0.115) and bright sunshine hours (0.258) whereas it was negatively significant with minimum temperature (-0.399), evening relative humidity (-0.345), wind speed (-0.568) and rainfall (-0.110). During second sowing window 25th MW (S2) with variety KDG-160 the per cent disease intensity for one week prior (W-1) was correlated significantly positive with maximum temperature (0.491), morning relative humidity (0.532), evaporation (0.089) and bright sunshine hours (0.332) whereas it was negatively significant with minimum temperature (-0.677), evening relative humidity (-0.436) and wind speed (-0.740). During third sowing window 27th MW (S3) with variety KDG-160 the per cent disease intensity for one week prior (W-1) was correlated significantly positive with maximum temperature (0.254), morning relative humidity (0.419) and bright sunshine hours (0.132) whereas it was negatively significant with minimum temperature (-0.644), evening relative humidity (-0.274), wind speed (-0.588) and evaporation (-0.244). During fourth sowing window 29th MW (S4) with variety KDG-160 the per cent disease intensity for one week prior (W-1) was correlated significantly positive with maximum temperature (0.458), morning relative humidity (0.639) and bright sunshine hours (0.358) whereas it was negatively significant with minimum temperature (-0.760), evening relative humidity (-0.549) and wind speed (-0.713) Meteorological Studies: 4.7.1 Growing Degree Day (GDD): The linear relationship between growing degree day and pod yield was graphically presented in fig. 4.15. It was evident from the data that accumulated growing degree days (GDD) varied considerably from sowing to physiological maturity of the crop. Different groundnut varieties responded differently in terms of accumulated GDD. Higher GDD was observed under 25th MW sowing window in variety JL-776 (1809) this was higher than (1746) in variety, RHRG-6083and the lowest GDD was observed in var. KDG-160 (1499) sown at 29th MW sowing window (S4) during the season from sowing to physiological maturity.

Pod yield Linear (Pod yield)

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Heat Use Efficiency (HUE)( g/GDD): Different groundnut varieties responded differently in terms of heat use efficiency (g/GDD) at different phenophases. The highest heat use efficiency was observed in 25th MW sowing window (S2) in all the varieties during kharif, 2019. Heat use efficiency (HUE) for different genotypes varied considerably at different growth stages (Table 4.20). Higher heat use efficiency (0.74 g/GDD) at rapid kernel growth to physiological maturity stage was observed under 25th MW sowing window (S4) in variety JL-776 (V1) during the season. The variety KDG-160 (V4) observed lowest heat use efficiency values at 29th MW sowing window (S4) (0.47g/GDD) at rapid kernel growth to physiological maturity stage. Table 4.20: Heat use efficiency as influenced by different sowing windows and varieties in kharif groundnut

Heat use efficiency (g/GDD) Treatment P1 P2 P3 P4 P5 P6 S – 23rd MW 1 0.07 0.19 0.25 0.37 0.45 0.61 S - 25th MW 2 0.08 0.20 0.26 0.42 0.52 0.74 Jl-776 S - 27th MW 3 0.06 0.19 0.24 0.38 0.46 0.63 S - 29th MW 4 0.08 0.19 0.26 0.37 0.46 0.62 rd S1 – 23 MW 0.06 0.15 0.20 0.29 0.35 0.47 S - 25th MW 2 0.06 0.14 0.19 0.31 0.38 0.54 RHRG-6083 S - 27th MW 3 0.05 0.14 0.19 0.29 0.37 0.51 S - 29th MW 4 0.06 0.15 0.21 0.30 0.37 0.49 S – 23rd MW 1 0.06 0.16 0.20 0.30 0.36 0.48

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S - 25th MW 2 0.06 0.14 0.19 0.31 0.37 0.52 JL-501 S - 27th MW 3 0.05 0.15 0.19 0.30 0.37 0.50 S - 29th MW 4 0.06 0.15 0.21 0.29 0.36 0.49 S – 23rd MW 1 0.06 0.16 0.20 0.30 0.36 0.47 S - 25th MW 2 0.06 0.14 0.19 0.30 0.37 0.51 KDG-160 S - 27th MW 3 0.05 0.15 0.19 0.29 0.36 0.49 S - 29th MW 4 0.05 0.15 0.20 0.28 0.35 0.47

P1: Germination to branching P2: Branching to first flower P3: First flower to 50 % flowering P4 : 50 % flowering to peg formation P5: Peg formation to rapid kernel growth,

P6: Rapid kernel growth to physiological maturity

Helio Thermal Unit (HTU): Different groundnut varieties responded differently in terms of accumulated HTU at the time of maturity. The highest HTU was observed in 25th MW sowing window (S2) in all the varieties. The linear relationship between growing heliothermal unit and pod yield was graphically depicted in Fig. 4.17. Heliothermal unit (HTU) for different genotypes varied considerably at maturity period (Table 4.21). Higher HTU (6911) was observed under 25th MW sowing window (S2) in variety JL-776 (V1). The variety KDG-160 accumulated the lowest HTU values was observed under 29th MW sowing window (S2) (5170). With delayed sowing window, accumulated HTU reduced significantly in groundnut. This was due to increase in the temperature during delayed plantings, which accelerated the growth of the crop. The similar results were reported by Singh et al.(1990), Kingra and Kaur (2012) and Meena et al.(2013)

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Heliothermal Use Efficiency (HTUE) (g/HTU): Heliothermal use efficiency (g/HTU) for different genotypes varied considerably at different growth stages (Table 4.22). Higher heliothermal use efficiency (2.64 g/HTU) at Peg formation to rapid kernel growth stage was observed under 25th MW sowing window (S2) in variety JL-776 (V1). The variety JL-501 observed lowest heat use efficiency values under 29th MW sowing window (S4) (1.41 g/HTU) at rapid kernel growth to physiological maturity stage. With delayed sowing window, heliothermal use efficiency decreases significantly in groundnut. This was due to increase in the temperature during delayed sowing which accelerated the growth of the crop. The similar results were reported by Singh et al.(1990), Kingra and Kaur (2012) and Meena et al.(2013) Photothermal unit (PTU): Photothermal unit (PTU) for different genotypes varied considerably at different phenophases of crop (Table 4.23). Higher PTU (22640) was observed under 25th MW sowing window (S2) in variety JL-776 (V1) at physiological maturity. The variety KDG-160 accumulated the lower PTU values was observed under 29th MW sowing window (S4) (18414) at physiological maturity. Photothermal Use Efficiency (g/PTU): Photothermal use efficiency (g/PTU) for different genotypes varied considerably at different growth stages (Table 4.24). Higher photothermal use efficiency (12.50 g/PTU) at physiological maturity was observed under 25th MW sowing window (S2) in variety JL-776 (V1). Variety KDG-160 observed lowest heat use efficiency values was observed under 29th MW sowing window (S4) (6.12 g/PTU) at physiological maturity. With delayed sowing window, photothermal use efficiency decreased significantly in groundnut. This was due to increase in the temperature during delayed plantings which accelerated the growth of the crop. The similar results were reported by Singh et al (1990), Kingra and Kaur (2012) and Meena et al. (2013) Canopy Temperature It was measured by using infrared thermometer. The canopy temperature was recorded at morning and at afternoon hrs and presented in Table 4.25 and fig.4.21. The mean canopy temperature at branching, at flowering and at peg formation stages were 28.48, 30.54 and 33.28 0C, respectively.

25 At branching

20 At flowering At peg formation 1510

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Light Use Efficiency by groundnut plant canopy (g/ MJ): Light use efficiency (LUE) is the relationship between dry matter production and absorbed photosynthetically active radiation (APAR) by the crop. The many indices are available for measuring the growth and yield of crop. However, light use efficiency (LUE) is the reliable index of measuring growth, development and yield of crop. The data regarding light use efficiency (LUE) as influenced periodically by different treatments are presented in Table 4.26 and Fig. 4.22. Maximum light use efficiency was recorded in variety JL-776 (V1) during 25th MW sowing window (S2) i.e. 12.56g MJ-1 because of favorable microclimatic situation for crop and the lowest light use efficiency was observed in variety KDG-160 (V4) during 29th sowing window (S4) i.e. 7.53g MJ-1. SUMMARY AND CONCLUSIONS The experiment was laid out in split plot design with three replications. The treatment comprised of four varieties viz., V1: JL-776 (Phule Bharati), V2: RHRG-6083 (Phule Unnati), V3: JL-501 and V4: KDG-160 (Phule Chaitanya) as main plot and four sowing dates viz., S1: 23rd MW (04th to 10th June), S2: 25th MW (18th to 24th June), S3: 27th MW (2nd to 8th July) and S4: 29th MW (16th to 22nd July) as sub plot treatments. Effects of sowing windows: Among all the sowing windows 25th MW (S2) sowing window recorded the highest growth attributes viz., plant count (324305), plant height (32.30cm), total number of branches plant-1 (11.37g), and total dry matter accumulation plant-1 (32.81g) during the season, 25th MW sowing window was at par with the 27th MW sowing window with all growth attributes. Yield contributing characters viz., number of pod plant-1 (42.18), weight of pods plant-1 (13.52), 100 kernel weight (37.51g) and shelling percentage (70.90) were observed higher in 25th MW (S2). 25th MW sowing window showed value which were at par with the 27th MW values in all the yield attribute. Pod yield (27.79 qha-1) and haulm yield (39.11 qha-1) was higher in 25th MW sowing window during the season which was at par with 27th MW sowing window. Effects of Interaction:

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The combination of JL-776 with 25th MW sowing window (S2) i.e. S2V1 was found to be superior for all the growth attributing characters viz., plant height (36.58 cm), total number of branches plant-1 (13.01), and total dry matter accumulation plant-1 (41.06 g). 5.4 Crop weather relationship: Higher GDD (1809) and Heat use efficiency (0.74) were observed in 25th MW sowing window in variety JL-776. Highest HTU (6911) and Heliothermal use efficiency (2.64) observed in 25th MW sowing window in variety JL-776 during the season.Highest PTU (22640) and Photothermal use efficiency (12.50) also observed in 25th MW sowing window in variety JL- 776. Canopy temperature and Light Use Efficiency (LUE) were found to be significant at all the critical growth stages of crop for different sowing windows. 5.5 Crop weather pest relationship The correlation of meteorological parameters with incidence of the thrips, the cumulative data of correlation showed that the population of thrips was found to have significant and positive correlation with minimum temperature, afternoon relative humidity, wind speed and bright sunshine hours whereas maximum temperature, morning relative humidity, and rainfall showed negative correlation with seasonal incidence of thrips. Conclusions:

1. Sowing during 25th MW was observed to be most suitable and optimum for groundnut considering the growth and yield attributes. This sowing window was at par with 27th MW sowing window. 2. The combination of JL-776 with 25th MW sowing window (S2) i.e. S2V1 was found to be superior for all the growth and yield characters. 3. Sowing of groundnut during 23rd MW (S1) and 25th (S2) recorded lower incidence of thrips, whereas, crop sown during 29th MW (S4) recorded with maximum incidence. Among the varieties, higher incidence was recorded with KDG-160 followed by RHRG-6083, JL-501 and minimum was recorded on JL-776. 4. The leaf spot and rust of groundnut was observed throughout the kharif season 2019, normally 30 days after sowing and then up to the harvesting. The disease intensity was higher mostly in the month of October. Among all sowing windows studied, the average leaf spot and rust intensity level were higher in 25th MW (S2) sowing followed by leaf spot in 29th MW (S4) and rust in 23rd MW (S1).

Future line of work: In the changing weather and climate scenarios, there is a need to know the best cultivars for different weather conditions. The evaluation of varieties for different environments should continue further. Crop weather pest and disease relationships are very useful to predict the incidence of pest population and per cent disease intensity of the diseases of crop sowing under different weather conditions. The crop weather pest and disease relationship should continue for different locations of Maharashtra. LITERATURE CITED

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Ashour, W. E., Mohamed, H. A., Sirry, A. R. and Arafa, M. A.1971. Date of planting wheat in relation to rust reaction. Agril. Res. Review. 49: (3) 19-31. Attarde, D. R., Suryawanshi, R. T. and Wadile, S. C. 2002. Performance of groundnut varieties to different dates of sowing in summer season. J. Maharashtra Agric Univ. 26 (3):329-330. Awurum, A. N. 2000. Effect of planting date on incidence and severity of some fungal diseases of cowpea in the humid tropics of South Eastern Nigeria. J. Sustainable Agril. and Environ., 2(1): 128-133. Banik, N. C., Nath, R. and Chakraborty, P. K. 2009. Effect of dates of sowing on growth and yield of groundnut crop. J. Crop and Weed. 5 (2): 59-62. Basu, S., Dutta, S.K., Fangzuva, D., Jena, S., Maji, R., Nath, R. and Chakraborty, P.K. 2013. PAR interception and dry matter accumulation in groundnut cultivars sown at different time periods in the Gangetic plains of West Bengal. J. Agromet. 15 (Spl. Issue 1):201-204. Bell, M. 1986. Effect of sowing date on growth and development of irrigated peanuts, (Arachis hypogaea L.) cv. Early bunch, in a monsoonal tropical environment. Aus. J. Agric. Res. 37(4) 361 -373 Bell, M. J., Wright, G. C. and Harch, G. R. 1993. Environmental and agronomic effects on the growth of four peanut cultivars in a sub-tropical environment. I. Dry matter accumulation and radiation use efficiency. Exptl. Agric. 29 (4):473-490 Benagi, V. I., Advani, M. R. and Kulkarni, S. 1998. Epidemiological factors in relation to development and prediction of late leaf spot of groundnut. Karnataka J. Agril. Sci. 11(3): 679- 683.. Canavar, O. and Kaynak, M. A. 2010. Growing degree day and sunshine radiation effects on peanut pod yield and growth. African J. Biotech. 9 (15):2234-2241. Cox, F. R. 1979. Effect of temperature treatment on peanut vegetative and fruit growth. Peanut Sci. 6(1): 14-17. Dash, P. C. and Santokke, B. K. 1994. Effect of sowing dates on insect pest incidence and yield of kharif groundnut under western Orissa conditions. Orissa J. Agric. Res. 7 (¾):63-66. Enikuomehin, O. A., Olowe, V. I. O., Alao, O. S. and Atayese, M. O. (2002). Assessment of Cercospora leaf spot disease of sesame in different planting dates in South Western Nigeria. Moor J. Agril. Res.,3(1) : 76-82. Fajola, A. O. 1978. The effect of some environmental factors on reproductive structures of some species of Cercospora. Nova Hedwigia. 29(3-4) : 922-934. FAO, (2010). FAO Production Year book, 60, Rome, Italy. Frimpong, A. 2004. Characterization of groundnut (Aarchis hypogaea L.) in Northen Ghana. Pakistan. J. Bio. Sci. 7: 838-842. Gajjar, R. B., Shekh, A. M. and Patel, N. M. 1994. Response of groundnut genotypes to photosynthetically active radiation. Ann. Arid Zone. 33(3): 223-227. Galgunde, L. P. and Kurundkar, B. P.2002.Occurrence of groundnut diseases as influenced by weather parameters in rabi crop. J. Maharashtra Agric. Univ., 27( 1): 113.

686

Ghadekar, S. R. 1988. Effect of sowing date on heat unit requirement and yield of winter groundnut. Ind. J. Agric. Sci.: 678-681. Ghosh, P. K., Dayal, D., Bandyopadhyay, K. K. and Mohanty, M. 2006. Evaluation of straw and polythene mulch for enhancing productivity of irrigated summer groundnut. Field Crops Res. 99 (2–3): 76–86. Ghuge, S. S. Mayee, C. D. and Godbole, G. M. (1981). Indian J. Phytopath., 34(2) : 179-182. 116 Gill, K. S., Sharma, I. and Aujla, S. S. 1993. Karnal bunt and wheat production. J. of Punjab Agril. Uni, Ludhiana, India, 12: 153. Hammons, R. O. 1977.Groundnut rust in the United States and the Caribbean. PANS (Pest Articles and News Summaries). 23: 300-304. Hazarika, D. K; Dubey, L . N and Das, K. K. 2000. Effect of sowing dates and weather factors on development of leaf spots and rust of groundnut. J. Mycol. and Pl. Path., 30(1): 27-30. Ikeda, T. and Awal, M.A. 2002. Effects of changes in soil temperature on seedling emergence and phenologIcal development in field-grown stands of peanut (Arachis hypogaea L). Environ. and Exptl. Bot .47(2): 101 – 113. Jackson, M.L. 1973. Soil chemical analysis, Prentice Hall, India Pvt. Ltd New Delhi. Jayanthi, M., singh, K. M and Singh, R. N. 1993. Population build up of insect pests on MH4 variety of groundnut influenced by abiotic factors. Indian J. Ent. 55:109-123. Karunakar, A. P., Jiotode, D.J. and Nalamvar, R.V. 2002. Basis of variation in pod yield of kharif groundnut under delayed sowings. Res. on Crops. 3(3): 546-550. Karunakaran, P. and Raj, J. S.1973. The survival of Cercospora personata (Berk. and Curt.) Cercospora hibisci tracy and earle, and Cercospora henningsii Allesch in the soil. Kerala Agril. Res. J. 11:162-163. 117

687

Kataria, G.K. and Pandya, R.B. 1995. Influence of seasons on yield physiology of bunch type groundnut. Plant Physiol and Biochem, New Delhi. 22(2): 143-146. Khan, A. A., Bano, J., Bakht, S. A., Khan, N. J., Malik and Naz, I. 2009. Effect of sowing geometry on pod yield and its attributes in groundnut under sub-mountainous conditions of Northern NWFP (Swat Valley), Pakistan. Sarhad J. Agric. 25(4): 537-543. Kingra, P. K. and Prabhjyot K. 2012. Effect of dates of sowing on thermal utilisation and heat use efficiency of groundnut cultivars in central Punjab. J. Agril. Physics 12(1): 54- 62. Knudsen, D., Peterson, G.A. and Pratt, P.F. 1982. Lithium, Sodium and Potassium. In A.L. Page et al. (Ed.) Methods of soil analysis, part II. 2nd ed. Agronomy Monogr. Madison. pp. 225-246. Kolte, S. J. 1986. Diseases of annual edible oilseeds crops, Peanut Diseases, CRC Press, Boca Raton, Florida. 1: 143. Kucharek, T. A. 1975. Reduction of Cercospora leaf spot of peanuts with crop rotation. Pl. Dis. Rep. 59: 822-823. Lavina, A., Aramburu, J and morines, E. 1996. Occurrence of tomato spotted wilt and cucumber mosaic viruses in field grown tomato crops and associated weeds in northeastern Spain. Plant Path. 45: 837-42. Leong, S. K. and Ong, C. K. 1983.The influence of temperature and soil water deficit on the development and morphology of groundnut (Arachishypogaea L.).J. Exp Bot. 34: 1551-1561. Lewin, H.D., Saroja, R., Sunanda Raju, D. and Padmanabhan, M.D. (1979). Influence of sowing time and weather on the incidence of groundnut leaf miner. Indian J. Agril. Sci. 49(11): 886-891. Lokhande, N. M., Newaskar, V. B. and Lanjewar, R. D. 1998. Epidemiology and forecasting of leaf rust of groundnut. J. Soil Crop., 8: 216–218. Malliah, K. V. 1976. A note on the seasonal changes in the incubation time of groundnut rust. Current Sci. 45: 26. Mane, P. S., Lad, D. B. and Jagtap, P. K. 2008. Correlation and path coefficient analysis in summer bunch groundnut. J. Maharashtra. Agric. Univ. 33 (2):174-176. March, G. J., Marinelli, A., Beviacqua, J. E.and Alcalde, M. 1993. The effect of temperature, relative humidity and rainfall on leaf spot caused by Cercospora arachidicola Hori and Cercosporidium personatum (Berk. & Curt.) (Deighton) in groundnut (Arachis hypogea L.) Boletin de Sanidad Vegetal, Plagas. 19( 2): 227-235. Marshall, B., Squire, G. R. and Terry, A. C. 1992. Effect of temperature on interception and conversion of solar radiation by stands of groundnut. J. Exp. Bot. 43 (1): 95-101. 118

688

Mayee, C. D. 1986. Epidemiology and management of groundnut rust. In:Vistas in Plant Pathology (A. Varma and J.P. Varma, eds). New Delhi Malhotra Publishing House. Meena, R. S., Yadav, R. P. and Meena, V. S. 2013. Heat unit efficiency of groundnut varieties in scattered planting with various fertility levels. The Biscan. 8(4):1189-1192. Mirshekari, M., Hosseini, N. M., Amiri, R. and Randvakili, O.R. 2012. Study the effects of planting date and low irrigation stress on quantitative traits of spring sunflower (Helianthus annuus l.). Romanian Agril. Res. 29, 201-203. Mishra, P. 2000. Diseases of vegetable crops, oxford and IBH publishing, New Delhi pp. 686. Mohamed, H.A. 1984. Varietal differences in the temperature responses of germination and crop establishment. Ph.D. Thesis, U.K. University of Nottingham, U.K. Muhr, G. R., Datta, N. P., Santrasubramoney, H., Leley, U.K., Donahuse, R.D. and Maekower, R.W. 1965. Soil testing in India 2nd edition USAID, New Delhi. Mukhtar, A.A., Babaji, B.A., Ibrahim, S., Mani, H., Mohammad, A. A. and Ibrahim, A. 2013. Dry matter production and harvest index of groundnut (Arachis hypogaea L.) varieties under irrigation. J. Agril. Sci. 5(8):153-162. Munde, P. N. and Mayee, C. D. 1980. Effect of temperature on development of groundnut rust. Indian phytopathology. 33: 444-449. Murthy, P. S. S. and Rao, R. C. N. 1986. Physiological basis of variations in pod yield of rainfed groundnut (Arachis hypogeae L.) under different dates of sowing. Indian J. Agron. 31: 106–108. Naidu, P. H. and Chandrika, V. 1997. Effect of dates of sowing on the occurrence of tikka late leaf spot and rust on groundnut in southern zone of Andhra Pradesh. J. Oilseeds Res. 14(2): 238- 240. Naidu, P. H. and Vasanthi, R. P.1998. Influence of sowing dates on tikka late leaf spot (Phaeoisariopsis personata) in groundnut. Indian J. Pl. Protection., 26( 2): 89-92. Nanda, R. and Saini, A. D. 1989. Solar-radiation interception, green area and dry-matter production in green gram (Vigna radiata). Ind. J. Agril Sci. 59 (5):305-311. Nigam, S. N., Rao, N., Wynne, J. C. Williams, J. H. and Nagbhushanam, G.V. 1994. Effect of interaction of temperature and photoperiod on growth and partitioning in three groundnut genotypes. Ann. Appl. Biology 125:541-552. Nigam, S. N., Rao, R.C.N. and Wynne, J.C. 1998. Effects of temperature and photoperiod on vegetative and reproductive growth of groundnut (Arachis hypogaea L.). J. Agron. and Crop Sci. 181 (2) :117-124. 119 Nigam, S. N. Nageswara Rao, R. C. and Wynne, J. C. 1998. Effects of temperature and photoperiod on vegetative and reproductive growth of groundnut (Arachis hypogaea L.). J. Agro and Crop Sci. 181: 117-124.

Ntare, B. R., Williams, J. H., and Nadunguru, B. J. 1998. Effects of seasonal variation in temperature and cultivar on yield and yield determination of irrigated groundnut (Arachis hypogaea L.) during the dry season in the Sahel of West Africa. J. Agril. Sci. 131(4): 439-448 . Olson, S. R. and Dean, L.A. 1965. Estimation of available phosphorous in soil by extraction with NaHCO3. Cir. U.S. Deptt. Agric. pp.939.

689

Ong, C. K. 1984. The Influence of temperature and water deficits on the partitioning of dry matter in groundnut (Arachis hypogaea L.). J. Exp. Bot. 35 (5): 746-755. Pandu, S. R. and Apparao, A. 1979. The influence of date of sowing and environment on the relative predominance of two species of Cercospora on groundnut. Andhra Agril. J. 26(3-4): 81- 84. Panse, V.G., and Sukhatme, P.V. 1967. Statistical method for agricultural workers. ICAR, Pub. New Delhi Paria, T. K. and Raj, S. K. 1987. Epidemiology of groundnut rust Puccinia arachidis Speg. Current Res. Uni. of Agril. Sci. Bangalore. 16(7): 100-102. Siddaramaiah, A. L., Desai, S. A., Hegde, R. K. and Jayaramaiah, H.1980. Effect of different dates of sowing of groundnut on rust development in Karnataka. Proceedings of the Indian National Sci. Aca., B., 46(3): 389-392. Subrahmanyam, P., Reddy, D. V. R., Gibbons, R. W., Rao, V. R. and Garren, K. H. 1979. Current distribution of groundnut rust in India. PANS (Pest Articles and News Summaries). 25: 25-29. Singh, G., Narwal, S. S., Rao, V.U.M. and Dahiya, D.S. 1990. Effect of sowing date on requirement of growing degree days, heliothermal units and photothermal units, and phenology of winter maize (Zea mays). Ind J. Agric. Sci. 60 (11): 723-731. Smartt, J. (1964). Factors influencing yield and quality of groundnuts in northern Rhodesia. Emp. J. Expo Agric. 32 : 343-351.pa Smith, A. F. 2002. Peanuts: The Illustrious history of the goober pea. Chicago: University of Illinois Press Sokhi and Jhooty, J. S. 1982. Factors associated with resistance to Puccinia arachidis. Peanut Sci., 9: 96-97. Songsri, P., Jogloy, S., Junjittakarn, J. M., Kesmala, T., Vorasoot, N., Holbrook, C. C. and Patanothai, A. 2013. Association of stomatal conductance and root distribution with water use efficiency of peanut under different soil water regimes. Aus. J. Crop Sci.7(7):948-955. Sorensen, R. B. and Wright, F. S. 2002. Soil temperature in the peanut pod zone with subsurface drip irrigation. Peanut Sci. 29 (2): 115-122. Subbiah, B. V. and Asija, G. L. 1956. A rapid procedure for the estimation of available nitrogen in soil. Curr. Sci. 25: 258 –260. Subramanyam, P. and D. Mc. Donald. 1970. Effect of Relative humidity on development of groundnut rust. Information Bulletin No. 13, ICRISAT patencheru, A. P., Indian phytopathology., 1-15 Subramanyam, P. and McDonald, D. 1982. Groundnut rust its survival and carry over in India. Proceedings of Indian Aca. of Sci. (Plant Science) 91: 93-100. Sud, V. K. and Singh B. M .1984. Effect of Environmental factors on the development of leaf spot (Cercospora canescens) in Urd bean. Indian phytopathology. 37(3): 511-515. Talwar, H.S., Takeda, H., Yashima, S. and Senboku, T. 1999. Growth and photosynthetic responses of groundnut genotypes to high temperature. Crop Sci. 39: 460-466. 12

690

Tsigbey, F. K., Brandenburg, R. L. and Clottey, V. A. 2003. Peanut production methods in northern Ghana and some disease perspectives. J. Agron. 34 (2): 36-47. Venkatraman, S. and Kazi, S. K. 1979. A climate disease calendar for tikka of groundnut. J. Maharashtra Agric. Univ. 4: 91-94. Verma, P. R. and Patel, P. N. 1969. Host range, varietal resistance and epidemiological observations on Cercospora leaf spot disease of cowpea. Indian phytopathology. 22: 61-66. Vijaya lakshmi, K. D. Raji Reddy, N. R. G. Verma and Pranuthi, G. 2010. Weather based pest and disease forewarning models in groundnut in the context of climate change. ISPRS Archives XXXVIII. 8/W3 Workshop Proceedings: Impact of climate change on agriculture. Wadia, K. D. R., Butler, D. R. and Jadhav, D. R. 1994 .Effects of leaf wetness and temperature on late leaf spot infection of groundnut. Plant Pathology., 43: 112-120. Waggoner, P. F. 1965. Microclimate and plant disease. Annual Review phytopathology., 3: 103- 126.development of leaf spot disease of cowpea. Indian phytopathology. 37: 340-341.