to assess the effect of row spacing, varieties and date of sowing on growth and yield of pigeonpea. Significantly higher growth parameters viz., plant height (165.4 cm), leaf area index (2.10), leaf area duration (60.34 days) and crop growth rate (2.39 g m -2 day -1 ) and yield parameters (grain: 940 kg ha -1 and stalk: 4089 kg ha -1 ) were recorded in narrow row spacing (60 cm) compared to wider row spacing (90 and 120 cm). The TTB-7 recorded significantly higher growth viz., plant height (163.6 cm), no. of branches per plant (10.4), total dry matter accumulation per plant (65.33 g), leaf area per plant (3429 cm -2 ), leaf area index (1.81), leaf area duration (50.97 days) and crop growth rate (2.33 g m -2 day -1 ) and yield (grain: 914 kg ha -1 and stalk: 3427 kg ha -1 ) compared to BRG-2 variety. Significantly recoded higher growth viz., plant height (185.2 cm), no. of branches per plant (10.7), total dry matter accumulation per plant (71.26 g), leaf area per plant (4030 cm -2 ), leaf area index (2.12), leaf area duration (57.23 days) and crop growth rate (2.66 g m -2 day -1 ) and yield (grain: 1149 kg ha -1 and stalk: 3721 kg ha -1 ) parameters in May had sown pigeonpea than June and July. Significantly higher grain yield (1284 kg ha -1 ) and stalk yield (4980 kg ha -1 ) was observed in narrow row spacing (60 cm) with TTB-7 variety at May month sown crop (S 1 V 1 D 1 ) which was on par with S

Crop weather calendars (CWC) serve as tools for taking crop management decisions. However, CWCs are not dynamic, as they were prepared by assuming normal sowing dates and fixed occurrence as well as duration of phenological stages of rainfed crops. Sowing dates fluctuate due to variability in monsoon onset and phenology varies according to crop duration and stresses encountered. Realizing the disadvantages of CWC for issuing accurate agromet advisories, a protocol of dynamic crop weather calendar (DCWC) was developed by All India Coordinated Research Project on Agrometeorology (AICRPAM). The DCWC intends to automatize agromet advisories using prevailing and forecasted weather. Different modules of DCWC, namely, Sowing & irrigation schedules, crop contingency plans, phenophase-wise crop advisory, and advisory for harvest were prepared using long-term data of ten crops at nine centers of AICRPAM in eight states in India. Modules for predicting sowing dates and phenology were validated for principal crops and varieties at selected locations. The predicted sowing dates of 10 crops pooled over nine centers showed close relationships with observed values (r 2 of .93). Predicted phenology showed better agreement with observed in all crops except cotton (Gossypium L.; at Parbhani) and pigeon pea [Cajanus cajan (L.) Millsp.] (at Bangalore). Predicted crop phenology using forecasted and realized weather by DCWC are close to each other, but number of irrigations differed, and it failed for accurate prediction in groundnut at Anantapur in drought year (2014). The DCWCs require further validation for making it operational to issue agromet advisories in all 732 districts of India.

The study was conducted to analyse the rainfall pattern of dry farming zones of Southern Karnataka to arrive at proper date of sowing by considering parameters like threshold rainfall (20 mm), threshold dry day (2.5 mm) and threshold dry spell period (10 days) as a main defining parameters for decision making in sowing of major crops (finger millet, pigeonpea, groundnut, etc.). In all the three zones, the agro-climatic onset of cropping season was earlier as compared to meteorological onset (June 1st week) due to bimodal distribution of rainfall having its peaks in May and September month. In Central Dry Zone, Southern Dry Zone and Eastern Dry Zone, fourteenth June, thirteenth June and twentythird May were the agro-climatic onset dates (average of all stations in each zone), respectively. Station wise analysis of the rainfall revealed different agro-climatic onset dates. Ninth May in central dry zone, eighth May in eastern dry zone and fifth May in southern dry zone were the earliest onset dates. These variations in between zonal and station specific onset dates were due to spatio-temporal variations in rainfall. Therefore, advancements in sowing of crops based on the agro-climatic onset should be taken into account for betterment of crop production.

In field trials of six years (2009-14) the influence of weather parameters on groundnut (The varieties: TMV-2, JL-24, K-134 and C-2) under varied sowing environments (July as normal sowing and August as late sowing months) was studied at Bengaluru, Karnataka in alfisols. Rainy days (RD), bright sun shine hours (BSS), total pan evaporation (EVP. in mm), growing degree days (GDD) and rainfall, the cumulative of all measured during crop period were found to influence significantly the growth and yield of ground nut in alfisols across the genotypes. Whereas, potential evapo-transpiration (PET) and length of growing period (LGP) during the cropping period did not show such significant influence. For achieving maximum yield, the optimum value of annual rainfall from the fitted quadratic curves, was found to be 650 mm. BSS, pan evaporation and GDD during the cropping period showed negative correlation with pod yield. Among the 11 multiple linear regression models established, model III was found to be the most reliable in judging the yield potential of groundnut in alfisols of southern Karnataka (Pod yield in kg/ha = -3058.24**+ 6.55 (RD) -2.01 ** (SSH) + 3.98* (GDD) -6.25 (evaporation in mm) + 8.01** (PET) -21.98** (LGP) + 3.38 ** (LAD) with R2 value of 0.86**. Model IV and XI were effective in predicting the yield (R2 =0.86**& 0.60**, respectively), however of the second order.

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