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The results of this study revealed that the pan evaporation and sensor based irrigation scheduling along with fertigation scheduling significantly affected the plant height, fruit weight, fruit length, crop water requirement, crop yield and water use efficiency of okra crop. The pan evaporation and crop evapotranspiration (ETc) values significantly vary over different stages of okra crop. The maximum and minimum average daily pan evaporation was recorded 8.4 mm day-1 and 4.5 mm day-1 at mid stage and late stage of okra crop respectively while, the maximum average daily ETc was recorded 7 mm day-1 at mid stage of okra crop. A approach of irrigation scheduling with 100 per cent field capacity, based on soil moisture sensor under automated drip irrigation system along with 100 per cent RDF through fertigation in equal splits at 4 day intervalor 80 % per cent of volume of crop water requirement based on pan evaporation under automated drip irrigation along with 100 per cent RDF through fertigation in equal splits at 2 day interval, can be used for irrigating okra crop with significant water saving, crop yield and water use efficiency under limited availability of daily weather datain climatic condition of Udaipur district of Rajasthan.

The study was undertaken to determine the crop water requirement and crop coefficient for capsicum (Capsicum annum L.) at plasticulture farm of CTAE, Udaipur, Rajasthan under four small protected structures; (i) shednet house (ii) insectnet house (iii) poly house with ventilation through shed net and (iv) polyhouse with ventilation through insect net. The reference evapotranspiration under each structure was determined by Penman Monteith method based on microclimatic observations under all four protected structures. Crop evapotranspiration was determined by soil moisture balance method. Reference evapotranspiration and crop coefficient observed minimum under structure covered with shadenet for all the growth stages. Reference evapotranspiration for shadenet house was 21.5 % less than the reference evapotranspiration outside the structure. It was found that shadenet house minimized crop evapotranspiration by 33.4% as compared to outside crop evapotranspiration. However, the higher fruit yield per plant (1720 g plant-1) was recorded under polyhouse with ventilation through insectnet, which was significantly superior over the all growing structures while the lowest yield (1285 g plant-1) was recorded under shadenet house.

Stochastic modelling for mean monthly wind speed of Udaipur (Rajasthan) was done using 26 years (1978–2003) data. The performed statistical tests indicated that the series of the monthly wind speed data is trend free. The periodic component can be represented by third harmonic expression. The stochastic components of the mean monthly wind speed follow fourth order Markov model. The correlation coefficient between generated and measured mean monthly wind speed series was 0.9995 and found to be highly significant 1 per cent level. The standard error (5.57 mm) is quite low. The regression equation is very near to 1:1 line. Therefore, developed model can be used for future prediction of monthly wind speed at Udaipur.

Study was conducted to develop stochastic model for monthly minimum and maximum relative humidity using 12 years (1992-2003) data of Banswara. The performed statistical test indicates that the series of monthly minimum and maximum relative humidity data are trend free. Their periodic components can be presented satisfactorily by the second harmonics. The stochastic components of both monthly minimum and maximum relative humidity follow second order Markov model. Validation of generated was made with measured series. A high correlation coefficient of 0.9980 and 0.9976 for mean monthly minimum and maximum relative humidity respectively was observed. The correlation was tested by ttest and found to be highly significant at 1 per cent level. The standard error is quite low. The regression equation was very close to 1:1 line. Therefore, the developed model could be used for future prediction of mean monthly minimum and maximum relative humidity, at Banswara.