Diploma in Agricultural Extension Services for Input Dealers (DAESI) programme is a one year diploma programme started by National Institute of Agricultural Extension Management (MANAGE) to impart technical knowledge on agriculture to input dealers. The programme is being implemented by MANAGE through SAMETIs under overall guidance and supervision of respective state departments. State Institute of Agriculture Management (SIAM) is designated as state level implementing institute in Rajasthan. The present study was conducted in agro-climatic zone IIIa (Semi Arid Eastern Plain) and V (Humid South Eastern Plain) of Rajasthan in the year 2021-22. Total 320 respondents, 160 beneficiaries and 160 non-beneficiaries were selected. Almost two third (64.37%) of beneficiaries had medium level of knowledge regarding important aspects covered under DAESI programme whereas in case of non-beneficiaries (68.12%) of respondents had medium to high level of knowledge. The beneficiaries also found high in level of knowledge in all the selected aspects to measure the knowledge level under study.

Aim: The present investigation was undertaken to assess the per se performance, correlation, heritability and genetic advance of temperate genotypes of Cape-gooseberry (Physalis peruviana L.) under sub-tropical condition of District, Nalanda, Bihar (India). Methodology: About 4-6 leaf stage seedlings of 18 temperate genotypes of Cape-gooseberry were arranged in the field in Randomized Block Design with three replications. Each plot consisted 3.00 m x 2.00 m with spacing of 60 cm and 45 cm between and within rows, respectively. Recommended package of practices were applied to raise a good crop. The data were recorded on ten randomly selected plants for eight characters viz., plant height, number of fruit bearing branches per plant, number of fruits per plant, fruit diameter, fruit length, fruit weight, total soluble solids and fruit yield per plant at maturity, and finally data were subjected to statistical analysis to derive valid conclusion. Results: Significant variation was observed for yield and all the yield traits studied except for plant height. High heritability was observed for fruit weight (0.85) and Total solble solids (0.87). Genetic advance was high for branches per plant (25.87), fruit yield per plant (23.21) and fruit weight (22.57). The fruit yield per plant was strongly positively associated with number of fruits per plant, fruit weight and Total soluble solids at genotypic level. Interpretation: Exhisting variability can be utilized for improvement of the crop. Number of branches per plant and number of fruits per plant are governed by additive genes. Heterosis breeding can be rewarding for the trait having high heritability coupled with low genetic advance. Strong genotypic correlation indicated that yield can be enhanced by giving due weightage to number of fruits per plant, fruit weight and total soluble solids during selection. Key words: Cape-gooseberry, Correlation, Genotypes, Genetic advance, Heritability, Yield

India has the world’s second-largest production of fruit and vegetables. In India, a variety of agro-climate zones with unique seasons allow for the cultivation of a diverse range of vegetables. From this study, it was attempted to estimate the production of vegetables in the upcoming year through means of ordinary least squares (OLS) method and ARIMA (Autoregressive Integrated Moving Average) model using secondary data. This study is based on time series data of vegetables from 1990-91 to 2020-21 in open field condition, which was taken from National Horticulture Board (NHB) website, while the area and production reports on cultivation of vegetables from the Horticulture Department, Haryana state of India. In the current context, it was fetched out that the forecasted value of the vegetables production for the year 2021-22 will be 7540814.31 tonnes in open field condition. Further, for predicting the area and production of vegetables in Haryana, ARIMA (1, 2, 1) was fitted after experimenting with various lags of the moving average and autoregressive procedures.