Not Available

Not AvailableIndia is the world's largest producer and consumer of a wide variety of pulses which is dominated by tropical and sub-tropical crops such as chickpea, black gram, red gram (pigeon pea), green gram (Mungbean), lentil and so on. The world pulse production, area and yield during 2013 was 73 million tonnes (MT), in nearly 80.8 million ha and 904 kg ha-1 respectively (FAOSTAT 2015). In India, production of pulses is around 19.3 million tonnes from 26.3 million ha (ESI 2015) with a very low average productivity of 764 kg/ha. India has witnessed an impressive growth in pulses production during last 5 years. The overall productivity of pulses increased to an impressive 786 kg ha-1 during 2012- 13 as compared to 577 kg ha-1during 2004-05. The credit goes to the improved varieties and production of breeder seed and schemes launched by the government to promote pulses cultivation. Pulses are rich sources of protein and energy but largely cultivated under energy starved conditions, mostly on marginal and sub-marginal land and more than three-fourth of the area under pulses is still rainfed resulting in poor crop productivity (Choudhary, 2013). Green revolution also adversely affected the acreage of pulses causing displacement by rice-wheat cultivation leading to shift of pulse crops in marginal dry lands in the country resulting in decline in the yield of pulses during last few decades. Pulses crop being rich in protein are loved by pests and Blue Bulls (Neelgais). They are also extremely sensitive to heat and cold, besides they are slow crop. All these factors contribute in high fluctuations in yield. To analyse trend and instability tolls like Cumulative Annual Growth Rate (CAGR) and Cuddy-Della Valle Index (CDVI) is employed. To accomplish the objective of import demand analysis to compute long run elasticity of determinant Stock Watson Dynamic OLS has been used. It has been found that import demand for pulses is determined by income, price and urbanization. Results indicate that import price of total pulses has no statistically significant impact on import demand for total pulses. It is important for policymakers to understand that abolishing the existing constraints on imports will not have a major impact on total pulse imports, because the pulse economy is rather weak to respond to market signals in India.Not Availabl

Not Available

Not AvailableRose is grown under traditional and hi-tech cultivation in India. There exists wide difference in the capital investment, variable costs incurred and returns realized in the both production systems. Therefore, the study was undertaken to examine the investments, costs, yields, returns and employment under traditional versus hi-tech cultivation. It was observed that although, the hi-tech farms were capital intensive, require huge initial investment and applied very high doses of inputs such as plant protection chemicals and fertilizers, they performed much better in terms of realization of returns and employment generation in comparison to traditional farms. Regarding gender equity, there was a discrimination against female casual labour working at both the types of farm. To enhance the profitability of rose cultivation, research should be prioritized for developing long-stalked, better shaded and pests and diseases resistant varieties, cost reduction in greenhouse structures and proper market intelligence.Not Availabl

Not Available

Not AvailableThe study was undertaken to examine the cost and returns and efficiency issues in rice cultivation under groundwater irrigation in different regions of Indo-Gangetic plains of India using primary data collected from 1172 randomly selected farmers. A deterministic frontier model namely Data Envelopment Analysis was used in the estimation of farm level efficiencies in rice production. The farm business analysis of rice cultivation showed that the returns were impressive in Trans-Gangetic plains, moderate in Upper and low in Middle and Lower-Gangetic plains. The economic efficiencies of rice farms were found to be low but highly varied spatially. The resource use efficiency for irrigation was poor in all the regions especially under electric operated tubewells. Measures such as educating the farmers regarding better utilization of inputs and rationalization of electricity tariff for irrigation will help to improve farm level efficiencies in rice cultivation.Not Availabl

Not Available

Not AvailableAn equity, efficiency and profitability aspect of migratory sheep production system was examined using primary data pertaining to year 2011 using Gini concentration ratio, data envelopment analysis, and cost accounting method, respectively. The study concluded an inverse relationship between size of farms and size of flocks, and per animal income realization was inversely related to flock size. Net income distribution was almost equitable among large flocks but still some scope existed for equitable income distribution among small flocks. Interestingly, landless sheep owners were technically more efficient but were allocating their resources judiciously. Allocative efficiency and farm size has directly positive relationship. Efforts are required in the forms of technologies, institutions and policies to enhance the production capacity of the sheep system besides tailoring the interventions to tap the existing potential.Not Availabl

Not Available

Not AvailableFumen arc encountenng se•cral is~ m cndea•our to incruse crop productivity. Despite aeveraJ successf \ JI new agricultural technologies related wrtb crop cultivation. India iJ unable to llllin world average mark in ptoductiviry. 0r .. of tho main reuo111 tOr this iJ climaiic conditions and abundance of insects and pests, To mitigate the loss due to pest 1nacb and for better yield, fon:cuting of pest populalion ~on ltlstoricel date end pertinent external cllmotic lnfom1atlon is consi<k'rtd. Autoregressive lntevared Movina A•m~ w11h Exoam011S variables (AR!MAX) hmc·Kries model is applied for modellingand forecesting tho pc$1 populationlfkr testing for stailOMMty. Primaryweekty date (2008-2012) for three pests namely Jassids, WhitcOy and Thrips in Guntur and flridk04 DISlricu along with weekly maximum temperature, minimum temperature, rainfall, maximum RH and minimum RH have been used for model denlopment. Evaluation of forccas11ng Is carried out with relative mean 1bsolutc prtchctoon mw (llMAPE). 01agDOStoc test were applied and re$uhs showed tl\.1t maximumtcmperanwand minimum~ •Iona widl mlltimum relallve humldit> have a slJnjfiamt role for Whitefly and Thrips at Ountur district rcspecll•cly. Rainfall was found to be sianillcant 11 Faridkot d1W1ct in case ofThrips. The fittcJ models olong wilh 1he data points ert also presented. A perusal of liaum 1nd1caies 1hat in bolb districts, the populallon of Whllcny is best pA'dlctcd followed by Jasslds and Thrips.Not Availabl

Not Available

Not AvailableFarmers are encountering several issues in endeavour to increase crop productivity. Despite several successful new agricultural technologies related with crop cultivation, India is unable to attain world average mark in productivity. One of the main reasons for this is climatic conditions and abundance of insects and pests. To mitigate the loss due to pest attacks and for better yield, forecasting of pest population based on historical data and pertinent external climatic information is considered. Autoregressive Integrated Moving Average with Exogenous variables (ARIMAX) time-series model is applied for modelling and forecasting the pest population after testing for stationarity. Primary weekly data (2008-2012) for three pests namely Jassids, Whitefly and Thrips in Guntur and Faridkot Districts along with weekly maximum temperature, minimum temperature, rainfall, maximum RH and minimum RH have been used for model development. Evaluation of forecasting is carried out with relative mean absolute prediction error (RMAPE). Diagnostic test were applied and results showed that maximum temperature and minimum temperature along with maximum relative humidity have a significant role for Whitefly and Thrips at Guntur district respectively. Rainfall was found to be significant at Faridkot district in case of Thrips. The fitted models along with the data points are also presented. A perusal of figures indicates that in both districts, the population of Whitefly is best predicted followed by Jassids and Thrips.Not Availabl

Not Available

Not AvailableChanges in tastes, preferences, lifestyle and changing diet pattern due to rising affluent population are prime factors responsible for emergence of modem retail in India. Primary survey on various socio-economic parameters from 120 randomly selected households in Kochi was conducted. Logit model, conjoint analysis and descriptive statistics were used to infer the results. The family income and distance to the nearest modern retail were found to influence the consumers ’ decision to purchase from modern retails. The high part-worth value for price (less than traditional retails ) points to the importance of price competition to attract consumers. Consumers are willing to coinpromi.se on quality for the sake of lower prime. Factor importance value of modern retail emphasized the need to devise a sale strategy containing two essential ingredients viz. less price than traditional retail and easiness to approach (less than 1 km ) to sustain in competitive race of agri-retail business in KochiNot Availabl

Not Available

Not AvailableModern retail is emerging as the prime factor responsible for changes in food markets mainly due to population expansion and rise in per capita incomeNot Availabl

Not Available

Not AvailableNot AvailableNot Availabl

Forecasting maize yield using ARIMA-Genetic Algorithm approach

Maize is widely cultivated throughout the world and has highest production among all the cereals. India is the sixth largest producer of maize in the world, contributing 2% of global production and accounting for 9% of the total food grain production in the country. Based on increasing growth rates of poultry, livestock, fish, and milling industries, the demand for maize is expected to increase from the current level of 17 to 45 million tons by 2030. To understand the growing pattern and economics of crop production, it is necessary to predict crop yield using statistical models and geographic information system soil mapping and the impacts of insect and pest damage. In this study, the focus was to forecast maize yield in India using an autoregressive integrated moving average (ARIMA) model and genetic algorithm (GA) approach. GA simulates the evolution of living organisms, where the fittest individual dominates the weaker ones by mimicking the biological mechanism of evolution, such as selection, crossover, and mutation. GA has successfully been applied to solve optimization problems. The study reveals that implementation of GA in ARIMA enhances the prediction accuracy of the model.ICA