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Due to climate change, the rainfall pattern has changed, which ultimately either cause flood or drought in any region of the world. Hence, a rainfall variability analysis helps to manage the water resources better. Rainfall variability analysis of a long term at particular area reveals vital information about past and future climate. The study's objective was to analyse the rainfall variability and intensity oflong term monthly rainfall data (1982-2018) using the Precipitation Concentration Index (PCI). Data was collected from Punjab Agricultural University, Regional Research Station, located at Bathinda, India. The PCI was calculated for the annual, winter, pre-monsoon, monsoon, post-monsoon season, and decadal scale. Results have outlined that PCIAnnual ranges from the lowest of 14.96 in 2006 to the highest of 43.82 in 2000, and the average of 3 7 years is 23.22. About "'59.5% of the year PCIAnnual was characterised by Strong Irregularity of Precipitation Distribution (SIPD, PCIAnnuai> 20), an indication of SIPD within the 37 years. While "'2.7% of the year recorded annual value within the moderate irregular range (lO

Changes in climatic conditions are associated with changes in the physicochemical properties of many fruits. Four germplasms of cashew apple originating from Brazil, Tanzania, Ghana (herein referred to as local) and Mozambique but all grown in Ghana were studied to assess the effect of agro-climatic zones on the sugar accumulation, pH, and weight of these cashew apples. Cashew apples were sourced from experimental stations in Bole and Wenchi in the Northern and Savannah regions of Ghana, respectively. A total of 1800 fruits were used for the experiment. Inter and intra significant differences (P < 0.05) were scored amongst germplasms collected from both locations concerning the measured parameters. Sugar ranged between 8.7% - 12.5% with fruits from Bole having the highest sugar content. The pH value ranged from 3.9 (Local germplasm from Bole) - 4.3 (Tanzania germplasm from both locations). The weight ranged between 33 g (Tanzania germplasm from Bole) - 69.8 g (Brazil germplasm from Bole). Meteorological data (from February 2017-April 2018) collected from both locations influenced the parameters, thus associating with the fruits from both locations. Conclusively, the present study indicated that, weather and geographical locations had effect on sugar content, pH, and weight of cashew apples. [ABSTRACT FROM AUTHOR]

Dynamics of poverty has become a debatable issue and has emerged as one of the most common socioeconomic challenge across the developing world. The present research examines the issue of poverty in the multidimensional spectrum across the agro-climatic zones in Punjab Province of Pakistan on the basis of Pakistan Social and Living Standard Management (PSLM)/Household Integrated Economic Survey (HIES) data (1998–1999 to 2013–2014). The study employed Alkire and Foster methodology and analyzed that the dynamics of multidimensional poverty across agro-climatic zones exhibits mixed trends. Overall estimates designate a significant decline over the decade, whereas slower declining pace was mainly attributed to the wider deprivation of different socioeconomic spheres of well-being. [ABSTRACT FROM AUTHOR]

The projected demand of maize production in India in 2050 is 4-5 times of current production. With the scope for area expansion being limited, there is need for enhancement of yield. This calls for identifying areas where huge unrealized yield potential exists. With a view to address the issue, the present study delineates homogeneous agro-climatic zones for maize production system in India taking district as a unit and using the factors production, viz. climate, soil, season and irrigated area under the crop. There are 146 districts in India that grow maize as a major crop. They were divided into 26 zones using multivariate cluster analysis. Study of variation in yield between districts within a zone vis-à-vis crop management practices adopted in those districts was found useful in targeting the yield gaps. These findings can have direct relevance to the maize farmers and district level administrators. [ABSTRACT FROM AUTHOR]

The main purpose of this study was to define the perspective of cultivating sunflower hybrids in the northeast of Kazakhstan. The trial included 10 hybrids that originated from the Institute of Field and Vegetable Crops, Novi Sad, Serbia (NS-sunflower hybrids). The study was conducted in the field and laboratory. Testing was carried out by PGTH technique (a preliminary testing of hybrids) ARRIOBC (All-Russian Research Institute of Oil-Bearing Crops) in quadruple frequency and as a production testing on big squares in single frequency. Phenological assessment, plant measurements, definition of oil content, 1000- seed weight and its nature were carried out by the standard methods. The experiments established the length of the vegetative period, growth indicators, yield, oil content and oil yield per hectare, 1000-seed weight and nature of the studied hybrids in three agro-climatic zones in the northeast of Kazakhstan. Two perspective locations for hybrid cultivation were allocated in Pavlodar and east Kazakhstan regions. Further research on developing seed farming technology of the perspective hybrids in Pavlodar region of Kazakhstanis planned. [ABSTRACT FROM AUTHOR]

Understanding yield potential (Yp) and yield gap (Yg) in current intensive maize ( Zea mays L.) production is essential to meet future food demand with the limited resources. In this study, we used the agro-climatic zones (CZs) and the reference weather stations (RWS) buffer zones, together with the Hybird-Maize model to estimate maize Yp in the four maize-growing-regions of China under both irrigated and rainfed conditions. In irrigated maize areas, we got 70 RWS buffer zones, and total maize area in the RWS buffer zones covered 67% of the whole irrigated maize area. In rainfed maize areas, we got 106 RWS buffer zones, which covered 51% of the whole rainfed maize area. As a result, the average Yp was 14.2 t ha −1 and farmers have achieved 58% of Yp. The average water-limited yield potential (Yw) was 10.7 t ha −1 and farmers have achieved 65% of Yw. Further analysis for four maize-growing-regions showed that precipitation was a limiting factor for Yw to fully achieve Yp except in Southwest China (SW), whereas the average precipitation was more than 653 mm during maize growing season. The ratio between Yw and Yp (Yw/Yp) was 51% in Northwest China (NW), and around 80% in both Northeast China (NE) and North China Plain (NCP). The comparison of Yp in different regions showed the low Yp in NE was due to low temperature while Yp in both NCP and SW were limited by low solar radiation. In conclusion, our findings highlight the efficiency and importance to estimate Yp, Yw and Yg by the upscaling method with CZs and RWS buffer zones. Meanwhile, the comparison of Yp, Yw and Yg in different regions was important to improve maize production in future in China. [ABSTRACT FROM AUTHOR]

• Six ML algorithms used for daily reference ET prediction over India. • Real-time and 1-day to 28-day ahead prediction models developed. • ML predictions with gridded climate inputs from ERA5 comparable to FAO-56 models. • MLP, SVR, CNN perform better than LSTM, RF, MARS for station level and gridwise analyses. • Model performance slightly better during Rabi (Oct–Mar) season and 'arid' zone. This study forecasts multi-step-ahead Potential Evapotranspiration (ET O) in India using globally available fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) gridded climate reanalysis products (ERA5). For this purpose, the potential of six machine learning approaches are examined across different agro climatic zones and cropping seasons. Support Vector Regression (SVR), Multivariate Adaptive Regression Splines (MARS), Random Forest (RF), Multi-Layer Perceptron (MLP), one-dimensional Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) models are first evaluated at the station level for up to 28-day-ahead prediction of daily ET O using meteorological station data as well as gridded ERA5 products. Using meteorological observations, at all three stations, SVR performs the best for a prediction horizon (PH) up to 2-days whereas LSTM performs the best for PH of 7-days. Using ERA5 datasets as input, among the three stations, the best performance is observed in Nagpur, where the best models for real-time and 28-day ahead prediction are LSTM (R2 = 0.847 and MAE = 0.474 mm/day) and RF (R2 = 0.722 and MAE = 0.635 mm/day) respectively. As the PH increases from 2-day to 28-day-ahead, models using ERA5 datasets performs better than those using station observations for most of the cases. Although the prediction performance drops initially with the increase in lead time, the drop in performance between 7-day and 28-day-ahead prediction is negligible. Evaluation of gridwise ET O prediction across entire India, using Global Land Evaporation Amsterdam Model (GLEAM) dataset as a reference, indicates MLP and CNN as the top performing models. Considering the crop seasons, model performance during Rabi season (October-March) ranged from 0.103 to 0.145 mm/day (MAE) and 0.977 to 0.988 (R2), which is better than the Kharif season (June-September) where MAE ranged from 0.140 to 0.234 mm/day and R2 ranged from 0.906 to 0.962. During the Rabi season, the ET O prediction performance of the arid agro-climatic zone is found to be superior to the other three agro-climatic zones, with the highest range of R2 (0.939 to 0.955) and lowest range of MAE (0.146 to 0.182 mm/day). Even the worst prediction performance, which is observed in the Humid region during the Rabi season, is also reasonably good (R2 = 0.656 to 0.79); thereby establishing the potential of the proposed models in multi-step ahead ET O prediction across various agro-climatic zones and cropping seasons. [ABSTRACT FROM AUTHOR]

Dairy farmers bear the flagship of the mammoth total of milk production, therefore, their preference for the bovine which includes cattle and buffalo, must be counted. The liking or preference is affected by a range of factors. Bovine preference can be referred to as the greater liking for one dairy animal over another or other dairy animal. This includes certain major factors as economic, climatic, animal or bovine trait, marketing, governmental support, traditional aspects, technical support, infrastructure and so on. For the study, South-Bihar Alluvial Plain Zone was selected purposefully from where two districts and under each district, two blocks and from each block two villages were selected randomly. From each village, twenty respondents were selected randomly, which constitute the total sample size of 160 respondents. The study, revealed that economic factor was found to be most (92.7%) influencing factor and ranked 1st among various factors followed by climatic factor (92.3%) ranked 2nd, marketing factor (91.8%) ranked 3rd, trait factor (85.6%) ranked 4th, governmental factors (78.5%) ranked 5th, traditional factors (76.9%) ranked 6th, technical factors (74.4%) ranked 7th, infrastructural factor (70.1%) ranked 8th, socio-psychological factor (61.7%) ranked 9th and NGOs factor (60.4%) ranked 10th among above said factors. [ABSTRACT FROM AUTHOR]

This study examines the marketing system of small ruminants in three different agro-climatic zones of Karnataka in India. Multistage random sampling technique was used to select 60 small ruminant farmers from three viz. Bijapur (Arid zone), Gulbarga (Semi-arid zone) and Udupi (Coastal zone) district of Karnataka state. A structured questionnaire which had earlier been subject to face validity and has a reliability coefficient of 0.87 was used to collect data from the samples respondents. Data was analysed using statistical package for social science (SPSS).The results of the study revealed that marketing of small ruminants is haphazard in the study areas. Majority of the respondents (85%) sold their animal when they needed cash for home consumption followed by to pay off loan (28.3%) was the main reason to sell their animals. Important marketing channels were relatives and friends, local markets and village collectors. Farmers gave different reasons for selling their animals through different channels. Majority of the farmers used relatives and friends as one of the marketing channels. Most of farmers also felt that there was a difference in the price offered by village collectors and the price they were getting in the livestock markets. And a few of them were of the opinion that village collectors were not reliable in marketing. Price of the animals was establishing based on the body confirmation of the animal. Study also revealed that injured animals fetch less value than the healthy animals. [ABSTRACT FROM AUTHOR]

In India, current fertilizer recommendations are very old and developed based on agro-climatic zones. The assumption is that agro-climatic zones are homogenous units. However, analyses of agro-climatic zones reveal variability in soil within each zone. Current agro-climatic zonal fertilizer recommendations are generalized for entire zone and not addressed to specific soil types. To know the soil variability within the National Agricultural Research Project (NARP) agro-climate zone and suitability of current fertilizer recommendations, sugarcane in northern dry zone of Karnataka was studied as a test crop. The results indicated that agro-climatic zones vary widely in soils and in their potentials, behaviour and response to management. It was also observed that fertilizer application efficiency varied within each zone and within the management units. These differences contributed to errors of both excess and insufficient applications. Besides, there is a continuous removal of secondary and micronutrients by crops in all farming situations resulting in inappropriate management practices. All these suggest that soil-based fertilizer recommendations should be preferred to achieve precision in farming and to maximize crop production, maintain soil health and minimize fertilizer misapplication. [ABSTRACT FROM AUTHOR]