Monthly, seasonal and annual trends of rainfall and temperature (both minimum and maximum) have been analyzed using the Mann–Kendall trend test (a non-parametric test) and Sen's slope estimator for Sagar division, India from 1988 to 2018. Sagar division is a drought-prone zone of Madhya Pradesh, India. The same analysis has been performed for two drought indices, the Standardized Precipitation Index (SPI) and Reconnaissance Drought Index (RDI). Both indices were calculated to see the trend in the drought for 35 rain-gauge stations belonging to the study area. The study revealed that the minimum temperature had increased more as compared to the maximum temperature in the last 31 years. The strong similarity in the results of Sen's slope of SPI and RDI were seen for both significant and non-significant trends. Analysis of Variance (ANOVA) test validates the substantial similarity between SPI and RDI based on Sen's slope. It also indicated the suitability of RDI for future projection of drought using the general circulation models (GCMs) or regional climate models (RCMs) in meteorological drought as well as the agricultural drought category. In contrast, the SPI indicated the meteorological drought only. The distribution of trends of temperature and drought indices were presented using the kriging interpolation.
To study the effect of Probiotic (Saccharomyces cervisiae) supplementation in pre-ruminant (0-3 months age) buffalo calves, twenty buffalo calves were divided into two groups of ten calves each according to their body weight. One group was the control while the other group was supplemented with bacteria Saccharomyces cervisiae-containing Probiotic @ 15g/calf/d in milk for a period of two months under field condition. Fortnightly growth rate of calves revealed that the effect of Saccharomyces cervisiae was more effective (P<0.01) during first month of supplementation but could not sustain in the second month. Never the less, probiotic supplementation led to an overall improvement (P<0.05) in the growth rate of buffalo calves. It also helped in preventing occurrence of diarrhea and reduced mortality during early stage of life.
The central India region has been seriously affected by repeated droughts in recent decades due to climate change, which is the main reason for conducting this research. It is still uncertain how the numerous climate models could precisely estimate the future climate for central India. The study mainly focuses on the forcing global climate models (GCMs) and the regional climate models (RCMs). The models have been checked using the coefficient of correlation (r2), Nash Sutcliffe efficiency (NSE) and an improved method, Skill score (SS). The performance is also spatially checked on ArcGIS using the kriging interpolation. The bias-corrected GCMs performed more authentic than the CORDEX RCMs in signifying maximum and minimum temperatures for the Bundelkhand region in central India. Bias-corrected GCMs, EC-EARTH, CCSM4 and GFDL-ESM-2M affirmed the best models on multiple time scales for maximum and minimum temperature in the study region. Maximum NSE and r2 have been observed for seasonal minimum temperature. GCM-EC-EARTH has shown 97% to 98% accuracy, while GCM-GFDL-ESM-2M has demonstrated 84% to 97% accuracy among other selected models. The research outcomes will also assist policymakers in developing strategies and policies for the future climate of central India with the help of more precise projected climatic data.
Arid zones are characterized by high evaporation, low and uneven rainfall, undulated topography, presence of salt layers at shallow depth in the soil and poor-quality ground water. Under these conditions an innovative farmer in the district of Pali in the state of Rajasthan, India explored options for farm diversification under hot-arid conditions at his farm. His motivation brought him to the ICAR-Central Arid Zone Research Institute (CAZRI), Krishi Vigyan Kendra (KVK) where he was trained in various basic aspects of rain water harvesting. KVK, Pali studied the methods and innovative ideas utilized by the farmers and the subsequent gain in yield and income by adoption of rainwater harvesting at his farm on a yearly basis. Initially he constructed a small rainwater harvesting structure by which he was able to store substantial quantities of water for longer duration. As a result of constant motivation, he constructed a concrete rainwater storage structure (40M x 40M x 3.5M) and explored further options to increase production at his farm. Also, development of goat farming, intercropping, raising fodder crops and grasses, and developing a fishery, all from the gains of water harvested from rains, gave him confidence and added to the prosperity of his farm. Presently, on farm productive activities, family labour mobilization and diversification provide him with a stable income. This experiential learning also led to new knowledge emerging from interactions among a hitherto powerful scientific hierarchy and served as role model for other farmers’ adoption of innovative techniques.
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