通过集群一线示范(CFLD)确保生产力优势——脉冲:全国经验

IF 0.3 4区 农林科学 Q4 AGRICULTURE, MULTIDISCIPLINARY Indian Journal of Agricultural Sciences Pub Date : 2023-06-06 DOI:10.56093/ijas.v93i5.103296
ATAR SINGH, A K SINGH, S K DUBEY, V P CHAHAL, RANDHIR SINGH, ANUPAM MISHRA, RAJBIR SINGH, B C DEKA, S K SINGH, S S SINGH, LAKHAN SINGH, A K TRIPATHI, Y G PRASAD, ANJANI KUMAR, M J CHANDRA GOWDA, SADHNA PANDEY, RAJEEV SINGH
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引用次数: 0

摘要

本研究分析了ICAR-ATARIs下主要豆类种植邦的大型数据(31949公顷面积和79873名农民),包括坎普尔(北方邦)、杰特布尔(拉贾斯坦邦)、浦那(马哈拉施特拉邦)、巴特那(比哈尔邦)、贾巴尔布尔(中央邦)、加尔各答(西孟加拉邦)、古瓦哈提(阿萨姆邦)、西隆(梅加拉亚邦)、海得拉巴(安得拉邦)、班加罗尔(卡纳塔克邦)和巴特那(比哈尔邦)。本分析中包括的脉冲作物来自所有三个生长季节:秋小麦(鸽子-5556公顷,黑豆-6067公顷,绿豆-2689公顷),豇豆(鹰嘴豆-8376公顷,扁豆-3747公顷,田豌豆-1890公顷)和夏季(绿豆-3624公顷)。在2016-17和2017-18两个种植季,获得了代表三个生长季的所有作物在上述状态下的CFLD平均性能数据。因此,CFLD数据的分析来自最小21个州(绿图)和最大24个州(黑图)。分析的主要变量为检验区和示范区平均产量。这些产量是根据产量优势计算的,并与报告的地区水平、州水平、国家水平的产量和给定州各自作物的潜在产量进行了比较(数据来自二手来源,为2017-18年)。因此,分析了不同水平上的产量优势(绝对和百分比),并计算了所有作物在不同季节的变化程度。本文客观地提出了上述分析的结果。
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Ensuring productivity advantages through Cluster Frontline Demonstrations (CFLD)-pulses: Nationwide experiences
The present study is the analysis of large scale data (31949 ha area and 79873 farmers) generated through the CFLD on pulses across the major pulses growing states under the ICAR-ATARIs of Kanpur (Uttar Pradesh), Jodhpur (Rajasthan), Pune (Maharashtra), Patna (Bihar), Jabalpur (Madhya Pradesh), Kolkata (West Bengal), Guwahati (Assam), Shillong (Meghalaya), Hyderabad (Andhra Pradesh), Bengaluru (Karnataka) and Patna (Bihar). The pulse crops included in this analysis were from all three growing seasons: kharif (pigeonpea-5556 ha, blackgram-6067 ha, and greengram-2689 ha), rabi (chickpea-8376 ha, lentil-3747 ha and field pea-1890 ha), and summer (greengram-3624 ha). The average performance data of CFLD were obtained for the above states for all the crops representing all three growing seasons during the cropping seasons of 2016–17 and 2017–18. Thus, CFLD data were analyzed fromacross minimum of 21 states (greengram) and maximum of 24 states (blackgram). The major variables analyzed were average yield obtained from the check plots and demonstrations plots. These yields were computed for yield advantages and also compared with the reported district level, state level, national level yields and the potential yields of the respective crops in the given states (data procured from secondary sources for the year 2017–18). Accordingly, the yield advantages (absolute as well as per cent) at various level were analyzed and their degree of variation was computed for all the crops across the seasons. The paper brings out the results of above analyses in objective manner.
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来源期刊
Indian Journal of Agricultural Sciences
Indian Journal of Agricultural Sciences 农林科学-农业综合
CiteScore
0.80
自引率
25.00%
发文量
273
审稿时长
6 months
期刊介绍: The Indian Journal of Agricultural Sciences publishes papers concerned with the advancement of agriculture throughout the world. It publishes original scientific work related to strategic and applied studies in all aspects of agricultural science and exploited species, as well as reviews of scientific topics of current agricultural relevance. Specific topics of interest include (but are not confined to): genetic resources, all aspects of crop improvement,crop production,crop protection, physiology, modeling of crop systems, the scientific underpinning of agronomy, engineering solutions, decision support systems, land use, environmental impacts of agriculture and forestry, impacts of climate change, rural biodiversity, experimental design and statistical analysis, the application of new analytical and study methods (including molecular studies) and agricultural economics. The journal also publishes book reviews. Articles are accepted on the following broad disciplines: Agric. Engineering & Technology, Agric. Social & Economic Sci., Agronomy, Biometry, Biosciences, Cytology, Ecology, Environmental Sciences, Fertilization, Forestry , Genetics, Horticultural Sciences, Microbiology, Pest, Weed Control etc., Molecular Biology, Plant Pathology, Plant Breeding, Physiology and Biochemistry, Soil Sciences, Special Cultivation Technology, Stress Breeding, Agric. extension, and Cell Biology.
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