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Conjugation of AMUL and ISRO: Development of Feed and Fodder for Dairy Industries
Journal of the Indian Society of Remote Sensing ( IF 2.2 ) Pub Date : 2020-09-28 , DOI: 10.1007/s12524-020-01172-x
Sujay Dutta , Shashank Dwivedi , B. K. Bhattacharya , R. S. Sodhi

Feed and fodder comprises about 65% of the cost of milk production of a dairy industry. It is a crucial input for enhancing the milk production. To address the issue of fodder availability at first, its assessment is required. Thus, we have implemented remote sensing technique for fodder crop assessment at state level to create a baseline for fodder crop availability for dairy managers to plan for its procurement during deficit and for better management purposes during its excess. We have devised a technique for remote sensing-based fodder crop assessment based on spectral pattern of growth, i.e. normalised difference vegetation index profile and land surface wetness index profile of series of IRS LISS-III satellite data taken during the crop growth cycle for a hybrid method of crop classification. Second objective to address the issue of mitigating the deficit of fodder crops, we have demonstrated the satellite derived intersection of probable high soil wetness area and available current fallows during a crop growing season which can be utilised for growing fodder crops. For macro-level planning in a state for developing new fodder-growing areas, we have demonstrated the availability of soil wetness factor from SMAP data. Fallow land available between two cropping seasons can be identified through remote sensing for growing short duration fast growing fodder crops. This project has been a demonstration project for AMUL in Gujarat to implement it subsequently at national level.

中文翻译:

AMUL 和 ISRO 的结合:为乳制品开发饲料和饲料

饲料和饲料约占乳制品行业牛奶生产成本的 65%。它是提高牛奶产量的关键投入。为了首先解决饲料供应问题,需要对其进行评估。因此,我们在州一级实施了用于饲料作物评估的遥感技术,为乳品管理人员制定饲料作物可用性基线,以便在短缺期间进行采购计划,并在过剩期间进行更好的管理。我们设计了一种基于生长光谱模式的基于遥感的饲料作物评估技术,即在作物生长周期期间采集的一系列 IRS LISS-III 卫星数据的归一化差异植被指数剖面和地表湿度指数剖面作物分类方法。解决减轻饲料作物短缺问题的第二个目标,我们已经证明了在作物生长季节期间可能的高土壤湿度区域和可用的当前休耕的卫星衍生的交叉点,可用于种植饲料作物。对于一个州开发新饲料种植区的宏观规划,我们已经证明了 SMAP 数据中土壤湿度因子的可用性。可以通过遥感确定两个作物季节之间可用的休耕地,用于种植短期快速生长的饲料作物。该项目一直是古吉拉特邦 AMUL 的示范项目,随后将在国家层面实施。我们已经展示了可能的高土壤湿度区域和作物生长季节期间可用的当前休耕地的卫星衍生交叉点,可用于种植饲料作物。对于一个州开发新饲料种植区的宏观规划,我们已经证明了 SMAP 数据中土壤湿度因子的可用性。可以通过遥感确定两个作物季节之间可用的休耕地,用于种植短期快速生长的饲料作物。该项目一直是古吉拉特邦 AMUL 的示范项目,随后将在国家层面实施。我们已经展示了在作物生长季节期间可能的高土壤湿度区域和可用的当前休耕的卫星衍生的交叉点,可用于种植饲料作物。对于一个州开发新饲料种植区的宏观规划,我们已经证明了 SMAP 数据中土壤湿度因子的可用性。可以通过遥感确定两个作物季节之间可用的休耕地,用于种植短期快速生长的饲料作物。该项目一直是古吉拉特邦 AMUL 的示范项目,随后将在国家层面实施。可以通过遥感确定两个作物季节之间可用的休耕地,用于种植短期快速生长的饲料作物。该项目一直是古吉拉特邦 AMUL 的示范项目,随后将在国家层面实施。可以通过遥感确定两个作物季节之间可用的休耕地,用于种植短期快速生长的饲料作物。该项目一直是古吉拉特邦 AMUL 的示范项目,随后将在国家层面实施。
更新日期:2020-09-28
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