农业
粮食安全
多元概率模型
业务
多元化(营销策略)
农业多样化
政府(语言学)
农业经济学
地理
Probit模型
气候变化
农业科学
经济
环境科学
生态学
生物
哲学
语言学
计量经济学
营销
考古
作者
Jeetendra Prakash Aryal,Dil Bahadur Rahut,Sofina Maharjan,Olaf Erenstein
标识
DOI:10.1111/1477-8947.12152
摘要
Climate change poses a major threat to agricultural production and food security in India, and climate‐smart agriculture (CSA) is crucial in addressing the potential impacts. Using survey data from 1,267 farm households in 25 villages from Bihar and Haryana in the Indo‐Gangetic Plains, this study analyzes the factors that determine the probability and level of adoption of multiple CSA practices, including seeds of stress‐tolerant varieties, minimum tillage, laser land leveling, site‐specific nutrient management and crop diversification. We applied a multivariate probit model for the simultaneous multiple adoption decisions, and ordered probit models for assessing the factors affecting the level of adoption. The adoption of the various CSA practices is interrelated, whereas several factors, including household characteristics, plot characteristics, market access and major climate risks are found to affect the probability and level of CSA adoption. Climate‐smart agriculture (CSA) adoption and its intensity also vary significantly between eastern Bihar, which is relatively poor and densely populated, and north‐western Haryana. Engaging multiple stakeholders such as farmers, agricultural institutions, agricultural service providers and concerned government departments at the local level is crucial for the large‐scale uptake of CSA. The study, therefore, calls for agricultural policy reforms so that most of the issues related to the uptake of CSA can be adequately addressed.
科研通智能强力驱动
Strongly Powered by AbleSci AI