通讯机构：
[Hui Liu] S;School of Economics, Hunan Agricultural University, Changsha 410128, China<&wdkj&>Author to whom correspondence should be addressed.
关键词：
climate change;farm irrigation facilities;agriculture total factor productivity (TFP);technical advancement
摘要：
Due to the trend of global warming, individuals from all walks of life have paid close attention to how climate change affects food security. China is a sizable nation with a rich climate and a diverse range of food crops that are of interest to researchers. Additionally, there is little mention of agricultural technology and farm irrigation facilities in academic research on climate change and agricultural economic growth in China. As a result, this study uses the SBM model, panel fixed effect model, and SYS-GMM model to examine the development trend of climate change and food security based on the panel data of Chinese provinces from 2000 to 2020. The study found that China has maintained an average annual growth rate of 4.3% in agricultural total factor productivity (TFP) in recent years, despite the impact of extreme weather. The average annual precipitation has a depressing influence on the TFP in agriculture, while the average annual temperature has the opposite effect. The farm irrigation facilities and agricultural technology’s moderating impact is mostly shown in how well they attenuate the impact of climate change on the TFP in agriculture. Food crops have thereby improved their ability to survive natural risks and attain higher yields as a result of advancements in agricultural technology and increasing investment in contemporary farm irrigation facilities. The study’s conclusions are used in the article to make the suggestion that strengthening climate change adaptation is necessary to ensure food security. The strategic policy of “storing grain in technology and storing grain in the soil” and the advancement of contemporary agricultural technology must be put into reality while the management system for grain reserves is being improved.
期刊：
Frontiers in Environmental Science,2023年11:1164781 ISSN：2296-665X
通讯作者：
Zhou, F.
作者机构：
[Luo, Zhonghua; Wang, Jingjing; Zhou, Faming] Hunan Agr Univ, Econ Coll, Changsha, Peoples R China.;[Chen, Chen; Wang, Jingjing] Hunan Univ Humanity Sci & Technol, Business Coll, Loudi, Peoples R China.;[Zhou, Faming] Hunan First Normal Univ, Business Coll, Changsha, Peoples R China.
通讯机构：
[Zhou, F.] E;Economic College, China
关键词：
integration of agriculture and tourism;Agricultural green total factor productivity;impact;dynamic spatial Durbin model;Dynamic threshold model
摘要：
The integrated development of agriculture and tourism is conducive to the realization of agricultural ecological value, which will promote the green development of agriculture and improve the green total factor productivity of agriculture as well. Based on panel data in China from 2008 to 2019, the super-efficiency SBM method and the coupling coordination degree model were used to estimate the agricultural green total factor productivity (AGTFP) and the integration level of agriculture and tourism (ATL). The dynamic spatial Durbin model and threshold effect model were used to demonstrate the effects and characteristics of the agriculture and tourism integration on AGTFP. Results showed that: 1) During the study period, AGTFP and ATL increased steadily, and showed obvious spatial agglomeration characteristics; 2) The integration of agriculture and tourism will directly promote the improvement of AGTFP in the local region, and this impact has a spatial spillover effect. The direct effect in the central region in China is the strongest, and the spillover effect in the eastern region is the largest. 3) The influence of the agriculture and tourism integration on AGTFP was enhanced with the improvement of ATL, showing a threshold characteristic. From the perspective of subregion, the threshold value of ATL in the eastern region is the lowest, while the threshold value in the western region is the highest. The results of this study provide useful enlightenment for promoting the deep integration of agriculture and tourism and improvement of AGTFP so as to promote the green development of agriculture.
作者机构：
[Zeng, Fusheng; Liao, Wangda] Hunan Agr Univ, Sch Econ, Changsha 410128, Peoples R China.;[Chanieabate, Meseret] Hunan Univ Sci & Engn, Res Inst Rural Revitalizat, Yongzhou 425199, Peoples R China.
通讯机构：
[Meseret Chanieabate] R;Research Institute of Rural Revitalization, Hunan University of Science and Engineering, Yongzhou 425199, China<&wdkj&>Author to whom correspondence should be addressed.
摘要：
Developing countries with small-scale agriculture have yet to exploit the untapped potential of agricultural mechanization. This is because of the misconception that mechanization is often seen as unworthy in small-scale agriculture. The purpose of this paper is to examine the development of agricultural mechanization in China and to provide evidence on how smallholder farmers can access agricultural machinery. A narrative approach was employed to conduct an in-depth analysis of the policies, strategies, and trends associated with agricultural mechanization development. The findings showed that: (1) the establishment and development of mechanization for smallholder agriculture is an evolutionary process that strongly opposes leapfrogging (technocratic behavior) and making large jumps; (2) the foundation of mechanization development should rely on a self-reliance system; (3) an appropriate mechanization theory is the key to inducing the rapid growth of mechanization in small-scale agriculture; (4) the successful application of agricultural machinery requires strong, target-oriented, and pro-farmer policies with effective leadership strategies. We present the key lessons on policy and institutional aspects for countries with small-scale agriculture and who are in the initial stages of agricultural mechanization.
通讯机构：
[Lin, MY ] H;Hunan Univ, Business Sch, Changsha 410082, Peoples R China.
关键词：
modified ensemble empirical mode decomposition (MEEMD);adjustment Mahalanobis–Taguchi system (AMTS);modified health index (MHI);deep neural networks (DNN);artificial intelligence;big data and analytics;data-driven engineering
摘要：
To improve fault diagnosis accuracy, a data-driven fault diagnosis model based on the adjustment Mahalanobis–Taguchi system (AMTS) was proposed. This model can analyze and identify the characteristics of vibration signals by using degradation monitoring as the classifier to capture and recognize the faults of the product more accurately. To achieve this goal, we first used the modified ensemble empirical mode decomposition (MEEMD) scalar index to capture the bearing condition; then, by using the key intrinsic mode function (IMF) extracted by AMTS as the input of classifier, the optimized properties of bearing is decomposed and extracted effectively. Next, to improve the accuracy of the fault diagnosis, we tested different modes, employing the modified health index (MHI), which is designed to overcome the shortcomings of the proposed health index as a classifier in a single fault mode and the deep neural networks (DNNs) as a classifier in a multifault mode. To evaluate the effectiveness of our model, the Case Western Reserve University (CWRU) bearing data were used for verification. Results indicated a strong robustness with 99.16% and 1.09s, 99.86% and 6.61s fault diagnosis accuracy in different data modes. Furthermore, we argue that this data-driven fault diagnosis obviously lowers the maintenance cost of complex systems by significantly reducing the inspection frequency and improves future safety and reliability.
通讯机构：
[Kuangyuan Pei] S;School of Business, Hunan Agriculture University, Changsha 410128, China<&wdkj&>Author to whom correspondence should be addressed.
