The identification of plant disease is the premise of the prevention of plant disease efficiently and precisely in the complex environment. With the rapid development of the smart farming, the identification of plant disease becomes digitalized and data-driven, enabling advanced decision support, smart analyses, and planning. This paper proposes a mathematical model of plant disease detection and recognition based on deep learning, which improves accuracy, generality, and training efficiency. Firstly, the region proposal network (RPN) is utilized to recognize and localize the leaves in complex surroundings. Then, images segmented based on the results of RPN algorithm contain the feature of symptoms through Chan–Vese (CV) algorithm. Finally, the segmented leaves are input into the transfer learning model and trained by the dataset of diseased leaves under simple background. Furthermore, the model is examined with black rot, bacterial plaque, and rust diseases. The results show that the accuracy of the method is 83.57%, which is better than the traditional method, thus reducing the influence of disease on agricultural production and being favorable to sustainable development of agriculture. Therefore, the deep learning algorithm proposed in the paper is of great significance in intelligent agriculture, ecological protection, and agricultural production.

As pesticide abuse becomes increasingly serious worldwide, it is necessary to pay attention to the biopesticide adoption behavior of agricultural producers. It is worth verifying whether agricultural cooperatives, as training organizations sharing the same social network with farmers, can promote the adoption of biopesticides through their technology diffusion function. Therefore, based on survey data of 837 citrus producers in Sichuan Province, China, the IV-probit regression model and a mediation effects model were used to empirically test the impact of technical training on farmers’ adoption of biopesticides in addition to its mechanism, considering the farmers’ perception of technology as the mediation variable. The results show that (a) participation in technical training can significantly enhance the probability of the adoption of biopesticides; (b) farmers’ perceptions of biopesticides’ economic and health benefits play a partial mediating role in the relationship; and (c) technical training has more significant effects on biopesticides adoption behavior for a household with higher-educated household heads, lower household total income, and smaller household size, relative to their counterparts. This study provides evidence for establishing relevant policy to encourage the full adoption of the technical training function of agricultural cooperatives and popularize the use of biopesticides.

The intensification of global climate change leads to frequent mountain torrents, landslides, debris flows and other disasters, which seriously threaten the safety of residents’ lives and property. However, few studies have compared and analyzed the livelihood vulnerability and adaptation strategies of farmers in different disaster-threatened areas under the background of climate change. Based on survey data of 327 households in the areas threatened by mountain floods, landslides and debris flow in Sichuan Province, this study analyzed the characteristics of livelihood vulnerability and adaptation strategies of households in the areas threatened by different disaster types and constructed multinomial logistic regression models to explore their correlations. The findings show that: (1) The livelihood vulnerability indices of farmers in different hazard types showed different characteristics. Among them, the livelihood vulnerability index of farmers in landslide-threatened zones is the highest, followed by the livelihood vulnerability index of farmers in debris-flow-threatened zones, and finally the livelihood vulnerability index of farmers in flash flood threat zones. At the same time, all three natural hazards show a trend of higher vulnerability in the sensitivity dimension than in the exposure and livelihood resilience dimensions. (2) The nonfarming livelihood strategy is the main livelihood strategy for farmers in different disaster-type-threatened areas. At the same time, the vulnerability of farmers choosing the nonfarming livelihood strategy is much higher than that of farmers choosing the part-time livelihood strategy and pure farming livelihood strategy, and the vulnerability of sensitivity dimension is higher than that of the exposure dimension and livelihood resilience dimension. (3) For farmers in landslide- and debris-flow-threatened areas, livelihood resilience is an important factor affecting their livelihood strategy. There was a positive correlation between livelihood resilience and farmers’ choice of pure agricultural livelihood strategies in these two natural-disaster-threatened areas. This study deepens our understanding of the characteristics and relationships of farmers’ livelihood vulnerability and adaptation strategies under different disaster types in the context of climate change, and then provides the reference basis for the formulation of livelihood-adaptive capacity promotion-related policy.

For residents living in earthquake-threatened areas, choosing suitable risk coping behaviors can effectively reduce the loss of family life and property. However, some residents still choose to continue to live within areas at risk of earthquake disaster. Place attachment may play an important role. Based on place attachment theory and the Protective Action Decision Model (PADM), this study explores the possible relationships among place attachment, efficacy beliefs, and evacuation/relocation intention. Furthermore, it examines the mediating role of efficacy beliefs. The study also used the partial least squares method (PLS-SEM) to test samples of 327 rural households in Wenchuan and Lushan earthquake-hit areas. The results show that: (1) Place attachment has a significant effect on response efficacy (RE), but not on self-efficacy (SE); (2) Place dependence (PD) has a negative and significant effect on relocation intention (RI) but has no significant effect on evacuation intention (EI). However, place identity (PI) can indirectly affect EI by influencing RE; (3) Efficacy beliefs have a significant positive effect on EI and RI. These results help us understand the complex relationships among place attachment, efficacy beliefs, and residents’ risk coping behavior, thus providing decision-making references for the formulation and improvement of regional disaster risk management policies.

This study explores the impact of farmland transfer on the multidimensional relative poverty of the elderly in rural areas to provide a reference for the study of rural land transfer in China and improve the welfare system for the elderly. Based on the China Family Panel Studies (CFPS) rural sample data in 2018, this paper uses the AF multidimensional index measurement method to assess multidimensional relative poverty in rural areas. Logit regression estimation examines the single index poverty of rural older adults transferred from rural land and the impact of multidimensional relative poverty, using the propensity score matching method (PSM) to analyze the results’ robustness. The transfer of agricultural land has different impacts on the poverty of different rural elderly poverty indicators and negatively affects the comprehensive effect of rural elderly poverty. The transfer of agricultural land significantly alleviates rural elderly poverty. Reasonable and effective transfer of agricultural land, together with improved rural social security and a caring service system for the elderly, will promote the continuous operation of large-scale agricultural operations and alleviate rural elderly poverty.

With the successful completion of the battle against poverty, after 2020, the focus and difficulty of China’s poverty governance will change from solving absolute poverty to alleviating relative poverty. Analyzing and studying the alleviation of relative poverty from the perspective of public health services is in line with the current needs of consolidating and expanding poverty alleviation in China, and it is also of great significance to building a long-term solution mechanism for relative poverty. In this study, basic panel data were constructed by using the data of five CFPS surveys in 2010, 2012, 2014, 2016, and 2018 and matched with the macro data. The correlation between public health services and rural households’ relative poverty was also analyzed by using logit regression analysis and the KHB mediation effect decomposition method. The results show that (1) public health services play a significant role in promoting the accumulation of health human capital, improving individual feasible ability, and alleviating the relative poverty of rural families; (2) the improvement of public health services is conducive to the alleviation of the relative poverty of rural families; (3) we should continue to increase investment in public health care in underdeveloped areas and strive to promote the balanced development of public health services, so as to further consolidate and expand the achievements of poverty eradication.