Determining the suitable areas for winter wheat under climate change and assessing the risk of freezing injury are crucial for the cultivation of winter wheat.  We used an optimized Maximum Entropy (MaxEnt) Model to predict the potential distribution of winter wheat in the current period (1970–2020) and the future period (2021–2100) under four shared socioeconomic pathway scenarios (SSPs).  We applied statistical downscaling methods to downscale future climate data, established a scientific and practical freezing injury index (FII) by considering the growth period of winter wheat, and analyzed the characteristics of abrupt changes in winter wheat freezing injury by using the Mann-Kendall (M-K) test.  The results showed that the prediction accuracy AUC value of the MaxEnt Model reached 0.976.  The minimum temperature in the coldest month, precipitation in the wettest season and annual precipitation were the main factors affecting the spatial distribution of winter wheat.  The total suitable area of winter wheat was approximately 4.40×10⁷ ha in the current period.  In the 2070s, the moderately suitable areas had the greatest increase by 9.02×10⁵ ha under SSP245 and the least increase by 6.53×10⁵ ha under SSP370.  The centroid coordinates of the total suitable areas tended to move northward.  The potential risks of freezing injury in the high-latitude and -altitude areas of the Loess Plateau, China increased significantly.  The northern areas of Xinzhou in Shanxi Province, China suffered the most serious freezing injury, and the southern areas of the Loess Plateau suffered the least.  Environmental factors such as temperature, precipitation and geographical location had important impacts on the suitable area distribution and freezing injury risk of winter wheat.  In the future, greater attention should be paid to the northward boundaries of both the winter wheat planting areas and the areas of freezing injury risk to provide the early warning of freezing injury and implement corresponding management strategies.

Agricultural mechanization and custom machine services have developed rapidly in China, which can influence rice production efficiency in the future.  We calculate technical efficiency, allocative efficiency, and scale efficiency using data collected in 2015 from a face-to-face interview survey of 450 households that cultivated 3 096 plots located in the five major rice-producing provinces of China.  We use a one-step stochastic frontier model to calculate technical efficiency and regress the efficiency scores on socio-demographic and physical land characteristics to find the influencing variables.  Variables influencing technical efficiency are compared at three different phases of rice cultivation.  We also calculate technical efficiency by using the Heckman Selection Model, which addresses technological heterogeneity and self-selection bias.  Results indicate that: (1) the average value of technical efficiency using a one-step stochastic frontier model was found to be 0.74.  When self-selection bias is accounted for using the Heckman Selection Model, the average value of the technical efficiency increases to 0.80; (2) mechanization at the chemical application phase has a positive effect on technical efficiency, but mechanization does not affect efficiency at the plowing and harvesting phases; (3) machines are overused relative to both land and labor, and high machine input use on the small size of landholding has resulted in allocative inefficiency; (4) rice farmers are overwhelmingly operating at a sub-optimal scale.  Future policies should focus on encouraging farmland transfer in rural areas to achieve scale efficiency and allocative efficiency while promoting mechanization at the chemical application phase of rice cultivation to improve technical efficiency. 

The ascomycete fungus Colletotrichum gloeosporioides is a devastating plant pathogen with a wide host range and worldwide distribution.  Carbendazim has been widely used to control anthracnose caused by the C. gloeosporioides complex in China for more than 30 years and resistance to carbendazim has been reported in China.  A total of 125 Colletotrichum isolates of strawberry and yam were collected from different geographical regions in Hubei Province, China.  Approximately 52.8% of Colletotrichum spp. isolates showed resistance to carbendazim.  The isolates tested in this study belong to four species, and the frequencies of resistant isolates differed across Colletotrichum species.  Resistant isolates were found in C. siamense and C. fructicola.  In contrast, all isolates of C. gloeosporioides and C. aenigma were sensitive to carbendazim.  Highly carbendazim-resistant isolates harbored the E198A mutation in the β-tubulin 2 (TUB2) gene, whereas moderately carbendazim-resistant isolates harbored the F200Y mutation in the TUB2 gene.  Carbendazim-sensitive Colletotrichum isolates in this study were not genetically similar enough to form a separate cluster from resistant isolates.  The result of this study emphasizes the importance of knowing which Colletotrichum sp. is present, when strategies for disease control are made.