Sesame is one of the important oil seed crops grown for the high-quality oil. Its growth, development, and yield are significantly affected by the changing climate conditions. Evaluating the sesame climatic suitability is crucial to optimize sesame cultivation patterns and planting distribution, and to aid strategic decision making for future agricultural adaptation. Based on agricultural climatic suitability theory and the fuzzy mathematics method, in this study, we established the temperature, precipitation, sunshine, and comprehensive suitability model. Then, we assessed the spatial distribution and chronological changes in climatic suitability under two periods, 1978–1998 (earlier 21 years) and 1999–2019 (latter 21 years). The results showed that compared with the meteorological data in the earlier 21 years, the mean temperature during the sesame-growing season in the latter 21 years increased from 24.48 °C to 25.05 °C, and the cumulative precipitation increased from 744.38 mm to 754.81 mm; however, the sunshine hours decreased from 6.05 h to 5.55 h. Temperature, precipitation, sunshine, and comprehensive suitability during the sesame-growing season in the main sesame-producing areas of China all had a downward trend. The distribution of temperature and comprehensive suitability in the north is higher than that in the south, while the precipitation and sunshine suitability had an uneven distribution. The area of high-temperature suitability and high-precipitation suitability increased from 43.45 × 10⁶ ha to 46.34 × 10⁶ ha and from 3.20 × 10⁶ ha to 7.97 × 10⁶ ha, respectively, whereas the area of high-sunshine suitability decreased from 4.04 × 10⁶ ha to 2.09 × 10⁶ ha. The climate change was more beneficial to sesame cultivation in northeast Anhui where the area of high climatic suitability clearly expanded, and in eastern Jiangxi where the area of the general climatic suitability increased. In contrast, it is worth noting that the area of high climatic suitability in northern Henan decreased and the area of low climatic suitability in Hubei increased. Our results have important implications for improving agricultural production to cope with ongoing climate change.

Sesame (Sesamum indicum L, flora of China) is an essential oil crop in China, but its growth and development are affected by climate change. To cope with the impacts of climate change on sesame cultivation, we used the Maximum Entropy (MaxEnt) model to analyze the bioclimatic variables of climate suitability of sesame in China and predicted the suitable area and trend of sesame in China under current and future climate scenarios. The results showed that the MaxEnt model prediction was excellent. The most crucial bioclimatic variable influencing the distribution of sesame was max temperature in the warmest month, followed by annual mean temperature, annual precipitation, mean diurnal range, and precipitation of the driest month. Under the current climate scenario, the suitable areas of sesame were widely distributed in China, from south (Hainan) to north (Heilongjiang) and from east (Yellow Sea) to west (Tibet). The area of highly suitable areas was 64.51 × 10⁴ km², accounting for 6.69% of the total land area in China, and was primarily located in mainly located in southern central Henan, eastern central Hubei, northern central Anhui, northern central Jiangxi, and eastern central Hunan. The area of moderately suitable areas and lowly suitable areas accounted for 17.45% and 25.82%, respectively. Compared with the current climate scenario, the area of highly and lowly suitable areas under future climate scenarios increased by 0.10%–11.48% and 0.08%–8.67%, while the area of moderately suitable areas decreased by 0.31%–23.03%. In addition, the increased highly suitable areas were mainly distributed in northern Henan. The decreased moderately suitable areas were mainly distributed in Heilongjiang, Jilin, and Liaoning. This work is practically significant for optimizing the regional layout of sesame cultivation in response to future climate conditions.

To overcome the challenges during the crop growth process, e.g., pest infestation, inadequate environmental monitoring, and poor intelligence, this study proposes a crop growth information collection system based on a solar insecticidal lamp. The system comprises two primary modules: (1) an environmental information collection module, and (2) a multi-view image collection module. The environmental information collection module acquires crucial parameters, e.g., temperature, relative humidity, light intensity, soil conductivity, nitrogen, phosphorus, potassium content, and pH, by means of various sensors. Simultaneously, the multi-view image collection module employs three industrial cameras to capture images of the crop from the top, left, and right perspectives. The system is developed on the ESP32-S3 platform. WiFi-Mesh wireless communication technology is adopted to achieve high-frequency, real-time data transmission. Additionally, visualization software has been developed for real-time data display, data storage, and dynamic curve plotting. Field verification indicates that the proposed system effectively meets the requirements of pest control and crop growth information collection, which provides substantial support for the advancement of smart agriculture.