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In China, unmanned aerial vehicles (UAVs) are increasingly used for broadcast application of agricultural inputs such as pesticides, fertilizers, and seeds. UAVs have the potential for site-specific precision agriculture, facilitating precise management of fertilization, plant protection, and irrigation to reduce environmental footprint of farming. There has been research on the use of UAVs in agriculture, but less is known about UAV-based precision agriculture, particularly pattern management. To close these research gaps, this paper conducted structured in-depth interviews with 18 experts from various fields related to UAVs in Chinese agriculture to study the status quo, drivers, and barriers of adopting UAVs, focusing on UAV-based precision agriculture, particularly pattern management. The results show that the adoption of UAVs in China is influenced by farmers’ production characteristics, farmers’ perceptions about UAVs, and social factors. UAV-based precision agriculture is at the initial stage in China, and the promotion of this approach still needs to overcome technical barriers such as improving the accuracy of crop measurements, developing real-time UAV positioning systems, and enhancing the response time of variable-rate spraying systems, as well as socio-economic barriers like farmers’ limited UAV-related knowledge, small farm sizes, and lack of technical assistance.

As a consequence of rapid ongoing technological developments and increasing integration into agricultural mechanization and agricultural intelligence, UAVs are gradually starting to play an increasingly important role in field crop management and monitoring. This review introduces and covers the development in four major applications of UAVs in maize production: (i) water stress detection, (ii) weed mapping, (iii) nutrient status monitoring and (iv) yield prediction. In addition, this review summarizes UAV data management methods, explains how expert systems work in UAV systems, and provides standardized workflow data for farmers in maize production. In addition, the strengths, weaknesses, opportunities, and threats of UAV use in maize production are analyzed. Based on more than eighty publications and our own research, the discussion and conclusions point out key issues in UAV usage in maize cropping and research gaps that need to be filled, along with a number of recommendations for the development of UAVs in maize production in the future.

As the major labor force has shifted from rural areas to cities, labor shortages in agricultural production have resulted. In the context of technical progress impact, and depending on farm resource endowments, farmers will choose effective labor saving technology such as machinery to substitute for the missing manual labor. The reasons behind farmers’ adoption of machinery technology are worth exploring. Therefore, this study uses 4165 Chinese maize farmers as the target group. Multivariate probit models were performed to identify the factors that affect maize farmers’ adoption of four machinery technologies as well as the interrelation between these adoption decisions. The empirical results indicate that maize sowing area, arable land area, crop diversity, family labor, subsidy, technical assistance, and economies of scale have positive effects on machinery adoption, while the number of discrete fields in the farm has a negative impact. Maize farmers in the Northeast and North have higher machinery adoption odds than other regions. The adoption of these four machinery technologies are interrelated and complementary. Finally, moderate scale production, crop diversification, subsidizing agricultural machinery and its extension education, and land consolidation, are given as recommendations for promoting the adoption of agricultural machinery by Chinese maize farmers.