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.
Aims: High maize yields in modern well‐managed agroecosystems depend on the use of elite varieties and hybrids. Unfortunately, because of repeated selection at high fertilizer rates, some beneficial traits, such as the interaction with arbuscular mycorrhizal fungi or the release of organic acid anions for phosphate mobilization and for attracting beneficial microorganisms, might be gradually declining in modern elite genotypes. However, old founder lines and landraces possibly carry genetic relicts that originate from pre‐green revolution times that are useful for breeding elite material for low input farming systems.
Methods: Seedling colonization with arbuscular mycorrhizal fungi (AMF) and organic acid anion release were measured in flint lines that were released over more than five decades ago and in six preselected doubled haploid (DH) lines from landraces. P‐uptake‐related root traits were compared under P‐sufficient and P‐deficient conditions.
Results: Weak trends for the loss of AMF colonization or changes in organic acid anion release at low P supply were detected in modern varieties. One DH line from a landrace was found with increased mycorrhization, whereas others were similar to modern elite lines. Overall, substantial genetic variance was encountered for these traits.
Conclusions: The concern that modern elite maize varieties have lost beneficial traits for nutrient acquisition is not substantiated for the flint pool of maize, although weak trends exist. Lines associated with better P‐acquisition efficiency under limited P availability should be utilized for breeding more sustainable varieties.
Unmanned aerial vehicles (UAVs) are a recent innovation in precision agriculture technology. They are being used in a wide range of agricultural practices, whereby pesticide application is one of the most common uses of UAVs in China’s agriculture. However, the economic effects of UAVs in pesticide application have not been sufficiently investigated. To address the gap, this paper used propensity score matching to evaluate the economic effects of UAV adoption on outcome variables including revenue, pesticide costs, time spent on pesticide application, and pesticide application frequency based on a dataset covering over 2000 grain farmers across 11 provinces of China. Furthermore, generalized propensity score matching was used to evaluate the heterogeneity of outcome variables arising from differing UAV adoption intensities. The empirical results show that adoption of UAV increased revenue by approximately 434–488 dollars per hectare and reduced the time spent on pesticide application in the range of 14.4–15.8 h per hectare. Depending on the area with use of UAVs for pesticide spraying, UAV adoption has heterogeneous impacts on grain farmers’ revenue and the time spent on pesticide application. In terms of marginal revenue and marginal time spent on pesticide application, the optimal area with use of UAVs for pesticide spraying is estimated to be 20 hectares of arable land.
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