Agricultural mechanization is recognized as an important technology to increase agricultural productivity, face labor shortages, and reduce post-harvest loss. However, variations among farms' characteristics and agricultural production systems suggest adopting a targeted strategy in mechanization programs for farmers. This research aimed to answer the following questions in the particular case of Haiti: are there different types of smallholder farmers in terms of mechanization use and socio-economic characteristics? What types of mechanization are used by farmers, and what drives their use among different types of farmers? What are the different types of farms in terms of mechanization use? We used typology construction methodology (principal component analysis (PCA) and hierarchical cluster analysis (HCA)) for a sample of 637 farmers and have identified four different clusters of farmers according to the characteristics of the farms they managed: "Little rain-fed farms" (cluster 1), "Little lowlands farms" (cluster 2), "Medium-sized farms in irrigated plains" (cluster 3), and "Large fragmented mountain farms". Farms in cluster 3 were those who used more agricultural mechanization, and the results of multinomial logistic regression (MNLR) model revealed that the significant drivers of this use were location, access to credit and low food security status. Mechanization use of farms in clusters 1 and 4 was distinctively driven by saving behavior and off-farm income, respectively. In the pooled sample, the drivers of mechanization were: regions or location, age of the farmers, irrigation, livestock, access to credit, off-farm income and food security status. This study contributes to the literature by testing new drivers of agricultural mechanization such as food security status, and off-farm income. The findings can be used to design appropriate mechanization strategies to increase productivity and face labor price/scarcity challenges. They suggest that mechanization policies should focus on agricultural equipment that are adapted to the specificities of the production systems of each farm type, and strengthen access to credit. Otherwise, mechanization will be predominantly used only in irrigated lowlands.
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http://dx.doi.org/10.1038/s41598-024-62883-6 | DOI Listing |
Sci Rep
December 2024
College of Economics and Management, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
In light of the Chinese government's dual carbon goals, achieving cleaner production activities has become a central focus, with regional environmental collaborative governance, including the management of agricultural carbon reduction, emerging as a mainstream approach. This study examines 268 prefecture-level cities in China, measuring the carbon emission efficiency of city agriculture from 2001 to 2022. By integrating social network analysis and a modified gravity model, the study reveals the characteristics of the spatial association network of city agricultural carbon emission efficiency in China.
View Article and Find Full Text PDFHuan Jing Ke Xue
January 2025
College of Ecology and Environment, Ningxia University, Yinchuan 750021, China.
Replacing traditional plastic mulch with fully biodegradable mulch is an important research direction to solve the problem of "white pollution," but whether it can truly realize biodegradation is still the focus of many scholars. In this study, field and indoor experiments were carried out in Pingluo County, Ningxia Hui Autonomous Region, using poly(butyleneadipate-co-terephthalate) (PBAT) fully biodegradable mulch film and ordinary polyethylene (PE) mulch film, with no mulch film (CK) as the control. Macroscopic characteristics such as the degree of apparent cracking of the mulch film, loss of the mulch film area, and the rate of weight loss were observed, and the results were combined with the results of scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and thermogravimetry (TGR).
View Article and Find Full Text PDFPlant Sci
December 2024
State Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan 455000, China; Zhengzhou Research Base, State Key Laboratory of Cotton Bio-breeding and Integrated Utilization, School of Agricultural Sciences, Zhengzhou University, Zhengzhou, Henan 450001, China. Electronic address:
Cotton is an important source of natural fibers. The AP2/ethylene response factor (ERF) family is one of the largest plant-specific transcription factors (TFs) groups, playing key roles in plant growth and development. However, the role of ERF TFs in cotton's growth and development remains unclear.
View Article and Find Full Text PDFFood Chem
December 2024
School of Agricultural Engineering and Food Science, Shandong University of Technology, No. 266 Xincun Xilu, Zibo, Shandong 255049, China. Electronic address:
Soybeans are used for human consumption or animal feed due to their abundant protein content. In this study, visible-near infrared (VNIR) hyperspectral imaging (HSI) and short-wave infrared HSI combined with three-levels data fusion methods were employed to detect the protein content of soybean seeds, including measurement-level fusion, feature-level fusion, and decision-level fusion. Additionally, three novel decision-level fusion methods were proposed, including binary linear regression, feature-based multiple linear regression (MLR), and model-based MLR.
View Article and Find Full Text PDFBMC Plant Biol
December 2024
College of Tobacco, Guizhou University, Guiyang, 550025, PR China.
Background: The degree of yellowing in tobacco leaves is an important indicator for determining the maturity and harvesting time of tobacco leaves. Decreasing chlorophyll levels helps speed up the ripening process of tobacco leaves for easier mechanical harvesting. Identifying and utilizing genes that regulate yellowing in tobacco leaves are crucial for developing tobacco varieties suitable for mechanized harvesting and understanding the molecular processes that control leaf color changes.
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