Productivity and Efficiency of Agricultural and Livestock Systems
- Measure and explain productivity and efficiency at farm, sectoral, and regional scales;
- Identify policy, market, and organizational levers (e.g., investments, support schemes, trade/digitalization, clustering) that shift performance;
- Align productivity with sustainability, especially via green total factor productivity, nutrition-sensitive metrics, and low-input strategies; Showcase innovation in practice—from passive acoustic monitoring to breeding strategies and mobile beekeeping—illustrating how technology and management can convert constraints into performance gains.
- I.
- Measuring green-productivity and spatial efficiency dynamics. This part includes four contributions in total [2,3,4,5]. Each provides a new framework for a multidimensional productivity, integrating environmental values and revealing the specific geographic areas that require spatially coordinated policies. He et al. [2] map the way that provinces’ “green development of agriculture” co-evolve and identify the main drivers through a spatial network analysis and econometric modeling, while Dong et al. [3] examine the impact of citrus industry agglomeration on the green total factor productivity by employing the dynamic spatial Durbin model. In their study, Yang et al. [4] measure the efficiency of citrus farms in China via the use of fertilizers and explore alternative pathways that will reduce their use while maintaining yields and hence productivity at a certain level, while Gu et al. [5] construct an evaluation index system for the development of nutrition-sensitive agriculture in China and measure its development level using an entropy method.
- II.
- Economic viability and optimal farm structures. This part includes five contributions in total [6,7,8,9,10], all of which are focused on the economic efficiency of farms, efficiency determinants and on revealing optimal farm structures. Czubak et al. [6], using primary farm accounting data, investigate the impact of farm investments on the economic efficiency of production factors in Poland while Sokratis et al. [7], using Data Envelopment Analysis on primary data, estimated the efficiency level of sheep farms in Cyprus that operate under extensive, semi-intensive, and intensive systems and presented the main features of the most efficient farms. Pawłowski et al. [8] also delt with livestock farms in their study and investigated which pig-keeping systems are more profitable for pig producers using data from the databases of the Central Statistical Office, the FADN, and the Integrated Agricultural Market Information System of the Ministry of Agriculture and Rural Development in Poland. Miljatović et al. [9] focuses on family farms in Serbia and evaluates their economic performance and sustainability over the 2015–2021 period using the opportunity cost approach, while Akpo et al. [10] assess the impact of different modes of access to land on agricultural productivity in small-scale farms in Benin using regression techniques.
- III.
- Production and management innovative solutions in livestock and apiculture sector. This part comprises two articles [11,12] that demonstrate practical innovations that convert biological and environmental variability into performance improvements. Šveistienė et al. [11] evaluate the effects of the controlled introgression of German Blackheaded Mutton rams on ewe prolificacy and lamb growth while preserving breed structure and integrity indicating enhanced flock management techniques, while Feketéné et al. [12], based on survey data from Hungary, evaluate how transhumant beekeeping practices affects apiary size, productivity, and resilience.
- IV.
- Technology and digitalization on farm efficiency. This part also includes two contributions [13,14] that examine how digitalization, knowledge, IoT and input flows can improve efficiency. Amenyedzi et al. [13] assessed farmers’ knowledge and attitudes toward acoustic technology for farm monitoring in Rwanda using survey data from 430 farmers, while Xu et al. [14] in their article adopt a stochastic frontier gravity model and a trade inefficiency model to analyze the influence of global digital trade development on the efficiency of China’s grain imports while simultaneously estimate the potential for trade expansion.
Conflicts of Interest
References
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Theodoridis, A.; Melfou, K. Productivity and Efficiency of Agricultural and Livestock Systems. Agriculture 2025, 15, 1977. https://doi.org/10.3390/agriculture15181977
Theodoridis A, Melfou K. Productivity and Efficiency of Agricultural and Livestock Systems. Agriculture. 2025; 15(18):1977. https://doi.org/10.3390/agriculture15181977
Chicago/Turabian StyleTheodoridis, Alexandros, and Katerina Melfou. 2025. "Productivity and Efficiency of Agricultural and Livestock Systems" Agriculture 15, no. 18: 1977. https://doi.org/10.3390/agriculture15181977
APA StyleTheodoridis, A., & Melfou, K. (2025). Productivity and Efficiency of Agricultural and Livestock Systems. Agriculture, 15(18), 1977. https://doi.org/10.3390/agriculture15181977