Agriculture

Research

15 pages, 1569 KiB

Open AccessArticle

Targeting Environmental and Technical Parameters through Eco-Efficiency Criteria for Iberian Pig Farms in the dehesa Ecosystem

by Javier García-Gudiño, Elena Angón, Isabel Blanco-Penedo, Florence Garcia-Launay and José Perea

Agriculture 2023, 13(1), 83; https://doi.org/10.3390/agriculture13010083 - 28 Dec 2022

Cited by 3 | Viewed by 3512

Abstract

Eco-efficiency could be defined as the simultaneous ability to achieve acceptable economic results with the least possible environmental degradation. Its analysis in crop and livestock production systems has become a hot topic among politicians and scientists. Pig pasture production systems are in high [...] Read more.

Eco-efficiency could be defined as the simultaneous ability to achieve acceptable economic results with the least possible environmental degradation. Its analysis in crop and livestock production systems has become a hot topic among politicians and scientists. Pig pasture production systems are in high commercial demand because they are associated with high quality and environmentally friendly products. This work aimed to assess the eco-efficiency of pig farms and subsequently explore the determinants of inefficiency in the dehesa ecosystem in the southwest of the Iberian Peninsula. Farmers from 35 randomly selected farms were interviewed to obtain farm-level data. The eco-efficiency level was calculated through a joined data envelopment analysis (DEA) and life cycle assessment (LCA) approach. Subsequently, a truncated Tobit model was applied to determine factors associated with inefficiency. The results of the research revealed that Iberian pig farms are highly eco-efficient. The estimated average eco-efficiency score is 0.919 and ranges from 0.479 to 1, suggesting that the average farm could increase its value by about 8.1%. This means that the aggregate environmental pressures could be reduced by approximately this proportion (8%) while maintaining the same input level. The determinants related to social and demographic characteristics that positively affected eco-efficiency were the number of children, while years of farm activity and educational level had a negative effect. On the other hand, farm’s characteristics and the type of management, the percentage of own surface area, the percentage of livestock use, and the high proportion of pigs fattened in montanera, positively affected the eco-efficiency level. Full article

(This article belongs to the Special Issue Optimization of Resource Use for Productivity, Efficiency, and Sustainability in Agriculture)

► Show Figures

Figure 1

16 pages, 1479 KiB

Open AccessArticle

Labour Commutation in the Agricultural Sector—An Analysis of Agricultural Workers in Chile

by Claudio Mancilla, Luz María Ferrada, Sergio Soza-Amigo and Adriano Rovira

Agriculture 2022, 12(12), 2110; https://doi.org/10.3390/agriculture12122110 - 9 Dec 2022

Viewed by 1826

Abstract

Agricultural activity is a key strategic sector for countries, particularly for food production. One way to strengthen the sector is through the use of technology. However, while integrating new technologies, challenges have emerged in the sector with regard to incorporating workers. Thus, one [...] Read more.

Agricultural activity is a key strategic sector for countries, particularly for food production. One way to strengthen the sector is through the use of technology. However, while integrating new technologies, challenges have emerged in the sector with regard to incorporating workers. Thus, one way to resolve this workforce shortfall could be through labour commutation, which consists of people living in one territory but working in another. Therefore, this study aims to analyse the likelihood of agricultural workers becoming worker commuters. Chile is used as a case study, drawing on the Chilean National Employment Survey of 2018 to analyse differences among the five largest regions in the country: Great North, Small North, Central Zone, South, and Chilean Patagonia. Each zone possesses different characteristics, and a propensity score matching process was carried out within the data. The results indicate that agricultural workers with a higher education level, full-time jobs, working in the formal sector, and younger workers are more likely to commute. Different impacts of variables were found across the zones. However, most of the variables have similar impact on the likelihood to commute in different areas. Thus, from a labour perspective, public policies can create general incentives to attract a new workforce to strengthen the agricultural sector. Full article

(This article belongs to the Special Issue Optimization of Resource Use for Productivity, Efficiency, and Sustainability in Agriculture)

► Show Figures

Figure 1

18 pages, 1501 KiB

Open AccessFeature PaperArticle

Technical Efficiency of Agriculture in the European Union and Western Balkans: SFA Method

by Danilo Đokić, Tihomir Novaković, Dragana Tekić, Bojan Matkovski, Stanislav Zekić and Dragan Milić

Agriculture 2022, 12(12), 1992; https://doi.org/10.3390/agriculture12121992 - 24 Nov 2022

Cited by 14 | Viewed by 2875

Abstract

Improvements in productivity and efficiency, together with agricultural modernization, are crucial in the process of future sustainable development. As Western Balkan (WB) countries are in the process of integration into the European Union (EU), the importance of agricultural efficiency in an economic and [...] Read more.

Improvements in productivity and efficiency, together with agricultural modernization, are crucial in the process of future sustainable development. As Western Balkan (WB) countries are in the process of integration into the European Union (EU), the importance of agricultural efficiency in an economic and environmental context and the actuality of the problems of the agricultural sector are very important. In that context, the paper’s main goal is to examine agriculture’s technical efficiency in the EU and WB. The additional goal is to group analyzed countries by agricultural performances. A stochastic frontier analysis (SFA) is used to calculate the technical efficiency of agriculture. Results have shown a significant difference in technical efficiency between WB and the EU. Furthermore, the cluster analysis has indicated the connection between overall economic development and agricultural development, partially “deformed” by agri-environmental and climate conditions. The exogenous factors do not have a crucial influence on the overall technical efficiency of agriculture in observed countries, indicating that the endogenous factors must be improved. The paper impacts recommendations for optimizing the use of inputs and improving the educations of farmers in WB countries to achieve economic and environmental goals. Full article

(This article belongs to the Special Issue Optimization of Resource Use for Productivity, Efficiency, and Sustainability in Agriculture)

► Show Figures

Figure 1

13 pages, 272 KiB

Open AccessArticle

Differences and Factors of Raw Milk Productivity between China and the United States

by Yuhang Bai, Kuixing Han, Lichun Xiong, Yifei Li, Rundong Liao and Fengting Wang

Agriculture 2022, 12(11), 1899; https://doi.org/10.3390/agriculture12111899 - 11 Nov 2022

Cited by 2 | Viewed by 2147

Abstract

In order to explore the differences in the productivity level and influencing factors of raw milk between China and the United States, this study uses the stochastic frontier production function and is based on the input and output of factors of raw milk [...] Read more.

In order to explore the differences in the productivity level and influencing factors of raw milk between China and the United States, this study uses the stochastic frontier production function and is based on the input and output of factors of raw milk in China and the United States from 2005 to 2020 to measure the impact of factor inputs on raw milk output and the output differences. The results of the study found that: the inefficiency term of raw milk production technology in China is higher than that in the United States; feed costs and fuel power costs have a significant positive role in promoting the growth of raw milk output in China and the United States; health and epidemic prevention costs, as well as maintenance costs, have significant impacts on the output value of raw milk in China, but they have no significant impact on the output value of raw milk in the United States. In terms of the contribution of each input factor, the contribution share of feed costs to the output value of raw milk in China is 52.53% and 25.74%, respectively, compared to the value of raw milk in the United States; The contribution share of technological progress to the output value of raw milk in China is 34.92%, and 53.77%, respectively, compared to U.S. raw milk production value. In order to narrow the productivity gap with the United States dairy industry, China’s dairy industry must pay attention to the moderate-scale breeding of dairy cows; develop an integrated production mode of planting and breeding; promote the development of grain to feed; accelerate the genetic improvement of dairy cattle populations; and learn from the pasture management experiences of foreign countries. Full article

(This article belongs to the Special Issue Optimization of Resource Use for Productivity, Efficiency, and Sustainability in Agriculture)

21 pages, 642 KiB

Open AccessFeature PaperArticle

Technical Efficiency Analysis of Layer and Broiler Poultry Farmers in Pakistan

by Nisar Ahmed Khan, Majid Ali, Nihal Ahmad, Muhammad Ali Abid and Sigrid Kusch-Brandt

Agriculture 2022, 12(10), 1742; https://doi.org/10.3390/agriculture12101742 - 21 Oct 2022

Cited by 6 | Viewed by 5098

Abstract

Achieving high production with limited resources is a major challenge faced by poultry farmers in countries with developing economies, such as Pakistan. Optimization of the technical efficiency (TE) of poultry business operations is a promising strategy. A representative sample of 210 poultry farms [...] Read more.

Achieving high production with limited resources is a major challenge faced by poultry farmers in countries with developing economies, such as Pakistan. Optimization of the technical efficiency (TE) of poultry business operations is a promising strategy. A representative sample of 210 poultry farms in the province of Punjab in Pakistan was analyzed for TE. The studied sample comprised 105 layer chicken farms (battery cage system, egg production) and 105 broiler chicken farms (environmental control shed system, meat production). A Cobb–Douglas stochastic frontier production analysis approach with the inefficiency effect model was used to simultaneously estimate TE levels and identify factors that influence efficiency. The results indicated that flock size, labor, feed, and water consumption are positively related to egg production, whereas vaccination was found to be insignificant. For broiler businesses, flock size, feed, and water consumption were positively related to the output, whereas labor and vaccination were found to be insignificant. The results of the TE inefficiency effect model revealed that farmer age, education, experience, access to credit, and access to extension services all had a significant and positive influence on the technical efficiency of both layer and broiler farmers. The estimated mean TE level of layer and broiler poultry farmers was 89% and 92%, respectively, evaluated against the benchmark of the identified frontier of efficient production with prevailing systems. The study concludes that it is possible to increase egg production by 11% and meat production by 8% by making more efficient use of the available resources and technology. To improve poultry farmers’ efficiency, policy interventions should focus more on the pronounced effects of variables such as education, farmer experience, credit access, and extension services. Full article

(This article belongs to the Special Issue Optimization of Resource Use for Productivity, Efficiency, and Sustainability in Agriculture)

► Show Figures

Figure 1

19 pages, 617 KiB

Open AccessArticle

The Impact of Social Capital on Farmers’ Willingness to Adopt New Agricultural Technologies: Empirical Evidence from China

by Mingyang Han, Ruifeng Liu, Hengyun Ma, Kaiyang Zhong, Jian Wang and Yifan Xu

Agriculture 2022, 12(9), 1368; https://doi.org/10.3390/agriculture12091368 - 2 Sep 2022

Cited by 10 | Viewed by 4329

Abstract

Based on the microdata of 11,547 farmers from the China Labor Dynamics Survey (CLDS) database in 2017, an ordered multi-classification logistic model was constructed to empirically test the impact of social capital (i.e., social networks, social participation, and social trust) on farmers’ willingness [...] Read more.

Based on the microdata of 11,547 farmers from the China Labor Dynamics Survey (CLDS) database in 2017, an ordered multi-classification logistic model was constructed to empirically test the impact of social capital (i.e., social networks, social participation, and social trust) on farmers’ willingness to adopt agricultural technology. The moderating effect of demographic changes (i.e., the number of instances of hukou migration) on social capital and farmers’ willingness to adopt new agricultural technology was further investigated. The results show that the following: (1) Social trust has a significant positive impact on farmers’ willingness to adopt new agricultural technologies, while social participation has no significant impact on farmers’ willingness to adopt new technologies. (2) Social networks influence farmers’ technology adoption behavior differently, e.g., the scope of relatives’ wedding gifts has a significant and positive influence on farmers’ technology adoption behavior, while the scope of non-relatives’ wedding gifts has no significant influence on farmers’ technology adoption behavior. (3) Demographic change plays a moderating role in the impact of social capital on farmers’ willingness to adopt new agricultural technologies. In other words, the greater the number of instances of hukou migration, the less the promoting effect of social capital on farmers’ willingness to adopt agricultural technology. (4) In the eastern and central regions of China, social capital has a significant positive impact on farmers’ adoption of new agricultural technologies. In the western region of China, social capital has a significant negative impact on farmers’ adoption of new agricultural technology. In the northeast region of China, social capital has no significant impact on farmers’ adoption of new agricultural technologies. Social capital and population changes are important factors that affect farmers’ willingness to adopt new agricultural technologies. Therefore, attention should be paid to cultivating and promoting farmers’ social capital to improve farmers’ willingness to adopt new agricultural technologies. Full article

(This article belongs to the Special Issue Optimization of Resource Use for Productivity, Efficiency, and Sustainability in Agriculture)

► Show Figures

Figure 1

17 pages, 879 KiB

Open AccessArticle

The Role of Innovation Capacities in the Relationship between Green Human Resource Management and Competitive Advantage in the Saudi Food Industry: Does Gender of Entrepreneurs Really Matter?

by Hassane Gharbi, Abu Elnasr E. Sobaih, Nadir Aliane and Ayth Almubarak

Agriculture 2022, 12(6), 857; https://doi.org/10.3390/agriculture12060857 - 13 Jun 2022

Cited by 21 | Viewed by 4020

Abstract

Adopting environmentally friendly behavior has become more than a claim. Green human resource management seems to be the solution where innovation will be a strategic lever to lead the company, with green practices, to the possession of a decisive competitive advantage. The purpose [...] Read more.

Adopting environmentally friendly behavior has become more than a claim. Green human resource management seems to be the solution where innovation will be a strategic lever to lead the company, with green practices, to the possession of a decisive competitive advantage. The purpose of this research is to examine the mediating role of innovation capacities in the relationship between green human resource management and competitive advantage in the Saudi food industry. The research compares between males and females in this relationship. For this purpose, we have used a quantitative approach to conduct the research. Using a sample of 1114 female and male entrepreneurs, owner–managers of small and medium different food companies, operating in the Saudi territory, especially in the major cities, namely Riyadh, Medina, Makkah, Sharaqiyah, Tabuk, Al Qasim and Najran. We were able to make a gender comparison of the mediating role of innovation in the above relationship. The results of the structural equation modelling (SEM) via AMOS software version 23 showed a perfect mediation of the innovation capacities for female entrepreneurs, and partial mediation for male entrepreneurs in the relationship between green human resource management and competitive advantage. Following a focus group with ten female and male entrepreneurs, we were able to understand the reasons for the results we arrived at. The results of our research have numerous implications for both scholars and policymakers, especially in relation to the Saudi food industry. Full article

(This article belongs to the Special Issue Optimization of Resource Use for Productivity, Efficiency, and Sustainability in Agriculture)

► Show Figures

Figure 1

21 pages, 838 KiB

Open AccessArticle

The Impact of Agricultural Ecological Capital Investment on the Development of Green Circular Economy

by Fanqi Zou and Tinghui Li

Agriculture 2022, 12(4), 461; https://doi.org/10.3390/agriculture12040461 - 25 Mar 2022

Cited by 10 | Viewed by 2827

Abstract

Agricultural ecological capital investment aims to achieve the coordinated and sustainable development of agricultural and rural ecology, economy, and society through a series of inputs to a specific range of agricultural ecological resources, ecological environment, and ecological service capacity. Based on the macro [...] Read more.

Agricultural ecological capital investment aims to achieve the coordinated and sustainable development of agricultural and rural ecology, economy, and society through a series of inputs to a specific range of agricultural ecological resources, ecological environment, and ecological service capacity. Based on the macro data of 31 provinces (including autonomous regions and municipalities) in China, this paper uses coupling coordination and linear regression models to study the impact of agricultural ecological capital investment on green circular economy development. At the same time, considering the differences between active and passive investment, their impacts on green circular economy development are discussed, respectively. The empirical conclusions are as follows. First, agricultural ecological capital investment plays a significant role in promoting the development of the green circular economy on the whole, but the roles of active investment and passive investment are different. Second, agricultural ecological capital investment positively impacts the development of the green circular economy by increasing green inventions and promoting green credit index. Third, the impacts mechanisms of active and passive investment have on green circular economy are different. Fourth, the impact of agricultural ecological capital investment on the green circular economy is regionally heterogeneous. Full article

(This article belongs to the Special Issue Optimization of Resource Use for Productivity, Efficiency, and Sustainability in Agriculture)

► Show Figures

Figure 1

18 pages, 2911 KiB

Open AccessFeature PaperArticle

Maximization of Water Productivity and Yield of Two Iceberg Lettuce Cultivars in Hydroponic Farming System Using Magnetically Treated Saline Water

by Abdelaziz M. Okasha, Eman M. Eldib, Adel H. Elmetwalli, Aitazaz Ahsan Farooque, Zaher Mundher Yaseen and Salah Elsayed

Agriculture 2022, 12(1), 101; https://doi.org/10.3390/agriculture12010101 - 12 Jan 2022

Cited by 6 | Viewed by 4208

Abstract

Egypt has limited agricultural land, associated with the scarcity of irrigation water and rapid population growth. Hydroponic farming, seawater desalination and magnetic treatment are among the practical solutions for sustaining rapid population growth. In this regard, the main objective of the present research [...] Read more.

Egypt has limited agricultural land, associated with the scarcity of irrigation water and rapid population growth. Hydroponic farming, seawater desalination and magnetic treatment are among the practical solutions for sustaining rapid population growth. In this regard, the main objective of the present research study was to design and construct a hierarchical engineering unit as a hydroponic farming system (soilless) to produce an iceberg lettuce crop using magnetically treated saline water. The treatments included four types of irrigation water: common irrigation water (IW₁) with an electrical conductivity (EC) of 0.96 dS/m as a control treatment, magnetically treated common irrigation water (IW₂) with an EC of 0.96 dS/m, saline water (IW₃) with an EC of 4.56 dS/m and magnetically treated saline water (IW₄) with an EC of 4.56 dS/m; three depletion ratios (DR) of field capacity (DR₀ = 50%, DR₁ = 60% and DR₂ = 70%) and three slopes of hydroponic pipes (S₁ = 0.0%, S₂ = 0.025% and S₃ = 0.075%). The results revealed that seawater contributed 7.15% to produce iceberg lettuce in the hydroponic system. The geometric parameter, the slope of the pipes, influenced the obtained luminous intensity by an average increase of 21% and 71% for S₂ and S₃, respectively, compared with the zero slope (horizontal pipes). Magnetization of irrigation water increased the total soluble solids (TSS) and enhanced the fresh weight and water productivity of both iceberg lettuce varieties used. The maximum percentages of TSS were 5.20% and 5.10% for lemur and iceberg 077, respectively, for the combination IW₄DR₂S₂. The highest values of fresh weight and water productivity of 3.10 kg/m and 39.15 kg/m³ were recorded with the combinations IW₃DR₂S₃ and IW₄DR₁S₃, respectively, for lemur and iceberg lettuce. The percentages of these increases were 109.46% and 97.78%, respectively, when compared with the combination IW₁DR₀S₁. The highest values of iceberg lettuce 077 fresh weight and water productivity were 2.93 kg/m and 36.15 kg/m³, respectively, which were recorded with the combination IW₄DR₁S₃. The percentages of these increases were 112.32% and 120.56%, respectively, when compared with IW₁DR₀S₁ (the control treatment). Full article

(This article belongs to the Special Issue Optimization of Resource Use for Productivity, Efficiency, and Sustainability in Agriculture)

► Show Figures

Figure 1

19 pages, 1831 KiB

Open AccessArticle

The Influence of Dense Planting System on the Technical Efficiency of Saffron Production and Land Use Sustainability: Empirical Evidence from Gonabad County, Iran

by Mohammadreza Ramezani, Arash Dourandish, Tinoush Jamali Jaghdani and Milad Aminizadeh

Agriculture 2022, 12(1), 92; https://doi.org/10.3390/agriculture12010092 - 11 Jan 2022

Cited by 11 | Viewed by 3416

Abstract

The cultivation of saffron, which is one of the most expensive agricultural products in the world, is the main source of livelihood and economic wellbeing for the rural communities of Gonabad county in the eastern part of Iran. Nevertheless, farm monitoring in the [...] Read more.

The cultivation of saffron, which is one of the most expensive agricultural products in the world, is the main source of livelihood and economic wellbeing for the rural communities of Gonabad county in the eastern part of Iran. Nevertheless, farm monitoring in the region has shown that many saffron growers apply a high-density planting system for more profit. This practice results in the loss of land productivity after a six-year production cycle. As a consequence, farmers abandon the cultivated lands and move to plant saffron in available virgin lands. The purpose of this study is to analyse the technical efficiency of saffron farms and its determinants with an emphasis on the role of planting density. A survey was conducted in 2019, and a cross-sectional random sampling technique was used to select 110 saffron growers. We first assessed the technical efficiency of farms using a data envelopment analysis (DEA) model with input orientation. In the next step, efficiency scores were regressed on explanatory variables using OLS and bootstrapped truncated regression to identify efficiency related factors. We find that planting density negatively influenced technical efficiency, suggesting that it is necessary for saffron growers to be educated on the negative impacts of the dense planting system. Full article

(This article belongs to the Special Issue Optimization of Resource Use for Productivity, Efficiency, and Sustainability in Agriculture)

► Show Figures

Figure 1

13 pages, 367 KiB

Open AccessEditor’s ChoiceArticle

Technical Efficiency and Technological Gaps of Rice Production in Anambra State, Nigeria

by Chukwujekwu A. Obianefo, John N. Ng’ombe, Agness Mzyece, Blessing Masasi, Ngozi J. Obiekwe and Oluchi O. Anumudu

Agriculture 2021, 11(12), 1240; https://doi.org/10.3390/agriculture11121240 - 8 Dec 2021

Cited by 19 | Viewed by 5502

Abstract

The traditional approach to modeling productive efficiency assumes that technology is constant across the sample. However, farms in different regions may face different production opportunities, and the technologies they employ may differ due to environmental factors. Therefore, rather than using a traditional stochastic [...] Read more.

The traditional approach to modeling productive efficiency assumes that technology is constant across the sample. However, farms in different regions may face different production opportunities, and the technologies they employ may differ due to environmental factors. Therefore, rather than using a traditional stochastic frontier model in such cases, a stochastic meta-frontier (SMF) analysis is recommended to account for environmental factors between regions. It follows that differences in environmental factors between the upland and lowland regions in Anambra State, Nigeria, may result in farmers producing rice under different production and environmental conditions. Using the SMF model, this study, for the first time, determines technical efficiency (TE) and technological gap ratios (TGRs) of rice production from the upland and lowland regions in the Awka North Local Government Area of Anambra State, Nigeria. Our data are from a cross-section sample of randomly selected rice farmers. Results reveal that lowland regional rice producers are on average, significantly more technically efficient (91.7%) than their upland counterparts (84.2%). Additionally, mean TGRs associated with lowland rice farmers are higher (92.1%) than their corresponding upland producers (84.7%). While the upland rice producers are less technically efficient and further away from their full potential, results indicate that both sets of farmers do not use advanced technologies to match the industry’s potential. We suggest that agricultural policy should focus on providing regionally specific technologies, such as improved rice varieties that fit the working environment of the lagging area, to help rice farmers improve their resource efficiency and minimize technological gaps. Full article

(This article belongs to the Special Issue Optimization of Resource Use for Productivity, Efficiency, and Sustainability in Agriculture)

18 pages, 17419 KiB

Open AccessArticle

Ways to Improve the Productivity of Oasis Agriculture: Increasing the Scale of Household Production and Human Capital? A Case Study on Seed Maize Production in Northwest China

by Yao Wei, Fanglei Zhong, Xijing Luo, Penglong Wang and Xiaoyu Song

Agriculture 2021, 11(12), 1218; https://doi.org/10.3390/agriculture11121218 - 2 Dec 2021

Cited by 6 | Viewed by 3586

Abstract

Oasis agriculture in arid areas faces the constraints of scarce resources and a fragile ecological environment. Improving agricultural production efficiency is the key solution. However, there are few studies analyzing the relationship between farmers’ production efficiency and planting scale from a micro-empirical perspective. [...] Read more.

Oasis agriculture in arid areas faces the constraints of scarce resources and a fragile ecological environment. Improving agricultural production efficiency is the key solution. However, there are few studies analyzing the relationship between farmers’ production efficiency and planting scale from a micro-empirical perspective. Herein, we study the seed-producing corn growers in Zhangye city, and supplement special survey data with national input–output survey data. We use data envelopment analysis to measure agricultural production efficiency, and tobit regression to calculate the marginal effects of factors affecting production efficiency on farms of different scales. The results show that production efficiency is greater for large-scale farmers than for small-scale farmers. Duration of technical training, education time of laborers, planting income, and productive expenditure are significantly positively correlated with production efficiency. Average age of farmers and the amount of pesticide and fertilizer use are significantly negatively correlated with production efficiency. Off-farm activities improve the production efficiency of small-scale farmers but inhibit it for medium- and large-scale farmers. Differences exist in marginal impacts for different scales of farmland. We conclude that expanding the scale of family farms and optimizing human capital are effective for improving agricultural production efficiency in arid oasis areas. Full article

(This article belongs to the Special Issue Optimization of Resource Use for Productivity, Efficiency, and Sustainability in Agriculture)

► Show Figures

Figure 1

11 pages, 598 KiB

Open AccessArticle

Natural Resource Dependence of Communities around the Giant Panda Protected Land Based on Livelihood Capital

by Mengjie Liu, Qing Qin, Qingchi Zou, Yue Wang and Yali Wen

Agriculture 2021, 11(11), 1123; https://doi.org/10.3390/agriculture11111123 - 10 Nov 2021

Cited by 4 | Viewed by 2073

Abstract

As the flagship species of biodiversity protection, the giant panda has an umbrella protection function. China is committed to building a natural protection system with national parks as the main body to achieve sustainable development. In this paper, the sustainable livelihood analysis framework [...] Read more.

As the flagship species of biodiversity protection, the giant panda has an umbrella protection function. China is committed to building a natural protection system with national parks as the main body to achieve sustainable development. In this paper, the sustainable livelihood analysis framework is used to study the livelihood of farmers in the surrounding communities of the giant panda protected land. Based on the data obtained from the field survey, the evaluation index of the natural resource dependence of the community farmers is established, and then the measurement model is constructed to analyze the main factors affecting the natural resource dependence of the communities. The results showed that: (1) The food dependence of farmers around the giant panda protected area is the highest (46.32%), followed by energy dependence (37.67%), and income dependence is the lowest (27.91%). (2) In terms of regional characteristics, the natural resource dependence of farmers is the lowest in Minshan and Qionglai, followed by Daxiangling and Xiaoxiangling, and Liangshan is the highest. (3) Physical capital has no significant effect on the natural resource dependence. The influence of human capital, natural capital, and social capital on the natural resource dependence is significant. Full article

(This article belongs to the Special Issue Optimization of Resource Use for Productivity, Efficiency, and Sustainability in Agriculture)

► Show Figures

Figure 1

11 pages, 988 KiB

Open AccessArticle

Factors Influencing the Adoption of Agricultural Machinery by Chinese Maize Farmers

by Xiuhao Quan and Reiner Doluschitz

Agriculture 2021, 11(11), 1090; https://doi.org/10.3390/agriculture11111090 - 4 Nov 2021

Cited by 11 | Viewed by 8195

Abstract

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 [...] Read more.

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. Full article

(This article belongs to the Special Issue Optimization of Resource Use for Productivity, Efficiency, and Sustainability in Agriculture)

► Show Figures

Figure 1

27 pages, 1636 KiB

Open AccessArticle

Input Use Efficiency Management for Paddy Production Systems in India: A Machine Learning Approach

by Priya Brata Bhoi, Veeresh S. Wali, Deepak Kumar Swain, Kalpana Sharma, Akash Kumar Bhoi, Manlio Bacco and Paolo Barsocchi

Agriculture 2021, 11(9), 837; https://doi.org/10.3390/agriculture11090837 - 31 Aug 2021

Cited by 3 | Viewed by 5460

Abstract

This research illustrates the technical efficiency of the pan-India paddy cultivation status obtained through a stochastic frontier approach. The results suggest that the mean technical efficiency varies from 0.64 in Gujarat to 0.95 in Odisha. Inputs like human labor, mechanical labor, fertilizer, irrigation [...] Read more.

This research illustrates the technical efficiency of the pan-India paddy cultivation status obtained through a stochastic frontier approach. The results suggest that the mean technical efficiency varies from 0.64 in Gujarat to 0.95 in Odisha. Inputs like human labor, mechanical labor, fertilizer, irrigation and insecticide were found to determine the yield in paddy cultivation across India (except for Chhattisgarh). Inefficiency in the paddy production in Punjab, Bihar, West Bengal, Andhra Pradesh, Tamil Nadu, Kerala, Assam, Gujarat and Odisha in 2016–2017 was caused by technical inefficiency due to poor input management, as suggested by the significant σ²U and σ²v values of the stochastic frontier model. In addition, most of the farm groups in the study operated in the high-efficiency group (80–90% technical efficiency). No specific pattern of input use can be visualized through descriptive measures to give any specific policy implication. Thus, machine learning algorithms based on the input parameters were tested on the data in order to predict the farmers’ efficiency class for individual states. The highest mean accuracy of 0.80 for the models of all of the states was achieved in random forest models. Among the various states of India, the best random forest prediction model based on accuracy was fitted to the input data of Bihar (0.91), followed by Uttar Pradesh (0.89), Andhra Pradesh (0.88), Assam (0.88) and West Bengal (0.86). Thus, the study provides a technique for the classification and prediction of a farmer’s efficiency group from the levels of input use in paddy cultivation for each state in the study. The study uses the DES input dataset to classify and predict the efficiency group of the farmer, as other machine learning models in agriculture have used mostly satellite, spectral imaging and soil property data to detect disease, weeds and crops. Full article

(This article belongs to the Special Issue Optimization of Resource Use for Productivity, Efficiency, and Sustainability in Agriculture)

► Show Figures

Figure 1

13 pages, 705 KiB

Open AccessArticle

Improved Rice Technology Adoption: The Role of Spatially-Dependent Risk Preference

by Omotuyole Isiaka Ambali, Francisco Jose Areal and Nikolaos Georgantzis

Agriculture 2021, 11(8), 691; https://doi.org/10.3390/agriculture11080691 - 22 Jul 2021

Cited by 13 | Viewed by 12864

Abstract

This study analyses farmers’ adoption of improved rice technology, taking into account farmers’ risk preferences; the unobserved spatial heterogeneity associated with farmers’ risk preferences; farmers’ household and farm characteristics; farm locations, farmers’ access to information, and their perceptions on the rice improved varieties [...] Read more.

This study analyses farmers’ adoption of improved rice technology, taking into account farmers’ risk preferences; the unobserved spatial heterogeneity associated with farmers’ risk preferences; farmers’ household and farm characteristics; farm locations, farmers’ access to information, and their perceptions on the rice improved varieties (i.e., high yield varieties, HYV). The study used data obtained from field experiments and a survey conducted in 2016 in Nigeria. An instrumental-variable probit model was estimated to account for potential endogenous farmers’ risk preference in the adoption decision model. Results show that risk averse (risk avoidant) farmers are less likely to adopt HYV, with the spatial lags of farmers’ risk attitudes found to be a good instrument for spatially unobserved variables (e.g., environmental and climatic factors). We conclude that studies supporting policy action aiming at the diffusion of improved rice varieties need to collect information, if possible, on farmers’ risk attitudes, local environmental and climatic conditions (e.g., climatic, topographic, soil quality, pest incidence) in order to ease the design and evaluation of policy actions on the adoption of improved agricultural technology. Full article

(This article belongs to the Special Issue Optimization of Resource Use for Productivity, Efficiency, and Sustainability in Agriculture)

► Show Figures

Figure 1

14 pages, 1713 KiB

Open AccessArticle

Fragmentation Reduction through Farmer-Led Land Transfer and Consolidation? Experiences of Rice Farmers in Wuhan Metropolitan Area, China

by Chaozheng Zhang and Danling Chen

Agriculture 2021, 11(7), 631; https://doi.org/10.3390/agriculture11070631 - 6 Jul 2021

Cited by 9 | Viewed by 3394

Abstract

Land fragmentation has become a serious obstacle to agricultural production, and land transfer and consolidation are traditionally emphasized as the two most effective solutions to this quandary. To identify the extent of land fragmentation accurately and systematically, this study selected the number of [...] Read more.

Land fragmentation has become a serious obstacle to agricultural production, and land transfer and consolidation are traditionally emphasized as the two most effective solutions to this quandary. To identify the extent of land fragmentation accurately and systematically, this study selected the number of plots, the average size of plots, and the average distance between plots to calculate the land fragmentation index (LFI). Taking the Wuhan metropolitan area as a case study, this study examined the effectiveness of farmer-led land transfer and consolidation on land fragmentation. The main results are as follows: (a) most of the transferred plots and contracted plots were not spatially adjacent, suggesting that the tenants could not merge and consolidate both plots; (b) land transfer caused the LFI to increase by 2.85%, suggesting that land transfer had intensified the degree of land fragmentation to some extent; (c) if the transferred and contracted plots were non-adjacent or adjacent but unmerged and unconsolidated, then the LFI might increase or decrease; (d) if the transferred and contracted plots were spatially adjacent, merged, and consolidated, then the LFI decreased significantly. Full article

(This article belongs to the Special Issue Optimization of Resource Use for Productivity, Efficiency, and Sustainability in Agriculture)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Optimization of Resource Use for Productivity, Efficiency, and Sustainability in Agriculture

Share This Special Issue

Special Issue Editors

Special Issue Information

Keywords

Benefits of Publishing in a Special Issue

Published Papers (17 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI