Asian journal of agriculture and food science CiteScore 2024-2025 - ResearchHelpDesk - Asian Journal of Agricultural and Food Sciences (AJAFS) is a bright ground for scientists and researchers dealing with agriculture, and food science. The Journal stresses on academic excellence, research inflexibility, data-information-knowledge distribution, and collaborative scholarly efforts. The Journal promotes abstract, experimental and methodological research on agriculture and food sciences at farm, community, regional, national and international levels. Journal of Agricultural and Food Sciences preserves prompt publication of manuscripts that meet the broad-spectrum criteria of scientific excellence. Areas of interest include, but are not limited to: Agricultural Engineering and Technology Agriculture and Environment Agriculture – Production Agriculture – Utilization Agriculture History Agricultural economics Agricultural engineering Agronomy Animal Sciences Antibody Production Aquaculture Biochemistry Biomass and Bio-energy Biotechnology Crop Science Dairy Science Entomology Environmental science Fermentation Technology Fish and Fisheries Food and Consumer Issues Food Chemistry Food Culture Food Engineering and Technology Food Health and Nutrition Food History Food Industry Development Food marketing Food manufacturing techniques Food Policy and Practices Food Processing Food Safety Forestry Freshwater Science Genomics Horticulture Institutional and Policy Issues Irrigation Materials and Processing Molecular Biology Morphology Organic Agriculture Pesticide Science Physiology Plant Sciences Post-Harvest Biology Poultry Science Primary production-related food science Rehabilitation Rural Economy and Development Seed Science Research Sensory and Consumer Sciences Soil Science Stored Products Sustainability Issues Tree Fruit Production Veterinary Virology Viticulture Water Resources Weed Biology

Journal of integrative agriculture Acceptance Rate - ResearchHelpDesk - Journal of Integrative Agriculture publishes manuscripts in the categories of Commentary, Review, Research Article, Letter and Short Communication, focusing on the core subjects: Crop Science, Horticulture, Plant Protection, Animal Science and Veterinary Medicine, Agro-Ecosystem and Environment, Food Science, Agricultural Economics and Management, Agricultural Information Science. JIA seeks to publish those papers that are influential and will significantly advance scientific understanding in agriculture fields worldwide. JIA publishes manuscripts in the five categories focusing on the five core subjects listed below. Core Subjects Crop Science Crop genetics, breeding, germplasm resources Crop cultivation, tillage, physiology Plant Protection Plant pathology Agricultural insect Pesticide and weed science Horticulture Horticultural crop (major vegetable and fruit crops) genetics, breeding, germplasm resources Horticultural crop (major vegetable and fruit crops) cultivation, physiology, biochemistry Animal Science & Veterinary Medicine Animal genetics and breeding, nutrition and metabolism, reproduction,forage science Basic veterinary, preventive veterinary, clinical veterinary Agro-Ecosystem & Environment Plant nutrition Soil & fertilization Soil microorganism Irrigation Agricultural remote sensing Food Science Food processing Food nutrition Food quality and safety Food biotechnology Agricultural Economics and Management Agricultural economics Food economics Environmental economics Agricultural policy Farm management JIA has been indexed in the following databases: SCI Scopus CABI Abstarct Journal (AJ) Zoological Record (ZR) AGRICultural OnLine Access (AGRICOLA) Food Science and Technology Abstracts (FSTA) AGRIS Database of Food and Agriculture Organization (FAO) Chinese Science and Technology Paper Citation Database (CSTPCD) CNKI Wanfang Data Chinese Science Citation Database (CSCD)

In this dataset we present core data of an integrative evaluation framework for assessing the environmental, social, and economic sustainability of urban agriculture. The multi-criteria analysis is conducted by an Analytic Hierarchy Process and a participatory approach. The data integrate the selection and weighting of sub-criteria based on two online surveys:

1) Survey 1: The selection of suitable sub-criteria for assessing the sustainability of urban agriculture was done by European scientific experts.

2) Survey 2: The weighting of the selected sub-criteria was done on the example of vertical farming and community supported agriculture. Therefore, we involved stakeholders representing key actors for the implementation of urban agriculture: city administrations and non-governmental organizations (NGOs) of ten German case study cities, practitioners and technical-scientific experts.

List of data and content

1) Survey_1 (*.zip):

• Survey_1_Criteria_Selection_English: Online survey in English (*.pdf)
• Survey_1_Information_Sub-criteria_English: Information about the sub-criteria provided in the survey (in English) (*.pdf)
• Survey_1_Groups: Results of the statistical analyses (U-tests and Kruscal-Wallis) to detect group-specific differences (e.g. gender, different length or degree of experience with urban agriculture, scientific focus, target group, expertise); the tests were conducted with IBM SPSS Statistics 25 (*.xlsx)

2) Survey_2 (*.zip):

• Survey_2_AHP_City_Administrations_German: Online survey for city administrations in German (*.pdf)
• Survey_2_AHP_Practitioners_German: Online survey for practitioners and technical-scientific experts in German (*.pdf)
• Survey_2_AHP_NGOs_German: Online survey for NGOs in German (*.pdf)
• Survey_2_Information_Sub-Criteria_German: Information about the sub-criteria provided in the survey (in German) (*.pdf)
• Survey_2_Groups: Results of the statistical analyses (U-tests and Kruscal-Wallis) to detect group-specific differences (e.g. gender, different length or degree of experience with urban agriculture, scientific focus, target group, expertise); the tests were conducted with IBM SPSS Statistics 25 (*.xlsx)
• rdata_CA_AHP_edible_Cities_2022-03-18_10-28: Results of the survey for city administrations (*.csv)
• rdata_NGO_AHP_edible_Cities_2022-03-18_10-40: Results of the survey for NGOs (*.csv)
• rdata_PE_AHP_edible_Cities_2022-03-18_10-41: Results of the survey for practitioners and technical-scientific experts (*.csv)
• rdata_all_AHP_edible_Cities_2022-03-18_09-53: Total results of the survey

Data acquisition and processing

The methods are described in this linked publication:

John, H., & Artmann, M. (2024). Introducing an integrative evaluation framework for assessing the sustainability of different types of urban agriculture. International Journal of Urban Sustainable Development, 16 (1), 35-52. doi: 10.1080/19463138.2024.2317795

The methodology of the performed analytic hierarchy process (AHP) is published in a separate repository on GitHub including a paper that systematically explains the AHP by means of code examples, starting with the raw data, through their adaptation to the software functions of the ahpsurvey R-package, and finally, execution of the AHP up to the visualization of the results.

Acknowledgments

The authors thank Mabel Killinger and Marie Herzig for their help in stakeholder identification as well as all experts and stakeholders for their participation in the two online surveys and their helpful comments. Data processing and analysis by means of an Analytic Hierarchy Process in R would not have been possible without the help of Björn Kasper.

Asian journal of agriculture and food science Abstract & Indexing - ResearchHelpDesk - Asian Journal of Agricultural and Food Sciences (AJAFS) is a bright ground for scientists and researchers dealing with agriculture, and food science. The Journal stresses on academic excellence, research inflexibility, data-information-knowledge distribution, and collaborative scholarly efforts. The Journal promotes abstract, experimental and methodological research on agriculture and food sciences at farm, community, regional, national and international levels. Journal of Agricultural and Food Sciences preserves prompt publication of manuscripts that meet the broad-spectrum criteria of scientific excellence. Areas of interest include, but are not limited to: Agricultural Engineering and Technology Agriculture and Environment Agriculture – Production Agriculture – Utilization Agriculture History Agricultural economics Agricultural engineering Agronomy Animal Sciences Antibody Production Aquaculture Biochemistry Biomass and Bio-energy Biotechnology Crop Science Dairy Science Entomology Environmental science Fermentation Technology Fish and Fisheries Food and Consumer Issues Food Chemistry Food Culture Food Engineering and Technology Food Health and Nutrition Food History Food Industry Development Food marketing Food manufacturing techniques Food Policy and Practices Food Processing Food Safety Forestry Freshwater Science Genomics Horticulture Institutional and Policy Issues Irrigation Materials and Processing Molecular Biology Morphology Organic Agriculture Pesticide Science Physiology Plant Sciences Post-Harvest Biology Poultry Science Primary production-related food science Rehabilitation Rural Economy and Development Seed Science Research Sensory and Consumer Sciences Soil Science Stored Products Sustainability Issues Tree Fruit Production Veterinary Virology Viticulture Water Resources Weed Biology

BackgroundAt present, agricultural robots are produced in large quantities and used in agricultural planting, and the traditional agricultural model is gradually shifting to rely on the Internet of Things and sensors to accurately detect crop growth information. The scientific and rational design of agricultural robots plays a huge role in planting and production efficiency, however, the factors affecting their design are complex and ambiguous, so it is necessary to use a rational evaluation system to make a preferential decision among multiple design options.PurposesIn order to reduce the subjectivity and blindness of program selection in the process of agricultural robot design, make the decision more objective and reasonable, and thus enhance the practicality and scientificity of the program, a new comprehensive evaluation method based on user requirements is proposed.MethodsFirst, after researching and interviewing users and farming operations, obtaining raw information on requirements, using the Kano model to classify the requirements and establishing an evaluation index system. Secondly, the combination of hierarchical analysis(AHP) and entropy weighting method is used to assign weights to the evaluation index system, calculate the weight value and importance ranking of each index, and carry out various program designs based on the ranking. Finally, the VIKOR method was applied to evaluate and rank the design solutions.ResultsThe new evaluation method can better complete the preferential decision of the agricultural robot design scheme and get a more perfect design scheme, which reduces the influence of human subjective thinking in the decision-making process.ConclusionsThe method not only corrects the traditional evaluation method, but also effectively improves the accuracy and comprehensiveness of the design evaluation process. It also provides a reference for designers to preferably select design solutions and promotes the development of small mobile machines in the context of smart agriculture.

DATASET: https://www.muratkoklu.com/datasets/

1: KOKLU, M., CINAR, I. and TASPINAR, Y. S. (2021). Classification of rice varieties with deep learning methods. Computers and Electronics in Agriculture, 187, 106285. DOI: https://doi.org/10.1016/j.compag.2021.106285

2: CINAR, I. and KOKLU, M. (2021). Determination of Effective and Specific Physical Features of Rice Varieties by Computer Vision In Exterior Quality Inspection. Selcuk Journal of Agriculture and Food Sciences, 35(3), 229-243. DOI: https://doi.org/10.15316/SJAFS.2021.252

3: CINAR, I. and KOKLU, M. (2022). Identification of Rice Varieties Using Machine Learning Algorithms. Journal of Agricultural Sciences, 28 (2), 307-325. DOI: https://doi.org/10.15832/ankutbd.862482

4: CINAR, I. and KOKLU, M. (2019). Classification of Rice Varieties Using Artificial Intelligence Methods. International Journal of Intelligent Systems and Applications in Engineering, 7(3), 188-194. DOI: https://doi.org/10.18201/ijisae.2019355381

Relevant Papers / Citation Requests / Acknowledgements: Cinar, I. and Koklu, M. (2019). Classification of Rice Varieties Using Artificial Intelligence Methods. International Journal of Intelligent Systems and Applications in Engineering, vol.7, no.3 (Sep. 2019), pp.188-194. https://doi.org/10.18201/ijisae.2019355381.

Data Set Name: Rice Dataset (Commeo and Osmancik) Abstract: A total of 3810 rice grain's images were taken for the two species (Cammeo and Osmancik), processed and feature inferences were made. 7 morphological features were obtained for each grain of rice.

Source: Ilkay CINAR Graduate School of Natural and Applied Sciences, Selcuk University, Konya, TURKEY ilkay_cinar@hotmail.com

Murat KOKLU Faculty of Technology, Selcuk University, Konya, TURKEY. mkoklu@selcuk.edu.tr

DATASET: https://www.muratkoklu.com/datasets/

Relevant Information: In order to classify the rice varieties (Cammeo and Osmancik) used, preliminary processing was applied to the pictures obtained with computer vision system and a total of 3810 rice grains were obtained. Furthermore, 7 morphological features have been inferred for each grain. A data set has been created for the properties obtained.

Attribute Information: 1. Area: Returns the number of pixels within the boundaries of the rice grain. 2. Perimeter: Calculates the circumference by calculating the distance between pixels around the boundaries of the rice grain. 3. Major Axis Length: The longest line that can be drawn on the rice grain, i.e. the main axis distance, gives. 4. Minor Axis Length: The shortest line that can be drawn on the rice grain, i.e. the small axis distance, gives. 5. Eccentricity: It measures how round the ellipse, which has the same moments as the rice grain, is. 6. Convex Area: Returns the pixel count of the smallest convex shell of the region formed by the rice grain. 7. Extent: Returns the ratio of the region formed by the rice grain to the bounding box pixels 8. Class: Commeo and Osmancik.

Relevant Papers / Citation Requests / Acknowledgements: Cinar, I. and Koklu, M. (2019). Classification of Rice Varieties Using Artificial Intelligence Methods. International Journal of Intelligent Systems and Applications in Engineering, vol.7, no.3 (Sep. 2019), pp.188-194. https://doi.org/10.18201/ijisae.2019355381.

Journal of integrative agriculture Impact Factor 2024-2025 - ResearchHelpDesk - Journal of Integrative Agriculture publishes manuscripts in the categories of Commentary, Review, Research Article, Letter and Short Communication, focusing on the core subjects: Crop Science, Horticulture, Plant Protection, Animal Science and Veterinary Medicine, Agro-Ecosystem and Environment, Food Science, Agricultural Economics and Management, Agricultural Information Science. JIA seeks to publish those papers that are influential and will significantly advance scientific understanding in agriculture fields worldwide. JIA publishes manuscripts in the five categories focusing on the five core subjects listed below. Core Subjects Crop Science Crop genetics, breeding, germplasm resources Crop cultivation, tillage, physiology Plant Protection Plant pathology Agricultural insect Pesticide and weed science Horticulture Horticultural crop (major vegetable and fruit crops) genetics, breeding, germplasm resources Horticultural crop (major vegetable and fruit crops) cultivation, physiology, biochemistry Animal Science & Veterinary Medicine Animal genetics and breeding, nutrition and metabolism, reproduction,forage science Basic veterinary, preventive veterinary, clinical veterinary Agro-Ecosystem & Environment Plant nutrition Soil & fertilization Soil microorganism Irrigation Agricultural remote sensing Food Science Food processing Food nutrition Food quality and safety Food biotechnology Agricultural Economics and Management Agricultural economics Food economics Environmental economics Agricultural policy Farm management JIA has been indexed in the following databases: SCI Scopus CABI Abstarct Journal (AJ) Zoological Record (ZR) AGRICultural OnLine Access (AGRICOLA) Food Science and Technology Abstracts (FSTA) AGRIS Database of Food and Agriculture Organization (FAO) Chinese Science and Technology Paper Citation Database (CSTPCD) CNKI Wanfang Data Chinese Science Citation Database (CSCD)

BackgroundAt present, agricultural robots are produced in large quantities and used in agricultural planting, and the traditional agricultural model is gradually shifting to rely on the Internet of Things and sensors to accurately detect crop growth information. The scientific and rational design of agricultural robots plays a huge role in planting and production efficiency, however, the factors affecting their design are complex and ambiguous, so it is necessary to use a rational evaluation system to make a preferential decision among multiple design options.PurposesIn order to reduce the subjectivity and blindness of program selection in the process of agricultural robot design, make the decision more objective and reasonable, and thus enhance the practicality and scientificity of the program, a new comprehensive evaluation method based on user requirements is proposed.MethodsFirst, after researching and interviewing users and farming operations, obtaining raw information on requirements, using the Kano model to classify the requirements and establishing an evaluation index system. Secondly, the combination of hierarchical analysis(AHP) and entropy weighting method is used to assign weights to the evaluation index system, calculate the weight value and importance ranking of each index, and carry out various program designs based on the ranking. Finally, the VIKOR method was applied to evaluate and rank the design solutions.ResultsThe new evaluation method can better complete the preferential decision of the agricultural robot design scheme and get a more perfect design scheme, which reduces the influence of human subjective thinking in the decision-making process.ConclusionsThe method not only corrects the traditional evaluation method, but also effectively improves the accuracy and comprehensiveness of the design evaluation process. It also provides a reference for designers to preferably select design solutions and promotes the development of small mobile machines in the context of smart agriculture.

Journal of integrative agriculture Abstract & Indexing - ResearchHelpDesk - Journal of Integrative Agriculture publishes manuscripts in the categories of Commentary, Review, Research Article, Letter and Short Communication, focusing on the core subjects: Crop Science, Horticulture, Plant Protection, Animal Science and Veterinary Medicine, Agro-Ecosystem and Environment, Food Science, Agricultural Economics and Management, Agricultural Information Science. JIA seeks to publish those papers that are influential and will significantly advance scientific understanding in agriculture fields worldwide. JIA publishes manuscripts in the five categories focusing on the five core subjects listed below. Core Subjects Crop Science Crop genetics, breeding, germplasm resources Crop cultivation, tillage, physiology Plant Protection Plant pathology Agricultural insect Pesticide and weed science Horticulture Horticultural crop (major vegetable and fruit crops) genetics, breeding, germplasm resources Horticultural crop (major vegetable and fruit crops) cultivation, physiology, biochemistry Animal Science & Veterinary Medicine Animal genetics and breeding, nutrition and metabolism, reproduction,forage science Basic veterinary, preventive veterinary, clinical veterinary Agro-Ecosystem & Environment Plant nutrition Soil & fertilization Soil microorganism Irrigation Agricultural remote sensing Food Science Food processing Food nutrition Food quality and safety Food biotechnology Agricultural Economics and Management Agricultural economics Food economics Environmental economics Agricultural policy Farm management JIA has been indexed in the following databases: SCI Scopus CABI Abstarct Journal (AJ) Zoological Record (ZR) AGRICultural OnLine Access (AGRICOLA) Food Science and Technology Abstracts (FSTA) AGRIS Database of Food and Agriculture Organization (FAO) Chinese Science and Technology Paper Citation Database (CSTPCD) CNKI Wanfang Data Chinese Science Citation Database (CSCD)

BackgroundAt present, agricultural robots are produced in large quantities and used in agricultural planting, and the traditional agricultural model is gradually shifting to rely on the Internet of Things and sensors to accurately detect crop growth information. The scientific and rational design of agricultural robots plays a huge role in planting and production efficiency, however, the factors affecting their design are complex and ambiguous, so it is necessary to use a rational evaluation system to make a preferential decision among multiple design options.PurposesIn order to reduce the subjectivity and blindness of program selection in the process of agricultural robot design, make the decision more objective and reasonable, and thus enhance the practicality and scientificity of the program, a new comprehensive evaluation method based on user requirements is proposed.MethodsFirst, after researching and interviewing users and farming operations, obtaining raw information on requirements, using the Kano model to classify the requirements and establishing an evaluation index system. Secondly, the combination of hierarchical analysis(AHP) and entropy weighting method is used to assign weights to the evaluation index system, calculate the weight value and importance ranking of each index, and carry out various program designs based on the ranking. Finally, the VIKOR method was applied to evaluate and rank the design solutions.ResultsThe new evaluation method can better complete the preferential decision of the agricultural robot design scheme and get a more perfect design scheme, which reduces the influence of human subjective thinking in the decision-making process.ConclusionsThe method not only corrects the traditional evaluation method, but also effectively improves the accuracy and comprehensiveness of the design evaluation process. It also provides a reference for designers to preferably select design solutions and promotes the development of small mobile machines in the context of smart agriculture.

Journal of integrative agriculture CiteScore 2024-2025 - ResearchHelpDesk - Journal of Integrative Agriculture publishes manuscripts in the categories of Commentary, Review, Research Article, Letter and Short Communication, focusing on the core subjects: Crop Science, Horticulture, Plant Protection, Animal Science and Veterinary Medicine, Agro-Ecosystem and Environment, Food Science, Agricultural Economics and Management, Agricultural Information Science. JIA seeks to publish those papers that are influential and will significantly advance scientific understanding in agriculture fields worldwide. JIA publishes manuscripts in the five categories focusing on the five core subjects listed below. Core Subjects Crop Science Crop genetics, breeding, germplasm resources Crop cultivation, tillage, physiology Plant Protection Plant pathology Agricultural insect Pesticide and weed science Horticulture Horticultural crop (major vegetable and fruit crops) genetics, breeding, germplasm resources Horticultural crop (major vegetable and fruit crops) cultivation, physiology, biochemistry Animal Science & Veterinary Medicine Animal genetics and breeding, nutrition and metabolism, reproduction,forage science Basic veterinary, preventive veterinary, clinical veterinary Agro-Ecosystem & Environment Plant nutrition Soil & fertilization Soil microorganism Irrigation Agricultural remote sensing Food Science Food processing Food nutrition Food quality and safety Food biotechnology Agricultural Economics and Management Agricultural economics Food economics Environmental economics Agricultural policy Farm management JIA has been indexed in the following databases: SCI Scopus CABI Abstarct Journal (AJ) Zoological Record (ZR) AGRICultural OnLine Access (AGRICOLA) Food Science and Technology Abstracts (FSTA) AGRIS Database of Food and Agriculture Organization (FAO) Chinese Science and Technology Paper Citation Database (CSTPCD) CNKI Wanfang Data Chinese Science Citation Database (CSCD)

BackgroundAt present, agricultural robots are produced in large quantities and used in agricultural planting, and the traditional agricultural model is gradually shifting to rely on the Internet of Things and sensors to accurately detect crop growth information. The scientific and rational design of agricultural robots plays a huge role in planting and production efficiency, however, the factors affecting their design are complex and ambiguous, so it is necessary to use a rational evaluation system to make a preferential decision among multiple design options.PurposesIn order to reduce the subjectivity and blindness of program selection in the process of agricultural robot design, make the decision more objective and reasonable, and thus enhance the practicality and scientificity of the program, a new comprehensive evaluation method based on user requirements is proposed.MethodsFirst, after researching and interviewing users and farming operations, obtaining raw information on requirements, using the Kano model to classify the requirements and establishing an evaluation index system. Secondly, the combination of hierarchical analysis(AHP) and entropy weighting method is used to assign weights to the evaluation index system, calculate the weight value and importance ranking of each index, and carry out various program designs based on the ranking. Finally, the VIKOR method was applied to evaluate and rank the design solutions.ResultsThe new evaluation method can better complete the preferential decision of the agricultural robot design scheme and get a more perfect design scheme, which reduces the influence of human subjective thinking in the decision-making process.ConclusionsThe method not only corrects the traditional evaluation method, but also effectively improves the accuracy and comprehensiveness of the design evaluation process. It also provides a reference for designers to preferably select design solutions and promotes the development of small mobile machines in the context of smart agriculture.

BackgroundAt present, agricultural robots are produced in large quantities and used in agricultural planting, and the traditional agricultural model is gradually shifting to rely on the Internet of Things and sensors to accurately detect crop growth information. The scientific and rational design of agricultural robots plays a huge role in planting and production efficiency, however, the factors affecting their design are complex and ambiguous, so it is necessary to use a rational evaluation system to make a preferential decision among multiple design options.PurposesIn order to reduce the subjectivity and blindness of program selection in the process of agricultural robot design, make the decision more objective and reasonable, and thus enhance the practicality and scientificity of the program, a new comprehensive evaluation method based on user requirements is proposed.MethodsFirst, after researching and interviewing users and farming operations, obtaining raw information on requirements, using the Kano model to classify the requirements and establishing an evaluation index system. Secondly, the combination of hierarchical analysis(AHP) and entropy weighting method is used to assign weights to the evaluation index system, calculate the weight value and importance ranking of each index, and carry out various program designs based on the ranking. Finally, the VIKOR method was applied to evaluate and rank the design solutions.ResultsThe new evaluation method can better complete the preferential decision of the agricultural robot design scheme and get a more perfect design scheme, which reduces the influence of human subjective thinking in the decision-making process.ConclusionsThe method not only corrects the traditional evaluation method, but also effectively improves the accuracy and comprehensiveness of the design evaluation process. It also provides a reference for designers to preferably select design solutions and promotes the development of small mobile machines in the context of smart agriculture.

Soy is the main product of Brazilian agriculture and the fourth most cultivated bean globally. Since soy cultivation tends to increase and due to this large market, the guarantee of product quality is an indispensable factor for enterprises to stay competitive. Industries perform vigor tests to acquire information and evaluate the quality of soy planting. The tetrazolium test, for example, provides information about moisture damage, bedbugs, or mechanical damage. However, the verification of the damage reason and its severity are done by an analyst, one by one. Since this is massive and exhausting work, it is susceptible to mistakes. Proposals involving different supervised learning approaches, including active learning strategies, have already been used, and have brought significant results. Therefore, this paper analyzes the performance of non-supervised techniques for classifying soybeans. An extensive experimental evaluation was performed, considering (9) different clustering algorithms (partitional, hierarchical, and density-based) applied to 5 image datasets of soybean seeds submitted to the tetrazolium test, including different damages and/or their levels. To describe those images, we considered 18 extractors of traditional features. We also considered four metrics (accuracy, FOWLKES, DAVIES, and CALINSKI) and two-dimensionality reduction techniques (principal component analysis and t-distributed stochastic neighbor embedding) for validation. Results show that this paper presents essential contributions since it makes it possible to identify descriptors and clustering algorithms that shall be used as preprocessing in other learning processes, accelerating and improving the classification process of key agricultural problems.

✅ Journal of integrative agriculture ISSN - ResearchHelpDesk - Journal of Integrative Agriculture publishes manuscripts in the categories of Commentary, Review, Research Article, Letter and Short Communication, focusing on the core subjects: Crop Science, Horticulture, Plant Protection, Animal Science and Veterinary Medicine, Agro-Ecosystem and Environment, Food Science, Agricultural Economics and Management, Agricultural Information Science. JIA seeks to publish those papers that are influential and will significantly advance scientific understanding in agriculture fields worldwide. JIA publishes manuscripts in the five categories focusing on the five core subjects listed below. Core Subjects Crop Science Crop genetics, breeding, germplasm resources Crop cultivation, tillage, physiology Plant Protection Plant pathology Agricultural insect Pesticide and weed science Horticulture Horticultural crop (major vegetable and fruit crops) genetics, breeding, germplasm resources Horticultural crop (major vegetable and fruit crops) cultivation, physiology, biochemistry Animal Science & Veterinary Medicine Animal genetics and breeding, nutrition and metabolism, reproduction,forage science Basic veterinary, preventive veterinary, clinical veterinary Agro-Ecosystem & Environment Plant nutrition Soil & fertilization Soil microorganism Irrigation Agricultural remote sensing Food Science Food processing Food nutrition Food quality and safety Food biotechnology Agricultural Economics and Management Agricultural economics Food economics Environmental economics Agricultural policy Farm management JIA has been indexed in the following databases: SCI Scopus CABI Abstarct Journal (AJ) Zoological Record (ZR) AGRICultural OnLine Access (AGRICOLA) Food Science and Technology Abstracts (FSTA) AGRIS Database of Food and Agriculture Organization (FAO) Chinese Science and Technology Paper Citation Database (CSTPCD) CNKI Wanfang Data Chinese Science Citation Database (CSCD)

Journal of integrative agriculture Publication fee - ResearchHelpDesk - Journal of Integrative Agriculture publishes manuscripts in the categories of Commentary, Review, Research Article, Letter and Short Communication, focusing on the core subjects: Crop Science, Horticulture, Plant Protection, Animal Science and Veterinary Medicine, Agro-Ecosystem and Environment, Food Science, Agricultural Economics and Management, Agricultural Information Science. JIA seeks to publish those papers that are influential and will significantly advance scientific understanding in agriculture fields worldwide. JIA publishes manuscripts in the five categories focusing on the five core subjects listed below. Core Subjects Crop Science Crop genetics, breeding, germplasm resources Crop cultivation, tillage, physiology Plant Protection Plant pathology Agricultural insect Pesticide and weed science Horticulture Horticultural crop (major vegetable and fruit crops) genetics, breeding, germplasm resources Horticultural crop (major vegetable and fruit crops) cultivation, physiology, biochemistry Animal Science & Veterinary Medicine Animal genetics and breeding, nutrition and metabolism, reproduction,forage science Basic veterinary, preventive veterinary, clinical veterinary Agro-Ecosystem & Environment Plant nutrition Soil & fertilization Soil microorganism Irrigation Agricultural remote sensing Food Science Food processing Food nutrition Food quality and safety Food biotechnology Agricultural Economics and Management Agricultural economics Food economics Environmental economics Agricultural policy Farm management JIA has been indexed in the following databases: SCI Scopus CABI Abstarct Journal (AJ) Zoological Record (ZR) AGRICultural OnLine Access (AGRICOLA) Food Science and Technology Abstracts (FSTA) AGRIS Database of Food and Agriculture Organization (FAO) Chinese Science and Technology Paper Citation Database (CSTPCD) CNKI Wanfang Data Chinese Science Citation Database (CSCD)

Rural women constitute a substantial portion of the global agricultural workforce yet remain marginalized in access to credit, agricultural inputs, and information. This persistent exclusion not only constrains their productivity but also undermines efforts to build resilient and sustainable food systems. As climate variability increasingly threatens smallholder farming, climate-smart agriculture (CSA) has gained prominence as a viable approach to enhance agricultural sustainability, productivity, and adaptation. However, adoption of CSA among smallholder women farmers remains patchy and elusive. In response, development actors have promoted village savings and loan associations (VSLAs) to enhance women’s access to financial services. Yet, whether—and through which mechanisms—women participation (WP) in VSLAs influences CSA adoption remains insufficiently understood. To address this knowledge gap, the study investigates the pathways through which WP in VSLAs influences CSA adoption, considering the mediating role of agricultural informatization (AgI). A cross-sectional, mixed-methods design was employed, using a multistage random sampling technique to survey 436 smallholder women farmers in rural Zambia. Quantitative data were collected through a pre-tested structured questionnaire, supplemented by qualitative data from key informant interviews. Mediation analysis, using the Sobel test and bias-corrected bootstrapping, was applied to estimate pathways, while propensity score matching (PSM) was used to check the robustness of results. Findings reveal that WP in VSLAs significantly boosts CSA adoption, with a total effect size of 47%. Notably, 66% of this effect is mediated through AgI, underscoring the critical role of digital tools in supporting agricultural processes and translating financial inclusion into sustainable farming outcomes. By advancing policy discourse on the intersection of financial inclusion, gender equality, and sustainable agriculture, this research provides valuable insights for informing inclusive agricultural policies and development programs aimed at shaping future interventions in global agricultural development.

Rural women constitute a substantial portion of the global agricultural workforce yet remain marginalized in access to credit, agricultural inputs, and information. This persistent exclusion not only constrains their productivity but also undermines efforts to build resilient and sustainable food systems. As climate variability increasingly threatens smallholder farming, climate-smart agriculture (CSA) has gained prominence as a viable approach to enhance agricultural sustainability, productivity, and adaptation. However, adoption of CSA among smallholder women farmers remains patchy and elusive. In response, development actors have promoted village savings and loan associations (VSLAs) to enhance women’s access to financial services. Yet, whether—and through which mechanisms—women participation (WP) in VSLAs influences CSA adoption remains insufficiently understood. To address this knowledge gap, the study investigates the pathways through which WP in VSLAs influences CSA adoption, considering the mediating role of agricultural informatization (AgI). A cross-sectional, mixed-methods design was employed, using a multistage random sampling technique to survey 436 smallholder women farmers in rural Zambia. Quantitative data were collected through a pre-tested structured questionnaire, supplemented by qualitative data from key informant interviews. Mediation analysis, using the Sobel test and bias-corrected bootstrapping, was applied to estimate pathways, while propensity score matching (PSM) was used to check the robustness of results. Findings reveal that WP in VSLAs significantly boosts CSA adoption, with a total effect size of 47%. Notably, 66% of this effect is mediated through AgI, underscoring the critical role of digital tools in supporting agricultural processes and translating financial inclusion into sustainable farming outcomes. By advancing policy discourse on the intersection of financial inclusion, gender equality, and sustainable agriculture, this research provides valuable insights for informing inclusive agricultural policies and development programs aimed at shaping future interventions in global agricultural development.

Rural women constitute a substantial portion of the global agricultural workforce yet remain marginalized in access to credit, agricultural inputs, and information. This persistent exclusion not only constrains their productivity but also undermines efforts to build resilient and sustainable food systems. As climate variability increasingly threatens smallholder farming, climate-smart agriculture (CSA) has gained prominence as a viable approach to enhance agricultural sustainability, productivity, and adaptation. However, adoption of CSA among smallholder women farmers remains patchy and elusive. In response, development actors have promoted village savings and loan associations (VSLAs) to enhance women’s access to financial services. Yet, whether—and through which mechanisms—women participation (WP) in VSLAs influences CSA adoption remains insufficiently understood. To address this knowledge gap, the study investigates the pathways through which WP in VSLAs influences CSA adoption, considering the mediating role of agricultural informatization (AgI). A cross-sectional, mixed-methods design was employed, using a multistage random sampling technique to survey 436 smallholder women farmers in rural Zambia. Quantitative data were collected through a pre-tested structured questionnaire, supplemented by qualitative data from key informant interviews. Mediation analysis, using the Sobel test and bias-corrected bootstrapping, was applied to estimate pathways, while propensity score matching (PSM) was used to check the robustness of results. Findings reveal that WP in VSLAs significantly boosts CSA adoption, with a total effect size of 47%. Notably, 66% of this effect is mediated through AgI, underscoring the critical role of digital tools in supporting agricultural processes and translating financial inclusion into sustainable farming outcomes. By advancing policy discourse on the intersection of financial inclusion, gender equality, and sustainable agriculture, this research provides valuable insights for informing inclusive agricultural policies and development programs aimed at shaping future interventions in global agricultural development.

The digital economy, as a new economic form with high information density, provides a new driving force for the realization of high-quality agricultural development. Panel data of 31 provinces in China from 2011 to 2020 were selected for analysis. The static panel data interaction effect model and panel threshold model were used to verify the nonlinear influence mechanism and heterogeneity of financial development in the process of the digital economy affecting high-quality agricultural development. The findings are as follows. (1) During the study period, the high-quality development of China’s agriculture showed a steady upward trend; however, the regional differences were significant, and the eastern part was larger than the central and western part. (2) The digital economy can promote high-quality agricultural development. (3) The digital economy has a double threshold effect in the process of affecting high-quality agricultural development, which depends on the level of financial development. When the threshold is exceeded, the digital economy has a more significant promoting effect on high-quality agricultural development. (4) The impact of the digital economy on high-quality agricultural development is heterogeneous. From the perspective of different regions, the impact effect is greatest in the eastern region, while the effect is smaller in the central and western regions. From different resource endowments, the positive impact effect is greatest in the major grain-selling areas, followed by the major grain producing areas, but the positive digital economy driving effect is not significant in the balance of production and sales areas. Finally, three policy suggestions are proposed. First, the Chinese government should increase investments in and support for digital technology to promote the integration of the digital economy and agriculture. Second, the Chinese government should promote the development of digital inclusive finance in areas with financial development below the threshold. Third, different regions should implement differentiated digital economies to promote high-quality agricultural development.