Pub Date : 2024-07-17DOI: 10.3390/agriculture14071169
Xuefeng Zhu, Yang Xu, C. Han, Jia You, Xuejun Zhang, Hanping Mao, Xu Ma
In view of the low degree of mechanization and poor quality of harvesting of edible sunflower after drying, an in situ bionic harvesting device was designed, which can achieve low-loss harvesting of edible sunflower without removing the edible sunflower disc. According to the physical characteristics of sunflower stalks in the field, influencing factors of in situ low-loss feeding were obtained, and the structural parameters of the in situ feeding mechanism were determined. Based on bionic technology and static analysis, the influencing factors on the performance of the bionic threshing mechanism were obtained. By analyzing the mechanical characteristics of edible sunflower seed, the operation parameters of the seed collection mechanism were determined. Based on the structural analysis results of the harvesting device, a response surface optimization test was carried out. The test results show that when the average rotation speed of the bionic loosening roller was 113.57 rpm, the average rotation speed of the simulated artificial striking roller was 230.80 rpm, the average forward speed of the harvesting device was 0.58 m/s, the working quality of the harvesting device was the best, the seed loss rate was 2.12%, and the edible sunflower disc threshing rate was 98.96%. A field verification test further confirms that under the optimal working parameters, the relative deviation between test indexes and response surface optimization test results was less than 2%. During the operation process, the movement of key components of the harvesting device was coordinated and stable. The research results can provide new ideas for the mechanized harvesting of the edible sunflower disc after drying.
{"title":"Design and Experiment of In-Situ Bionic Harvesting Device for Edible Sunflower","authors":"Xuefeng Zhu, Yang Xu, C. Han, Jia You, Xuejun Zhang, Hanping Mao, Xu Ma","doi":"10.3390/agriculture14071169","DOIUrl":"https://doi.org/10.3390/agriculture14071169","url":null,"abstract":"In view of the low degree of mechanization and poor quality of harvesting of edible sunflower after drying, an in situ bionic harvesting device was designed, which can achieve low-loss harvesting of edible sunflower without removing the edible sunflower disc. According to the physical characteristics of sunflower stalks in the field, influencing factors of in situ low-loss feeding were obtained, and the structural parameters of the in situ feeding mechanism were determined. Based on bionic technology and static analysis, the influencing factors on the performance of the bionic threshing mechanism were obtained. By analyzing the mechanical characteristics of edible sunflower seed, the operation parameters of the seed collection mechanism were determined. Based on the structural analysis results of the harvesting device, a response surface optimization test was carried out. The test results show that when the average rotation speed of the bionic loosening roller was 113.57 rpm, the average rotation speed of the simulated artificial striking roller was 230.80 rpm, the average forward speed of the harvesting device was 0.58 m/s, the working quality of the harvesting device was the best, the seed loss rate was 2.12%, and the edible sunflower disc threshing rate was 98.96%. A field verification test further confirms that under the optimal working parameters, the relative deviation between test indexes and response surface optimization test results was less than 2%. During the operation process, the movement of key components of the harvesting device was coordinated and stable. The research results can provide new ideas for the mechanized harvesting of the edible sunflower disc after drying.","PeriodicalId":7447,"journal":{"name":"Agriculture","volume":" 18","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141831108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-17DOI: 10.3390/agriculture14071165
Jinglian Tian, Yongzhong Tian, Wenhao Wan, Chenxi Yuan, Kangning Liu, Yang Wang
Rice is a globally important food crop, and it is crucial to accurately and conveniently obtain information on rice fields, understand their spatial patterns, and grasp their dynamic changes to address food security challenges. In this study, Chongqing’s Yongchuan District was selected as the research area. By utilizing UAVs (Unmanned Aerial Vehicles) to collect multi-spectral remote sensing data during three seasons, the phenological characteristics of rice fields were analyzed using the NDVI (Normalized Difference Vegetation Index). Based on Sentinel data with a resolution of 10 m, the NDVI difference method was used to extract rice fields between 2019 and 2023. Furthermore, the reasons for changes in rice fields over the five years were also analyzed. First, a simulation model of the rice harvesting period was constructed using data from 32 sampling points through multiple regression analysis. Based on the model, the study area was classified into six categories, and the necessary data for each region were identified. Next, the NDVI values for the pre-harvest and post-harvest periods of rice fields, as well as the differences between them, were calculated for various regions. Additionally, every year, 35 samples of rice fields were chosen from high-resolution images provided by Google. The thresholds for extracting rice fields were determined by statistically analyzing the difference in NDVI values within the sample area. By utilizing these thresholds, rice fields corresponding to six harvesting regions were extracted separately. The rice fields extracted from different regions were merged to obtain the rice fields for the study area from 2019 to 2023, and the accuracy of the extraction results was verified. Then, based on five years of rice fields in the study area, we analyzed them from both temporal and spatial perspectives. In the temporal analysis, a transition matrix of rice field changes and the calculation of the rice fields’ dynamic degree were utilized to examine the temporal changes. The spatial changes were analyzed by incorporating DEM (Digital Elevation Model) data. Finally, a logistic regression model was employed to investigate the causes of both temporal and spatial changes in the rice fields. The study results indicated the following: (1) The simulation model of the rice harvesting period can quickly and accurately determine the best period of remote sensing images needed to extract rice fields. (2) The confusion matrix shows the effectiveness of the NDVI difference method in extracting rice fields. (3) The total area of rice fields in the study area did not change much each year, but there were still significant spatial adjustments. Over the five years, the spatial distribution of gained rice fields was relatively uniform, while the lost rice fields showed obvious regional differences. In combination with the analysis of altitude, it tended to grow in lower areas. (4) The logistic regression analysis revealed that gained ric
{"title":"Research on the Temporal and Spatial Changes and Driving Forces of Rice Fields Based on the NDVI Difference Method","authors":"Jinglian Tian, Yongzhong Tian, Wenhao Wan, Chenxi Yuan, Kangning Liu, Yang Wang","doi":"10.3390/agriculture14071165","DOIUrl":"https://doi.org/10.3390/agriculture14071165","url":null,"abstract":"Rice is a globally important food crop, and it is crucial to accurately and conveniently obtain information on rice fields, understand their spatial patterns, and grasp their dynamic changes to address food security challenges. In this study, Chongqing’s Yongchuan District was selected as the research area. By utilizing UAVs (Unmanned Aerial Vehicles) to collect multi-spectral remote sensing data during three seasons, the phenological characteristics of rice fields were analyzed using the NDVI (Normalized Difference Vegetation Index). Based on Sentinel data with a resolution of 10 m, the NDVI difference method was used to extract rice fields between 2019 and 2023. Furthermore, the reasons for changes in rice fields over the five years were also analyzed. First, a simulation model of the rice harvesting period was constructed using data from 32 sampling points through multiple regression analysis. Based on the model, the study area was classified into six categories, and the necessary data for each region were identified. Next, the NDVI values for the pre-harvest and post-harvest periods of rice fields, as well as the differences between them, were calculated for various regions. Additionally, every year, 35 samples of rice fields were chosen from high-resolution images provided by Google. The thresholds for extracting rice fields were determined by statistically analyzing the difference in NDVI values within the sample area. By utilizing these thresholds, rice fields corresponding to six harvesting regions were extracted separately. The rice fields extracted from different regions were merged to obtain the rice fields for the study area from 2019 to 2023, and the accuracy of the extraction results was verified. Then, based on five years of rice fields in the study area, we analyzed them from both temporal and spatial perspectives. In the temporal analysis, a transition matrix of rice field changes and the calculation of the rice fields’ dynamic degree were utilized to examine the temporal changes. The spatial changes were analyzed by incorporating DEM (Digital Elevation Model) data. Finally, a logistic regression model was employed to investigate the causes of both temporal and spatial changes in the rice fields. The study results indicated the following: (1) The simulation model of the rice harvesting period can quickly and accurately determine the best period of remote sensing images needed to extract rice fields. (2) The confusion matrix shows the effectiveness of the NDVI difference method in extracting rice fields. (3) The total area of rice fields in the study area did not change much each year, but there were still significant spatial adjustments. Over the five years, the spatial distribution of gained rice fields was relatively uniform, while the lost rice fields showed obvious regional differences. In combination with the analysis of altitude, it tended to grow in lower areas. (4) The logistic regression analysis revealed that gained ric","PeriodicalId":7447,"journal":{"name":"Agriculture","volume":" 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141828429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-17DOI: 10.3390/agriculture14071166
Baoqi Liu, Lishan Xu, Yulin Long, Yuehua Wei, Changlin Ao
Farmland eco-compensation, as a typical payment for ecosystem services scheme, aims to address trade-offs between environmental and developmental objectives. As indispensable eco-compensation supporters, the public’s willingness to pay (WTP) for farmland eco-compensation and the allocation to farmers directly affect ecological safety and sustainable development for farmland. Therefore, this study links the public’s WTP for the farmland eco-compensation to the financial subsidies received by farmers and presents a theoretical framework and research approach that connects stakeholders, applying improved choice experiments for empirical study in the black soil region of northeastern China. The results showed that the public has a positive WTP for the farmland eco-compensation program that improves the area, soil thickness, and organic content expeditiously. The public’s WTP allocation for eco-compensation varies considerably, with the share allocated to farmers in their WTP averaging 46.96%, showing a benchmark for compensation standards. The results revealed the influential relationship between the socioeconomic characteristics of the public with WTP allocation and the preferences for farmland eco-compensation, such as the positive correlation between age with WTP allocation and females’ greater preference for eco-compensation. These findings can provide new perspectives and approaches to exploring sustainable pathways for farmland eco-compensation.
{"title":"Public Willingness to Pay for Farmland Eco-Compensation and Allocation to Farmers: An Empirical Study from Northeast China","authors":"Baoqi Liu, Lishan Xu, Yulin Long, Yuehua Wei, Changlin Ao","doi":"10.3390/agriculture14071166","DOIUrl":"https://doi.org/10.3390/agriculture14071166","url":null,"abstract":"Farmland eco-compensation, as a typical payment for ecosystem services scheme, aims to address trade-offs between environmental and developmental objectives. As indispensable eco-compensation supporters, the public’s willingness to pay (WTP) for farmland eco-compensation and the allocation to farmers directly affect ecological safety and sustainable development for farmland. Therefore, this study links the public’s WTP for the farmland eco-compensation to the financial subsidies received by farmers and presents a theoretical framework and research approach that connects stakeholders, applying improved choice experiments for empirical study in the black soil region of northeastern China. The results showed that the public has a positive WTP for the farmland eco-compensation program that improves the area, soil thickness, and organic content expeditiously. The public’s WTP allocation for eco-compensation varies considerably, with the share allocated to farmers in their WTP averaging 46.96%, showing a benchmark for compensation standards. The results revealed the influential relationship between the socioeconomic characteristics of the public with WTP allocation and the preferences for farmland eco-compensation, such as the positive correlation between age with WTP allocation and females’ greater preference for eco-compensation. These findings can provide new perspectives and approaches to exploring sustainable pathways for farmland eco-compensation.","PeriodicalId":7447,"journal":{"name":"Agriculture","volume":" 22","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141829644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-16DOI: 10.3390/agriculture14071153
Jiancheng Zhai, Xiao Sun, Xueqin Hu, Jun Tian, Zhiqiang Huang
Livelihood strategies are an effective response to survival risks and stress shocks. Agricultural residents engaged in agriculture, forestry, animal husbandry, and fishery, who are extremely dependent on natural resources, are vulnerable to various livelihood risks. Therefore, the livelihood strategies of agricultural residents are increasingly receiving attention from researchers around the world. However, research on the livelihood strategies of agricultural residents has not yet been systematically analyzed through bibliometrics. Our study was based on 1424 publications in the Web of Science Core Collection database (WoSCC) from 2014 to 2023 to analyze the development history, research hotspots, and trends in the field. Bibliometric analysis was conducted on publications, countries, institutions, authors, journals, and keywords, as well as cited journals and cited references using Excel and CiteSpace software. The number of publications has steadily increased and showed an upward trend. The United States and China were the countries with the most contributions, and Chinese institutions were more active. Cooperation between authors was relatively weak. Sustainability was one of the most productive and highly cited journals. The research hotspots mainly included the relationship between climate change and the livelihood strategies of agricultural residents, the relationship between the land and the livelihood strategies of agricultural residents, the sustainable development of livelihood strategies of agricultural residents, and the characteristics of livelihood strategies of agricultural residents. This is the first time that bibliometric and visual analyses have been conducted on the livelihood strategies of agricultural residents, which may further promote development of the field and lay a foundation for future research.
{"title":"Evolutionary Trends and Hotspot Analysis of Livelihood Strategy for Agricultural Residents Based on Bibliometrics","authors":"Jiancheng Zhai, Xiao Sun, Xueqin Hu, Jun Tian, Zhiqiang Huang","doi":"10.3390/agriculture14071153","DOIUrl":"https://doi.org/10.3390/agriculture14071153","url":null,"abstract":"Livelihood strategies are an effective response to survival risks and stress shocks. Agricultural residents engaged in agriculture, forestry, animal husbandry, and fishery, who are extremely dependent on natural resources, are vulnerable to various livelihood risks. Therefore, the livelihood strategies of agricultural residents are increasingly receiving attention from researchers around the world. However, research on the livelihood strategies of agricultural residents has not yet been systematically analyzed through bibliometrics. Our study was based on 1424 publications in the Web of Science Core Collection database (WoSCC) from 2014 to 2023 to analyze the development history, research hotspots, and trends in the field. Bibliometric analysis was conducted on publications, countries, institutions, authors, journals, and keywords, as well as cited journals and cited references using Excel and CiteSpace software. The number of publications has steadily increased and showed an upward trend. The United States and China were the countries with the most contributions, and Chinese institutions were more active. Cooperation between authors was relatively weak. Sustainability was one of the most productive and highly cited journals. The research hotspots mainly included the relationship between climate change and the livelihood strategies of agricultural residents, the relationship between the land and the livelihood strategies of agricultural residents, the sustainable development of livelihood strategies of agricultural residents, and the characteristics of livelihood strategies of agricultural residents. This is the first time that bibliometric and visual analyses have been conducted on the livelihood strategies of agricultural residents, which may further promote development of the field and lay a foundation for future research.","PeriodicalId":7447,"journal":{"name":"Agriculture","volume":" 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141832072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-16DOI: 10.3390/agriculture14071159
C. Purwin, K. Żuk-Gołaszewska, Józef Tyburski, Marta Borsuk-Stanulewicz, B. Stefańska
The aim of this study was to determine the quality of organically grown red clover herbage and silage after being influenced by supplementary mineral fertilization. The experimental treatments were as follows: control treatment without fertilization (group C), treatment where kalimagnesia (Patentkali) was applied (group P), and treatment where potassium sulfate (SOP) was applied (group S). In each year of the experiment, first-cut herbage was harvested at the beginning of flowering and ensiled. The year of the study had a significant (p ≤ 0.05) influence on the analyzed parameters of herbage and silage, excluding the content of calcium (Ca), acetic acid (AA), and ammonia nitrogen (N-NH3). The organic production system exerted a significant (p ≤ 0.05) effect on the concentrations of crude protein (CP), acid detergent lignin (ADL), water-soluble carbohydrates (WSC), minerals (P, K, Ca, Na), lactic acid (LA), ethanol, and N-NH3. The pattern of fermentation was affected by both experimental factors. True protein (TP) content was determined at 70–84% CP in herbage and 53–65% CP in silages. The energy value and the protein value of herbage varied significantly across years of the study and in response to the combined effects of both experimental factors (p ≤ 0.05). Red clover grown in organic production systems supplied high-quality forage.
{"title":"Quality of Red Clover Forage in Different Organic Production Systems","authors":"C. Purwin, K. Żuk-Gołaszewska, Józef Tyburski, Marta Borsuk-Stanulewicz, B. Stefańska","doi":"10.3390/agriculture14071159","DOIUrl":"https://doi.org/10.3390/agriculture14071159","url":null,"abstract":"The aim of this study was to determine the quality of organically grown red clover herbage and silage after being influenced by supplementary mineral fertilization. The experimental treatments were as follows: control treatment without fertilization (group C), treatment where kalimagnesia (Patentkali) was applied (group P), and treatment where potassium sulfate (SOP) was applied (group S). In each year of the experiment, first-cut herbage was harvested at the beginning of flowering and ensiled. The year of the study had a significant (p ≤ 0.05) influence on the analyzed parameters of herbage and silage, excluding the content of calcium (Ca), acetic acid (AA), and ammonia nitrogen (N-NH3). The organic production system exerted a significant (p ≤ 0.05) effect on the concentrations of crude protein (CP), acid detergent lignin (ADL), water-soluble carbohydrates (WSC), minerals (P, K, Ca, Na), lactic acid (LA), ethanol, and N-NH3. The pattern of fermentation was affected by both experimental factors. True protein (TP) content was determined at 70–84% CP in herbage and 53–65% CP in silages. The energy value and the protein value of herbage varied significantly across years of the study and in response to the combined effects of both experimental factors (p ≤ 0.05). Red clover grown in organic production systems supplied high-quality forage.","PeriodicalId":7447,"journal":{"name":"Agriculture","volume":"2 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141642697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-16DOI: 10.3390/agriculture14071152
S. Milijašević-Marčić, L. Santric, Jelena Luković, I. Potočnik, Nikola Grujić, Tanja Drobnjaković, D. Marčić
Green mould, caused by Trichoderma aggressivum, is one of the major fungal diseases of button mushrooms. The main problems in chemical disease control include a lack of effective agents, the occurrence of pathogen resistance to pesticides, and the harmful impact on the environment. In an attempt to find a solution, the interaction between two beneficial microorganisms, Bacillus amyloliquefaciens B-241 (an antifungal agent) and Streptomyces flavovirens A06 (a yield stimulant), was investigated in vivo. The synergy factor (SF) was calculated as a ratio between the observed and expected impact on the yield or efficacy of disease suppression after artificial inoculation with T. aggressivum. The highest control of T. aggressivum was achieved by joint application of the two beneficial microorganisms. The additive interaction between microorganisms in efficacy against the pathogen was revealed. The largest yield was obtained in mushroom beds sprayed with the two beneficial microorganisms combined (B-241 80% and A06 20%). Regarding the impact on the yield, synergistic interaction between the two microorganisms was confirmed (SFs were 1.62 or 1.52). The introduction of optimized microbial combinations could create new possibilities for biorational edible mushroom protection, with improved yield and quality and reduced risks to human health and the environment.
{"title":"Altering Microbial Communities in Substrate to Stimulate the Growth of Healthy Button Mushrooms","authors":"S. Milijašević-Marčić, L. Santric, Jelena Luković, I. Potočnik, Nikola Grujić, Tanja Drobnjaković, D. Marčić","doi":"10.3390/agriculture14071152","DOIUrl":"https://doi.org/10.3390/agriculture14071152","url":null,"abstract":"Green mould, caused by Trichoderma aggressivum, is one of the major fungal diseases of button mushrooms. The main problems in chemical disease control include a lack of effective agents, the occurrence of pathogen resistance to pesticides, and the harmful impact on the environment. In an attempt to find a solution, the interaction between two beneficial microorganisms, Bacillus amyloliquefaciens B-241 (an antifungal agent) and Streptomyces flavovirens A06 (a yield stimulant), was investigated in vivo. The synergy factor (SF) was calculated as a ratio between the observed and expected impact on the yield or efficacy of disease suppression after artificial inoculation with T. aggressivum. The highest control of T. aggressivum was achieved by joint application of the two beneficial microorganisms. The additive interaction between microorganisms in efficacy against the pathogen was revealed. The largest yield was obtained in mushroom beds sprayed with the two beneficial microorganisms combined (B-241 80% and A06 20%). Regarding the impact on the yield, synergistic interaction between the two microorganisms was confirmed (SFs were 1.62 or 1.52). The introduction of optimized microbial combinations could create new possibilities for biorational edible mushroom protection, with improved yield and quality and reduced risks to human health and the environment.","PeriodicalId":7447,"journal":{"name":"Agriculture","volume":"55 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141643452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-16DOI: 10.3390/agriculture14071164
Aleksandra Zimmer, K. Masztalerz, K. Lech
This study investigates the effects of osmotic dehydration on garlic clove halves using a low-pH osmotic solution with ascorbic acid, concentrated tomato juice, and basil extract (45° Brix). Samples, both dehydrated and fresh, were subjected to various drying methods. Physical properties, such as CT scan analysis, texture profile analysis (TPA), porosity, and density, were examined. Additional parameters like energy consumption, specific energy consumption, moisture content, water activity, and color change were evaluated. Osmotic dehydration reduced moisture content by over 7.5%. The specific energy consumption for microwave vacuum drying (MVD) was 95 kJ/g for osmotically dehydrated samples compared to 118 kJ/g for non-dehydrated samples. Drying times decreased by 24 min for MVD and 15% for microwave convective drying (MCD). The Weibull model best fit the drying kinetics, with R2 values above 0.99 and RMSE below 0.03 for all methods. TPA tests showed no significant impact of osmotic dehydration on hardness, though drying methods significantly affected hardness, ranging from 49 N to 707 N. Color change was higher for osmotically dehydrated samples, reaching 37.09 for OD-CD compared to 29.78 for CD.
{"title":"Effect of Osmotic Dehydration in Tomato Juice on Microstructure of Garlic and on Drying Using Different Methods","authors":"Aleksandra Zimmer, K. Masztalerz, K. Lech","doi":"10.3390/agriculture14071164","DOIUrl":"https://doi.org/10.3390/agriculture14071164","url":null,"abstract":"This study investigates the effects of osmotic dehydration on garlic clove halves using a low-pH osmotic solution with ascorbic acid, concentrated tomato juice, and basil extract (45° Brix). Samples, both dehydrated and fresh, were subjected to various drying methods. Physical properties, such as CT scan analysis, texture profile analysis (TPA), porosity, and density, were examined. Additional parameters like energy consumption, specific energy consumption, moisture content, water activity, and color change were evaluated. Osmotic dehydration reduced moisture content by over 7.5%. The specific energy consumption for microwave vacuum drying (MVD) was 95 kJ/g for osmotically dehydrated samples compared to 118 kJ/g for non-dehydrated samples. Drying times decreased by 24 min for MVD and 15% for microwave convective drying (MCD). The Weibull model best fit the drying kinetics, with R2 values above 0.99 and RMSE below 0.03 for all methods. TPA tests showed no significant impact of osmotic dehydration on hardness, though drying methods significantly affected hardness, ranging from 49 N to 707 N. Color change was higher for osmotically dehydrated samples, reaching 37.09 for OD-CD compared to 29.78 for CD.","PeriodicalId":7447,"journal":{"name":"Agriculture","volume":" 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141832164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-16DOI: 10.3390/agriculture14071155
Yafei Wang, Tiezhu Li, Tianhua Chen, Xiaodong Zhang, Mohamed Farag Taha, Ning Yang, Hanping Mao, Qiang Shi
It is of great significance to develop early prediction technology for controlling downy mildew and promoting cucumber production. In this study, a cucumber downy mildew prediction method was proposed by fusing quantitative disease information and environmental data. Firstly, the number of cucumber downy mildew spores during the experiment was collected by a portable spore catcher, and the proportion of cucumber downy mildew leaf area to all cucumber leaf area was recorded, which was used as the incidence degree of cucumber plants. The environmental data in the greenhouse were monitored and recorded by the weather station in the greenhouse. Environmental data outside the greenhouse were monitored and recorded by a weather station in front of the greenhouse. Then, the influencing factors of cucumber downy mildew were analyzed based on the Pearson correlation coefficient method. The influencing factors of the cucumber downy mildew early warning model in greenhouse were identified. Finally, the CNN-LSTM (Convolutional Neural Network-Long Short-Term Memory) algorithm was used to establish the cucumber downy mildew incidence prediction model. The results showed that the Mean Absolute Error (MAE), Mean Square Error (MSE), Root Mean Square Error (RMSE), and determination coefficient (R2) of the CNN-LSTM network model were 0.069, 0.0098, 0.0991, and 0.9127, respectively. The maximum error between the predicted value and the true value for all test sets was 16.9398%. The minimum error between the predicted value and the true value for all test sets was 0.3413%. The average error between the predicted and true values for all test sets was 6.6478%. The Bland–Altman method was used to analyze the predicted and true values of the test set, and 95.65% of the test set data numbers were within the 95% consistency interval. This work can serve as a foundation for the creation of early prediction models of greenhouse crop airborne diseases.
{"title":"Cucumber Downy Mildew Disease Prediction Using a CNN-LSTM Approach","authors":"Yafei Wang, Tiezhu Li, Tianhua Chen, Xiaodong Zhang, Mohamed Farag Taha, Ning Yang, Hanping Mao, Qiang Shi","doi":"10.3390/agriculture14071155","DOIUrl":"https://doi.org/10.3390/agriculture14071155","url":null,"abstract":"It is of great significance to develop early prediction technology for controlling downy mildew and promoting cucumber production. In this study, a cucumber downy mildew prediction method was proposed by fusing quantitative disease information and environmental data. Firstly, the number of cucumber downy mildew spores during the experiment was collected by a portable spore catcher, and the proportion of cucumber downy mildew leaf area to all cucumber leaf area was recorded, which was used as the incidence degree of cucumber plants. The environmental data in the greenhouse were monitored and recorded by the weather station in the greenhouse. Environmental data outside the greenhouse were monitored and recorded by a weather station in front of the greenhouse. Then, the influencing factors of cucumber downy mildew were analyzed based on the Pearson correlation coefficient method. The influencing factors of the cucumber downy mildew early warning model in greenhouse were identified. Finally, the CNN-LSTM (Convolutional Neural Network-Long Short-Term Memory) algorithm was used to establish the cucumber downy mildew incidence prediction model. The results showed that the Mean Absolute Error (MAE), Mean Square Error (MSE), Root Mean Square Error (RMSE), and determination coefficient (R2) of the CNN-LSTM network model were 0.069, 0.0098, 0.0991, and 0.9127, respectively. The maximum error between the predicted value and the true value for all test sets was 16.9398%. The minimum error between the predicted value and the true value for all test sets was 0.3413%. The average error between the predicted and true values for all test sets was 6.6478%. The Bland–Altman method was used to analyze the predicted and true values of the test set, and 95.65% of the test set data numbers were within the 95% consistency interval. This work can serve as a foundation for the creation of early prediction models of greenhouse crop airborne diseases.","PeriodicalId":7447,"journal":{"name":"Agriculture","volume":" 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141832459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-16DOI: 10.3390/agriculture14071158
S. Tu, Hua Lei, Yun Liang, Enli Lyu, Hongxing Liu
Pig behavioral analysis based on multi-object tracking (MOT) technology of surveillance videos is vital for precision livestock farming. To address the challenges posed by uneven lighting scenes and irregular pig movements in the MOT task, we proposed a pig MOT method named RpTrack. Firstly, RpTrack addresses the issue of lost tracking caused by irregular pig movements by using an appropriate Kalman Filter and improved trajectory management. Then, RpTrack utilizes BIoU for the second matching strategy to alleviate the influence of missed detections on the tracking performance. Finally, the method utilizes post-processing on the tracking results to generate behavioral statistics and activity trajectories for each pig. The experimental results under conditions of uneven lighting and irregular pig movements show that RpTrack significantly outperforms four other state-of-the-art MOT methods, including SORT, OC-SORT, ByteTrack, and Bot-SORT, on both public and private datasets. The experimental results demonstrate that RpTrack not only has the best tracking performance but also has high-speed processing capabilities. In conclusion, RpTrack effectively addresses the challenges of uneven scene lighting and irregular pig movements, enabling accurate pig tracking and monitoring of different behaviors, such as eating, standing, and lying. This research supports the advancement and application of intelligent pig farming.
{"title":"RpTrack: Robust Pig Tracking with Irregular Movement Processing and Behavioral Statistics","authors":"S. Tu, Hua Lei, Yun Liang, Enli Lyu, Hongxing Liu","doi":"10.3390/agriculture14071158","DOIUrl":"https://doi.org/10.3390/agriculture14071158","url":null,"abstract":"Pig behavioral analysis based on multi-object tracking (MOT) technology of surveillance videos is vital for precision livestock farming. To address the challenges posed by uneven lighting scenes and irregular pig movements in the MOT task, we proposed a pig MOT method named RpTrack. Firstly, RpTrack addresses the issue of lost tracking caused by irregular pig movements by using an appropriate Kalman Filter and improved trajectory management. Then, RpTrack utilizes BIoU for the second matching strategy to alleviate the influence of missed detections on the tracking performance. Finally, the method utilizes post-processing on the tracking results to generate behavioral statistics and activity trajectories for each pig. The experimental results under conditions of uneven lighting and irregular pig movements show that RpTrack significantly outperforms four other state-of-the-art MOT methods, including SORT, OC-SORT, ByteTrack, and Bot-SORT, on both public and private datasets. The experimental results demonstrate that RpTrack not only has the best tracking performance but also has high-speed processing capabilities. In conclusion, RpTrack effectively addresses the challenges of uneven scene lighting and irregular pig movements, enabling accurate pig tracking and monitoring of different behaviors, such as eating, standing, and lying. This research supports the advancement and application of intelligent pig farming.","PeriodicalId":7447,"journal":{"name":"Agriculture","volume":"1 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141642901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In addressing the challenges of high labor intensity, cost, and potential mechanical damage to banana fruit in orchards, this study presents the design of a banana bunch transport device featuring a lifting mechanism and an automatic fruit shaft bottom-fixing system. The device is tailored to the planting and morphological characteristics of banana bunches, aiming for efficient, low-loss, and labor-saving mechanized transport. Key design considerations included the anti-overturning mechanism and the lifting system based on transportation conditions and the physical dimensions of banana bunches. A dynamic simulation was conducted to analyze the angular velocity and acceleration during the initial conveying stages, forming the basis for the fruit shaft bottom-fixation mechanism. A novel horizontal multi-point scanning method was developed to accurately identify and secure the fruit shaft bottom, complemented by an automated control system. Experimental results showed a 95.83% success rate in identification and fixation, validated by field trials that confirmed the necessity and stability of the fixation mechanism. To enhance the durability of the fruit shaft bottom-fixation mechanism, a multi-factor test was conducted, optimizing the device’s maximum travel speed and minimizing the banana bunch’s oscillation angle. Field tests showed an oscillation angle of 8.961°, closely matching the simulated result of 9.526°, demonstrating the reliability of the response surface analysis model. This study offers a practical and efficient solution for banana bunch transport in orchards, showcasing significant practical value and potential for wider adoption.
{"title":"Design and Experimental Study of Banana Bunch Transportation Device with Lifting Mechanism and Automatic Bottom-Fixing Fruit Shaft","authors":"Weiqin Li, Zhou Yang, Xing Xu, Weixi Li, Xingkang Mo, Jiaxiang Yu, Jieli Duan","doi":"10.3390/agriculture14071161","DOIUrl":"https://doi.org/10.3390/agriculture14071161","url":null,"abstract":"In addressing the challenges of high labor intensity, cost, and potential mechanical damage to banana fruit in orchards, this study presents the design of a banana bunch transport device featuring a lifting mechanism and an automatic fruit shaft bottom-fixing system. The device is tailored to the planting and morphological characteristics of banana bunches, aiming for efficient, low-loss, and labor-saving mechanized transport. Key design considerations included the anti-overturning mechanism and the lifting system based on transportation conditions and the physical dimensions of banana bunches. A dynamic simulation was conducted to analyze the angular velocity and acceleration during the initial conveying stages, forming the basis for the fruit shaft bottom-fixation mechanism. A novel horizontal multi-point scanning method was developed to accurately identify and secure the fruit shaft bottom, complemented by an automated control system. Experimental results showed a 95.83% success rate in identification and fixation, validated by field trials that confirmed the necessity and stability of the fixation mechanism. To enhance the durability of the fruit shaft bottom-fixation mechanism, a multi-factor test was conducted, optimizing the device’s maximum travel speed and minimizing the banana bunch’s oscillation angle. Field tests showed an oscillation angle of 8.961°, closely matching the simulated result of 9.526°, demonstrating the reliability of the response surface analysis model. This study offers a practical and efficient solution for banana bunch transport in orchards, showcasing significant practical value and potential for wider adoption.","PeriodicalId":7447,"journal":{"name":"Agriculture","volume":"14 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141641089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：