Pub Date : 2024-09-04DOI: 10.3390/agronomy14092019
Yuelong Zhou, Mingyuan Xu, Yong Zhou, Zhaoyang Hu, Shiqiang Liu
The commercial value of cucumbers is influenced by the presence of spines or trichomes on their fruit, while the trichomes found on other parts of the plant are essential for protecting the cucumber against a range of biotic and abiotic stresses. In our research, we identified a glabrous nwd mutant from EMS-induced cucumber (Cucumis sativus L.) mutant lines. This mutant displays a consistent glabrous phenotype across all plant organs. Upon analysis, it was revealed that the nwd mutation is governed by a lone recessive nuclear gene. The nwd plants show a significant reduction in both their photosynthetic capacity and chlorophyll a content when compared to the wild-type. Furthermore, there are notable changes in the antioxidant enzyme activities, soluble protein levels, and malondialdehyde content of the nwd mutant. Genotyping and MutMap approaches identified the CsNWD gene, encoding a VPS protein, as a candidate responsible for the glabrous trait. Transcriptome analysis indicated that 15 trichome-related genes exhibit significant expression changes in the nwd mutant, implying that CsNWD may regulate trichome development through interactions with these genes. This study contributes to the understanding of VPS proteins in trichome initiation and the underlying mechanisms of trichome development.
{"title":"CsNWD Encoding VPS62 Emerges as a Candidate Gene Conferring the Glabrous Phenotype in Cucumber","authors":"Yuelong Zhou, Mingyuan Xu, Yong Zhou, Zhaoyang Hu, Shiqiang Liu","doi":"10.3390/agronomy14092019","DOIUrl":"https://doi.org/10.3390/agronomy14092019","url":null,"abstract":"The commercial value of cucumbers is influenced by the presence of spines or trichomes on their fruit, while the trichomes found on other parts of the plant are essential for protecting the cucumber against a range of biotic and abiotic stresses. In our research, we identified a glabrous nwd mutant from EMS-induced cucumber (Cucumis sativus L.) mutant lines. This mutant displays a consistent glabrous phenotype across all plant organs. Upon analysis, it was revealed that the nwd mutation is governed by a lone recessive nuclear gene. The nwd plants show a significant reduction in both their photosynthetic capacity and chlorophyll a content when compared to the wild-type. Furthermore, there are notable changes in the antioxidant enzyme activities, soluble protein levels, and malondialdehyde content of the nwd mutant. Genotyping and MutMap approaches identified the CsNWD gene, encoding a VPS protein, as a candidate responsible for the glabrous trait. Transcriptome analysis indicated that 15 trichome-related genes exhibit significant expression changes in the nwd mutant, implying that CsNWD may regulate trichome development through interactions with these genes. This study contributes to the understanding of VPS proteins in trichome initiation and the underlying mechanisms of trichome development.","PeriodicalId":7601,"journal":{"name":"Agronomy","volume":"47 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142209288","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 : 2024-09-03DOI: 10.3390/agronomy14092009
Marcos Antonio de Bortolli, Tangriani Simioni Assmann, Betania Brum de Bortolli, Marcieli Maccari, Angela Bernardon, Jorge Jamhour, Alan J. Franzluebbers, Andre Brugnara Soares, Igor Kieling Severo
Current fertilizer recommendations often neglect nutrient cycling across crop rotations. This study aimed to assess the decay rate and nutrient (N, P, K) release patterns of sorghum, black oat, and corn residues (omitido) in an integrated crop–livestock system. The experiment used factorial treatments based on two sward heights (high and low) and two nitrogen fertilization levels (N-pasture at 200 kg N ha−1 and N-corn at 0 kg N ha−1). Litter bags were collected at various intervals from each crop to measure nutrient release patterns and decomposition rates. The results showed that pasture height and nitrogen fertilization significantly influenced decomposition and nutrient release, affecting the subsequent grain crop phase. Potassium was released rapidly and in high amounts. Nitrogen fertilization during the pasture phase prevented nitrogen and phosphorus immobilization in black oat residue and reduced immobilization in corn residue. These findings highlight the importance of accounting for nutrient cycling and decomposition rates in fertilization strategies to enhance the sustainability of integrated crop–livestock systems.
{"title":"Nutrient Dynamics in Integrated Crop–Livestock Systems: Effects of Stocking Rates and Nitrogen System Fertilization on Litter Decomposition and Release","authors":"Marcos Antonio de Bortolli, Tangriani Simioni Assmann, Betania Brum de Bortolli, Marcieli Maccari, Angela Bernardon, Jorge Jamhour, Alan J. Franzluebbers, Andre Brugnara Soares, Igor Kieling Severo","doi":"10.3390/agronomy14092009","DOIUrl":"https://doi.org/10.3390/agronomy14092009","url":null,"abstract":"Current fertilizer recommendations often neglect nutrient cycling across crop rotations. This study aimed to assess the decay rate and nutrient (N, P, K) release patterns of sorghum, black oat, and corn residues (omitido) in an integrated crop–livestock system. The experiment used factorial treatments based on two sward heights (high and low) and two nitrogen fertilization levels (N-pasture at 200 kg N ha−1 and N-corn at 0 kg N ha−1). Litter bags were collected at various intervals from each crop to measure nutrient release patterns and decomposition rates. The results showed that pasture height and nitrogen fertilization significantly influenced decomposition and nutrient release, affecting the subsequent grain crop phase. Potassium was released rapidly and in high amounts. Nitrogen fertilization during the pasture phase prevented nitrogen and phosphorus immobilization in black oat residue and reduced immobilization in corn residue. These findings highlight the importance of accounting for nutrient cycling and decomposition rates in fertilization strategies to enhance the sustainability of integrated crop–livestock systems.","PeriodicalId":7601,"journal":{"name":"Agronomy","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142209285","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 response to water scarcity in the Bashang area of northwest Hebei Province, a cold and arid region in north China, and to address the diminishing groundwater levels caused by pumping irrigation, this study investigated the impact of rainwater tank size and water supply on kidney beans production in greenhouses under various precipitation scenarios to determine the production potential and development strategies for regional precipitation resources. Under the background of average annual precipitation, kidney bean yield increased with increasing reservoir volume and shorter irrigation cycles. Under a 4-day irrigation cycle, the water demand satisfaction rate of kidney beans reached 100% water demand when the rainwater tank size was 15.7 m3. Against the wide variation in multi-year regional precipitation from 1992 to 2023, the annual effect of rainwater harvest was simulated using precipitation data collected 20 years with an 80% precipitation guarantee rate. The average minimum yield reduction rate obtained was 9.4%, and the corresponding minimum rainwater tank size was 29.5 m3. By superimposing the rainwater harvested in the shed and nonshed areas, the volume of the reservoir without yield reduction could be reduced to 20.0 m3. The sum of discharged and inventory water was much greater than the water scarcity in each water supply situation. Simulating and analyzing the effect of the relationship between rainwater tank size and water supply on rainwater harvesting in regional farmland by year provides important data affecting the construction of regional rainwater storage facilities and water supply efficiency. To achieve a high, stable yield of kidney beans grown in a greenhouse with shed film and shed area rainwater harvesting in north China, 2.6 m3 supplementary groundwater irrigation is still needed during the annual growing season.
{"title":"Effect of Water Tank Size and Supply on Greenhouse-Grown Kidney Beans Irrigated by Rainwater in Cold and Arid Regions of North China","authors":"Mengmeng Sun, Jizong Zhang, Zhihui Wang, Jingxin Ran, Yunjie Han, Jianheng Zhang, Huibin Li, Lifeng Zhang","doi":"10.3390/agronomy14081767","DOIUrl":"https://doi.org/10.3390/agronomy14081767","url":null,"abstract":"In response to water scarcity in the Bashang area of northwest Hebei Province, a cold and arid region in north China, and to address the diminishing groundwater levels caused by pumping irrigation, this study investigated the impact of rainwater tank size and water supply on kidney beans production in greenhouses under various precipitation scenarios to determine the production potential and development strategies for regional precipitation resources. Under the background of average annual precipitation, kidney bean yield increased with increasing reservoir volume and shorter irrigation cycles. Under a 4-day irrigation cycle, the water demand satisfaction rate of kidney beans reached 100% water demand when the rainwater tank size was 15.7 m3. Against the wide variation in multi-year regional precipitation from 1992 to 2023, the annual effect of rainwater harvest was simulated using precipitation data collected 20 years with an 80% precipitation guarantee rate. The average minimum yield reduction rate obtained was 9.4%, and the corresponding minimum rainwater tank size was 29.5 m3. By superimposing the rainwater harvested in the shed and nonshed areas, the volume of the reservoir without yield reduction could be reduced to 20.0 m3. The sum of discharged and inventory water was much greater than the water scarcity in each water supply situation. Simulating and analyzing the effect of the relationship between rainwater tank size and water supply on rainwater harvesting in regional farmland by year provides important data affecting the construction of regional rainwater storage facilities and water supply efficiency. To achieve a high, stable yield of kidney beans grown in a greenhouse with shed film and shed area rainwater harvesting in north China, 2.6 m3 supplementary groundwater irrigation is still needed during the annual growing season.","PeriodicalId":7601,"journal":{"name":"Agronomy","volume":"50 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141939982","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}
Recent studies have focused on using big-data-based machine learning to address the effects of climate change scenarios on the production and quality of medicinal plants. Challenges relating to data collection can hinder the analysis of key feature variables that affect the quality of medicinal plants. In the study presented herein, we analyzed feature variables that affect the phenolic content of Korean Cnidium officinale Makino (C. officinale Makino) under different climate change scenarios. We applied different climate change scenarios based on environmental information obtained from Yeongju city, Gyeongsangbuk-do, Republic of Korea, and cultivated C. officinale Makino to collect data. The collected data included 3237, 75, and 45 records, and data augmentation was performed to address this data imbalance. We designed a function based on the DPPH value to set the phenolic content grade in C. officinale Makino and proposed a stacking ensemble model for predicting the total phenol contents and classifying the phenolic content grades. The regression model in the performance evaluation presented an improvement of 6.23–7.72% in terms of the MAPE; in comparison, the classification model demonstrated a 2.48–3.34% better performance in terms of accuracy. The classification accuracy was >0.825 when classifying phenol content grades using the predicted total phenol content values from the regression model, and the area under the curve values of the model indicated high model fitness (0.987–0.981). We plan to identify the key feature variables for the optimal cultivation of C. officinale Makino and explore the relationships among these feature variables.
{"title":"Prediction and Classification of Phenol Contents in Cnidium officinale Makino Using a Stacking Ensemble Model in Climate Change Scenarios","authors":"Hyunjo Lee, Hyun Jung Koo, Kyeong Cheol Lee, Yoojin Song, Won-Kyun Joo, Cheol-Joo Chae","doi":"10.3390/agronomy14081766","DOIUrl":"https://doi.org/10.3390/agronomy14081766","url":null,"abstract":"Recent studies have focused on using big-data-based machine learning to address the effects of climate change scenarios on the production and quality of medicinal plants. Challenges relating to data collection can hinder the analysis of key feature variables that affect the quality of medicinal plants. In the study presented herein, we analyzed feature variables that affect the phenolic content of Korean Cnidium officinale Makino (C. officinale Makino) under different climate change scenarios. We applied different climate change scenarios based on environmental information obtained from Yeongju city, Gyeongsangbuk-do, Republic of Korea, and cultivated C. officinale Makino to collect data. The collected data included 3237, 75, and 45 records, and data augmentation was performed to address this data imbalance. We designed a function based on the DPPH value to set the phenolic content grade in C. officinale Makino and proposed a stacking ensemble model for predicting the total phenol contents and classifying the phenolic content grades. The regression model in the performance evaluation presented an improvement of 6.23–7.72% in terms of the MAPE; in comparison, the classification model demonstrated a 2.48–3.34% better performance in terms of accuracy. The classification accuracy was >0.825 when classifying phenol content grades using the predicted total phenol content values from the regression model, and the area under the curve values of the model indicated high model fitness (0.987–0.981). We plan to identify the key feature variables for the optimal cultivation of C. officinale Makino and explore the relationships among these feature variables.","PeriodicalId":7601,"journal":{"name":"Agronomy","volume":"22 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141939983","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}
Tomatoes are a critical economic crop. The realization of tomato harvesting automation is of great significance in solving the labor shortage and improving the efficiency of the current harvesting operation. Accurate recognition of fruits is the key to realizing automated harvesting. Harvesting fruit at optimum ripeness ensures the highest nutrient content, flavor and market value levels, thus maximizing economic benefits. Owing to foliage and non-target fruits obstructing target fruits, as well as the alteration in color due to light, there is currently a low recognition rate and missed detection. We take the greenhouse tomato as the object of research. This paper proposes a tomato recognition model based on the improved YOLOv8 architecture to adapt to detecting tomato fruits in complex situations. First, to improve the model’s sensitivity to local features, we introduced an LSKA (Large Separable Kernel Attention) attention mechanism to aggregate feature information from different locations for better feature extraction. Secondly, to provide a higher quality upsampling effect, the ultra-lightweight and efficient dynamic upsampler Dysample (an ultra-lightweight and efficient dynamic upsampler) replaced the traditional nearest neighbor interpolation methods, which improves the overall performance of YOLOv8. Subsequently, the Inner-IoU function replaced the original CIoU loss function to hasten bounding box regression and raise model detection performance. Finally, the model test comparison was conducted on the self-built dataset, and the test results show that the mAP0.5 of the YOLOv8-Tomato model reached 99.4% and the recall rate reached 99.0%, which exceeds the original YOLOv8 model detection effect. Compared with faster R-CNN, SSD, YOLOv3-tiny, YOLOv5, and YOLOv8 models, the average accuracy is 7.5%, 11.6%, 8.6%, 3.3%, and 0.6% higher, respectively. This study demonstrates the model’s capacity to efficiently and accurately recognize tomatoes in unstructured growing environments, providing a technical reference for automated tomato harvesting.
{"title":"Tomato Recognition Method Based on the YOLOv8-Tomato Model in Complex Greenhouse Environments","authors":"Shuhe Zheng, Xuexin Jia, Minglei He, Zebin Zheng, Tianliang Lin, Wuxiong Weng","doi":"10.3390/agronomy14081764","DOIUrl":"https://doi.org/10.3390/agronomy14081764","url":null,"abstract":"Tomatoes are a critical economic crop. The realization of tomato harvesting automation is of great significance in solving the labor shortage and improving the efficiency of the current harvesting operation. Accurate recognition of fruits is the key to realizing automated harvesting. Harvesting fruit at optimum ripeness ensures the highest nutrient content, flavor and market value levels, thus maximizing economic benefits. Owing to foliage and non-target fruits obstructing target fruits, as well as the alteration in color due to light, there is currently a low recognition rate and missed detection. We take the greenhouse tomato as the object of research. This paper proposes a tomato recognition model based on the improved YOLOv8 architecture to adapt to detecting tomato fruits in complex situations. First, to improve the model’s sensitivity to local features, we introduced an LSKA (Large Separable Kernel Attention) attention mechanism to aggregate feature information from different locations for better feature extraction. Secondly, to provide a higher quality upsampling effect, the ultra-lightweight and efficient dynamic upsampler Dysample (an ultra-lightweight and efficient dynamic upsampler) replaced the traditional nearest neighbor interpolation methods, which improves the overall performance of YOLOv8. Subsequently, the Inner-IoU function replaced the original CIoU loss function to hasten bounding box regression and raise model detection performance. Finally, the model test comparison was conducted on the self-built dataset, and the test results show that the mAP0.5 of the YOLOv8-Tomato model reached 99.4% and the recall rate reached 99.0%, which exceeds the original YOLOv8 model detection effect. Compared with faster R-CNN, SSD, YOLOv3-tiny, YOLOv5, and YOLOv8 models, the average accuracy is 7.5%, 11.6%, 8.6%, 3.3%, and 0.6% higher, respectively. This study demonstrates the model’s capacity to efficiently and accurately recognize tomatoes in unstructured growing environments, providing a technical reference for automated tomato harvesting.","PeriodicalId":7601,"journal":{"name":"Agronomy","volume":"41 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141969114","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 : 2024-08-12DOI: 10.3390/agronomy14081763
Esengül Erdem
The Mediterranean Corn Borer (MCB), Sesamia nonagrioides, poses a significant threat to maize crops, necessitating effective pest management strategies. This study investigates the compatibility of two entomopathogenic nematode (EPN) isolates, Steinernema feltiae KV6 and Heterorhabditis bacteriophora EO7, with four registered insecticides for MCB control: deltamethrin, flubendiamide, spinetoram, and betacyfluthrin. The impact of these insecticides on EPN mortality, infectivity, and reproduction was assessed. Results indicate that deltamethrin exhibits the lowest toxicity to EPNs, with mortality rates of 1.3% for S. feltiae and 0.63% for H. bacteriophora at field dose (FD) after 24 h and 4.63% and 1.96%, respectively, after 48 h. In contrast, betacyfluthrin showed higher toxicity, with mortality rates of 38.04% and 14.17% for S. feltiae at 2FD and FD after 48 h. The infectivity assays demonstrated that deltamethrin-treated EPNs caused up to 100% mortality in MCB larvae, while the reproduction capacity varied significantly between the EPN species and insecticides. H. bacteriophora exhibited higher progeny production, especially in the presence of deltamethrin (87,900 IJs/larva). The findings suggest that integrating EPNs with selective insecticides like deltamethrin can enhance pest control efficacy and support sustainable agricultural practices. This study provides valuable insights for developing integrated pest management (IPM) strategies aimed at mitigating MCB infestations in maize while minimizing environmental impacts.
{"title":"Laboratory Evaluation of the Combine Usage Possibilities of Entomopathogenic Nematodes with Insecticides against Mediterranean Corn Borer Sesamia nonagrioides (Lefebvre)","authors":"Esengül Erdem","doi":"10.3390/agronomy14081763","DOIUrl":"https://doi.org/10.3390/agronomy14081763","url":null,"abstract":"The Mediterranean Corn Borer (MCB), Sesamia nonagrioides, poses a significant threat to maize crops, necessitating effective pest management strategies. This study investigates the compatibility of two entomopathogenic nematode (EPN) isolates, Steinernema feltiae KV6 and Heterorhabditis bacteriophora EO7, with four registered insecticides for MCB control: deltamethrin, flubendiamide, spinetoram, and betacyfluthrin. The impact of these insecticides on EPN mortality, infectivity, and reproduction was assessed. Results indicate that deltamethrin exhibits the lowest toxicity to EPNs, with mortality rates of 1.3% for S. feltiae and 0.63% for H. bacteriophora at field dose (FD) after 24 h and 4.63% and 1.96%, respectively, after 48 h. In contrast, betacyfluthrin showed higher toxicity, with mortality rates of 38.04% and 14.17% for S. feltiae at 2FD and FD after 48 h. The infectivity assays demonstrated that deltamethrin-treated EPNs caused up to 100% mortality in MCB larvae, while the reproduction capacity varied significantly between the EPN species and insecticides. H. bacteriophora exhibited higher progeny production, especially in the presence of deltamethrin (87,900 IJs/larva). The findings suggest that integrating EPNs with selective insecticides like deltamethrin can enhance pest control efficacy and support sustainable agricultural practices. This study provides valuable insights for developing integrated pest management (IPM) strategies aimed at mitigating MCB infestations in maize while minimizing environmental impacts.","PeriodicalId":7601,"journal":{"name":"Agronomy","volume":"78 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141939981","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}
A 2-year field experiment was conducted to test the effects of individual and co-application of biochar and inorganic fertilizer on soil quality using the principal component analysis (PCA) technique. The dry season field experiments were performed with biochar applied at 0 and 20 t ha−1, and fertilizer at 300 and 0 kg ha−1 (control). The factorial combinations of the above-mentioned treatments were subjected to irrigation at 60, 80, and 100% of irrigation amounts (IAs). Soil hydro-physical and chemical properties and grain yield were determined at harvest. Results from the PCA indicated that the soil total nitrogen (N) and moisture content (MC) were the soil properties mostly affecting the grain yield. The amendments’ effects on the soil physico-chemical properties and maize yield were in the order control < biochar < fertilizer < biochar + fertilizer. The derived comprehensive soil quality index (CSQI) from the PCA showed that the soil quality increased by 76, 100, and 200% in treatments individually applied with biochar, inorganic fertilizer, and the co-applications. This study therefore showed that the PCA revealed the actual dynamics in soil properties, in terms of the SQI upon the soil amendment addition, as well as their relationship with maize yield under different weather conditions.
{"title":"Evaluating Impacts of Biochar and Inorganic Fertilizer Applications on Soil Quality and Maize Yield Using Principal Component Analysis","authors":"Oluwaseun Temitope Faloye, Ayodele Ebenezer Ajayi, Viroon Kamchoom, Olayiwola Akin Akintola, Philip Gbenro Oguntunde","doi":"10.3390/agronomy14081761","DOIUrl":"https://doi.org/10.3390/agronomy14081761","url":null,"abstract":"A 2-year field experiment was conducted to test the effects of individual and co-application of biochar and inorganic fertilizer on soil quality using the principal component analysis (PCA) technique. The dry season field experiments were performed with biochar applied at 0 and 20 t ha−1, and fertilizer at 300 and 0 kg ha−1 (control). The factorial combinations of the above-mentioned treatments were subjected to irrigation at 60, 80, and 100% of irrigation amounts (IAs). Soil hydro-physical and chemical properties and grain yield were determined at harvest. Results from the PCA indicated that the soil total nitrogen (N) and moisture content (MC) were the soil properties mostly affecting the grain yield. The amendments’ effects on the soil physico-chemical properties and maize yield were in the order control < biochar < fertilizer < biochar + fertilizer. The derived comprehensive soil quality index (CSQI) from the PCA showed that the soil quality increased by 76, 100, and 200% in treatments individually applied with biochar, inorganic fertilizer, and the co-applications. This study therefore showed that the PCA revealed the actual dynamics in soil properties, in terms of the SQI upon the soil amendment addition, as well as their relationship with maize yield under different weather conditions.","PeriodicalId":7601,"journal":{"name":"Agronomy","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141939976","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 : 2024-08-12DOI: 10.3390/agronomy14081768
Agnė Buivydienė, Irena Deveikytė, Agnė Veršulienė, Virginijus Feiza
Conservation soil management strategies, particularly no-tillage and cropping strategies, have become an effective and widely adopted practice that has a direct influence on root parameters and mitigation of greenhouse gasses. However, the effect of different tillage and cropping strategies on root growth in field conditions is rarely studied. The study aimed to quantify and characterise the relationship between root network development and CO2 emission and how these parameters are affected by different cropping and tillage strategies. Five different crop rotations were tested, with or without the inclusion of catch crops (CC), by growing them in the soil where different tillage practices were applied. Selected cropping strategies differed among themselves in terms of the frequency of CC grown per rotation. The data revealed that in NT treatments, the CO2 emission (both autotrophic and heterotrophic simultaneously) was 25% higher than in CT. The cropping strategies were identified as an important factor influencing CO2 emissions. An increase in CO2 emission varied between 30 and 35% depending on the share of legume and CC inclusion. The frequency of CC grown per rotation has had an effect on the rate of CO2 emission. The cropping strategy when CC was grown every year showed the lowest amount of CO2 (by 26%), while in other cropping strategies, when CC was grown once or twice per rotation, significantly higher CO2 emissions were observed. Root growth and their development were significantly affected (p < 0.05) by soil depth and cropping strategies concerning root length and root volume changes. The inclusion of CC into the rotations led towards a decrease in root volume (by 21%). Root length (R2 = 0.45; p < 0.05) and root volume (R2 = 0.82; p < 0.05) had a significant impact on soil CO2 emissions. The results collected from 2021 to 2023 experiments indicated that cropping strategies and CC management areas are important tools not only for the improvement of root parameters but also for understanding how they affect CO2 emissions. The main message for stakeholders is that the cropping strategies diversification with the inclusion of CC every year in a winter oil-seed rape, spring wheat and pea crop rotation (R/W/P + CC) had demonstrated the possibilities to reduce CO2 emission and improve the root network parameters as compared to the monoculture strategy.
土壤保持管理策略，尤其是免耕和种植策略，已成为一种有效且被广泛采用的做法，对根系参数和温室气体减排有直接影响。然而，在田间条件下，不同耕作和种植策略对根系生长的影响却鲜有研究。本研究旨在量化和描述根系网络发展与二氧化碳排放之间的关系，以及这些参数如何受到不同种植和耕作策略的影响。通过在采用不同耕作方式的土壤中种植五种不同的轮作作物，测试了是否加入接茬作物（CC）。选定的耕作策略在每次轮作中种植 CC 的频率方面存在差异。数据显示，NT 处理的二氧化碳排放量（同时包括自养和异养）比 CT 处理高 25%。种植策略被认为是影响二氧化碳排放量的一个重要因素。根据豆科植物和 CC 的种植比例，CO2 排放量的增幅在 30% 到 35% 之间。每轮种植 CC 的频率对二氧化碳排放量有影响。在每年种植 CC 的种植策略中，二氧化碳排放量最低（26%），而在其他种植策略中，当每轮种植 CC 一到两次时，二氧化碳排放量明显较高。根的生长和发育受到土壤深度和种植策略的显著影响（p < 0.05），涉及根的长度和体积变化。在轮作中加入 CC 会导致根系体积减少（21%）。根长（R2 = 0.45；p < 0.05）和根量（R2 = 0.82；p < 0.05）对土壤二氧化碳排放量有显著影响。从 2021 年到 2023 年收集的实验结果表明，种植策略和 CC 管理区不仅是改善根系参数的重要工具，也是了解它们如何影响二氧化碳排放的重要工具。对利益相关者的主要启示是，与单一种植策略相比，在冬油菜、春小麦和豌豆轮作（R/W/P + CC）中每年加入 CC 的多样化种植策略证明了减少二氧化碳排放和改善根网参数的可能性。
{"title":"Tillage Practices Effect on Root Distribution and Variation of Soil CO2 Emission under Different Cropping Strategies","authors":"Agnė Buivydienė, Irena Deveikytė, Agnė Veršulienė, Virginijus Feiza","doi":"10.3390/agronomy14081768","DOIUrl":"https://doi.org/10.3390/agronomy14081768","url":null,"abstract":"Conservation soil management strategies, particularly no-tillage and cropping strategies, have become an effective and widely adopted practice that has a direct influence on root parameters and mitigation of greenhouse gasses. However, the effect of different tillage and cropping strategies on root growth in field conditions is rarely studied. The study aimed to quantify and characterise the relationship between root network development and CO2 emission and how these parameters are affected by different cropping and tillage strategies. Five different crop rotations were tested, with or without the inclusion of catch crops (CC), by growing them in the soil where different tillage practices were applied. Selected cropping strategies differed among themselves in terms of the frequency of CC grown per rotation. The data revealed that in NT treatments, the CO2 emission (both autotrophic and heterotrophic simultaneously) was 25% higher than in CT. The cropping strategies were identified as an important factor influencing CO2 emissions. An increase in CO2 emission varied between 30 and 35% depending on the share of legume and CC inclusion. The frequency of CC grown per rotation has had an effect on the rate of CO2 emission. The cropping strategy when CC was grown every year showed the lowest amount of CO2 (by 26%), while in other cropping strategies, when CC was grown once or twice per rotation, significantly higher CO2 emissions were observed. Root growth and their development were significantly affected (p < 0.05) by soil depth and cropping strategies concerning root length and root volume changes. The inclusion of CC into the rotations led towards a decrease in root volume (by 21%). Root length (R2 = 0.45; p < 0.05) and root volume (R2 = 0.82; p < 0.05) had a significant impact on soil CO2 emissions. The results collected from 2021 to 2023 experiments indicated that cropping strategies and CC management areas are important tools not only for the improvement of root parameters but also for understanding how they affect CO2 emissions. The main message for stakeholders is that the cropping strategies diversification with the inclusion of CC every year in a winter oil-seed rape, spring wheat and pea crop rotation (R/W/P + CC) had demonstrated the possibilities to reduce CO2 emission and improve the root network parameters as compared to the monoculture strategy.","PeriodicalId":7601,"journal":{"name":"Agronomy","volume":"50 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141939987","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 : 2024-08-12DOI: 10.3390/agronomy14081762
Maria Duk, Alexander Kanapin, Ekaterina Orlova, Maria Samsonova
Chickpea is a staple crop for many nations worldwide. Modeling genotype-by-environment interactions and assessing the genotype’s ability to contribute adaptive alleles are crucial for chickpea breeding. In this study, we evaluated 12 agronomically important traits of 159 accessions from the N.I. Vavilov All Russian Institute for Plant Genetic Resources collection. These included 145 landraces and 13 cultivars grown in different climatic conditions in Kuban (45°18′ N and 40°52′ E) in both 2016 and 2022, as well as in Astrakhan (46°06′ N and 48°04′ E) in 2022. Using the IIIVmrMLM model in multi-environmental mode, we identified 161 quantitative trait nucleotides (QTNs) with stable genetic effects across different environments. Furthermore, we have observed 254 QTN-by-environment interactions with distinct environment-specific effects. Notably, five of these interactions manifested large effects, with R2 values exceeding 10%, while the highest R2 value for stable QTNs was 4.7%. Within the protein-coding genes and their 1 Kb flanking regions, we have discerned 22 QTNs and 45 QTN-by-environment interactions, most likely tagging the candidate causal genes. The landraces obtained from the N.I Vavilov All Russian Institute for Plant Genetic Resources collection exhibit numerous favorable alleles at quantitative trait nucleotide loci, showing stable effects in the Kuban and Astrakhan regions. Additionally, they possessed a significantly higher number of Kuban-specific favorable alleles of the QTN-by-environment interaction loci compared to the Astrakhan-specific ones. The environment-specific alleles found at the QTN-by-environment interaction loci have the potential to enhance chickpea adaptation to specific climatic conditions.
{"title":"IIIVmrMLM Provides New Insights into the Genetic Basis of the Agronomic Trait Variation in Chickpea","authors":"Maria Duk, Alexander Kanapin, Ekaterina Orlova, Maria Samsonova","doi":"10.3390/agronomy14081762","DOIUrl":"https://doi.org/10.3390/agronomy14081762","url":null,"abstract":"Chickpea is a staple crop for many nations worldwide. Modeling genotype-by-environment interactions and assessing the genotype’s ability to contribute adaptive alleles are crucial for chickpea breeding. In this study, we evaluated 12 agronomically important traits of 159 accessions from the N.I. Vavilov All Russian Institute for Plant Genetic Resources collection. These included 145 landraces and 13 cultivars grown in different climatic conditions in Kuban (45°18′ N and 40°52′ E) in both 2016 and 2022, as well as in Astrakhan (46°06′ N and 48°04′ E) in 2022. Using the IIIVmrMLM model in multi-environmental mode, we identified 161 quantitative trait nucleotides (QTNs) with stable genetic effects across different environments. Furthermore, we have observed 254 QTN-by-environment interactions with distinct environment-specific effects. Notably, five of these interactions manifested large effects, with R2 values exceeding 10%, while the highest R2 value for stable QTNs was 4.7%. Within the protein-coding genes and their 1 Kb flanking regions, we have discerned 22 QTNs and 45 QTN-by-environment interactions, most likely tagging the candidate causal genes. The landraces obtained from the N.I Vavilov All Russian Institute for Plant Genetic Resources collection exhibit numerous favorable alleles at quantitative trait nucleotide loci, showing stable effects in the Kuban and Astrakhan regions. Additionally, they possessed a significantly higher number of Kuban-specific favorable alleles of the QTN-by-environment interaction loci compared to the Astrakhan-specific ones. The environment-specific alleles found at the QTN-by-environment interaction loci have the potential to enhance chickpea adaptation to specific climatic conditions.","PeriodicalId":7601,"journal":{"name":"Agronomy","volume":"95 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141939980","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}
The arid and semi-arid region of Northwest China plays a significant role in potato production, yet yields are often hampered by drought due to limited precipitation and irrigation water. The ridge–furrow rainwater-harvesting technology is an efficient and widely used technique to relieve drought impact and improve crop yield by changing the micro-topography to harvest rainwater to meet the water demand of crops. An analysis of precipitation, water demand, and runoff data spanning 30 years guided the selection of suitable rainwater-harvesting methods tailored to meteorological conditions. The results showed that potato water demand exceeded precipitation in the region. The mulching approach performed best in the western arid region with the most significant increase in yield and water use efficiency (WUE) and was suitable for the western semi-arid region and the agro-pastoral ecotone. In the potato dryland farming areas, the water deficit increased from southeast to northwest. Specifically, northern Gansu, northern Ningxia, and midwestern Inner Mongolia experienced a water deficit of over 200 mm, and rainwater harvesting combined with irrigation was recommended. Conversely, regarding deficits below 200 mm in southern Gansu, Ningxia, and central Inner Mongolia, a 1:1 or 2:1 pattern of ridges could be applied, and mulching was needed only in the necessary areas. For the southern Qinghai, Shaanxi, and eastern Inner Mongolia regions, ridge–furrow rainwater harvesting could be replaced by flat potato cropping. In summary, rainwater harvesting addresses water deficits, aiding climate adaptation in Northwest China’s arid and semi-arid regions. The implementation of mulching and ridge–furrow technology must be location-specific.
{"title":"Optimizing Ridge–Furrow Rainwater-Harvesting Strategies for Potato Cultivation in the Drylands of Northwestern China: A Regional Approach","authors":"Lina Zhang, Siqi Ren, Feifei Pan, Jianshuo Zhou, Jingyan Jiang, Xuebiao Pan, Jing Wang, Baoru Sun, Qi Hu","doi":"10.3390/agronomy14081759","DOIUrl":"https://doi.org/10.3390/agronomy14081759","url":null,"abstract":"The arid and semi-arid region of Northwest China plays a significant role in potato production, yet yields are often hampered by drought due to limited precipitation and irrigation water. The ridge–furrow rainwater-harvesting technology is an efficient and widely used technique to relieve drought impact and improve crop yield by changing the micro-topography to harvest rainwater to meet the water demand of crops. An analysis of precipitation, water demand, and runoff data spanning 30 years guided the selection of suitable rainwater-harvesting methods tailored to meteorological conditions. The results showed that potato water demand exceeded precipitation in the region. The mulching approach performed best in the western arid region with the most significant increase in yield and water use efficiency (WUE) and was suitable for the western semi-arid region and the agro-pastoral ecotone. In the potato dryland farming areas, the water deficit increased from southeast to northwest. Specifically, northern Gansu, northern Ningxia, and midwestern Inner Mongolia experienced a water deficit of over 200 mm, and rainwater harvesting combined with irrigation was recommended. Conversely, regarding deficits below 200 mm in southern Gansu, Ningxia, and central Inner Mongolia, a 1:1 or 2:1 pattern of ridges could be applied, and mulching was needed only in the necessary areas. For the southern Qinghai, Shaanxi, and eastern Inner Mongolia regions, ridge–furrow rainwater harvesting could be replaced by flat potato cropping. In summary, rainwater harvesting addresses water deficits, aiding climate adaptation in Northwest China’s arid and semi-arid regions. The implementation of mulching and ridge–furrow technology must be location-specific.","PeriodicalId":7601,"journal":{"name":"Agronomy","volume":"45 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141939895","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}
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