Pub Date : 2023-09-08DOI: 10.3390/agronomy13092341
Karla E. Zarco-González, J. D. Valle-García, Yendi E. Navarro-Noya, Fabián Fernández-Luqueño, Luc Dendooven
The amount of nanoparticles that enters the environment has increased substantially in the last years. How they might affect plant characteristics and the bacterial community structure when they enter the soil, however, is still debated, as there is a continuous interaction between them. In this study, we determined the effect of silver (Ag-NPs) and hematite (α-Fe2O3-NPs) nanoparticles (0.15 g kg−1) on the characteristics of common bean (Phaseolus vulgaris L.) and the rhizosphere, non-rhizosphere and uncultivated soil bacterial community. The application of Ag-NPs or α-Fe2O3-NPs did not affect plant growth but changed the amount of some heavy metals in the roots and aerial parts. The application of nanoparticles had a limited effect on the diversity, structure and functional profile of the soil and rhizosphere bacterial communities, but they were altered by cultivation of the bean plants and changed over time. It was found that application of Ag-NPs or α-Fe2O3-NPs had no effect on bean plant growth and only a small effect on the bacterial community structure and its putative metabolic functions. These findings show that in a complex system, such as a soil, different factors might affect the bacterial community structure and alter the possible effect of nanoparticles on it.
在过去的几年里，进入环境的纳米颗粒的数量大幅增加。然而，当它们进入土壤时，它们如何影响植物特性和细菌群落结构，仍然存在争议，因为它们之间存在持续的相互作用。研究了银(Ag-NPs)和赤铁矿(α-Fe2O3-NPs)纳米颗粒(0.15 g kg−1)对菜豆(Phaseolus vulgaris L.)及根际、非根际和未开垦土壤细菌群落特征的影响。Ag-NPs和α-Fe2O3-NPs的施用不影响植株生长，但改变了根系和地上部分重金属的含量。施用纳米颗粒对土壤和根际细菌群落的多样性、结构和功能特征的影响有限，但它们会随着豆类植物的种植而改变，并随着时间的推移而改变。结果表明，施用Ag-NPs或α-Fe2O3-NPs对大豆植株生长无明显影响，对细菌群落结构及其代谢功能影响较小。这些发现表明，在土壤等复杂系统中，不同的因素可能会影响细菌群落结构，并改变纳米颗粒对其可能产生的影响。
{"title":"Silver and Hematite Nanoparticles Had a Limited Effect on the Bacterial Community Structure in Soil Cultivated with Phaseolus vulgaris L.","authors":"Karla E. Zarco-González, J. D. Valle-García, Yendi E. Navarro-Noya, Fabián Fernández-Luqueño, Luc Dendooven","doi":"10.3390/agronomy13092341","DOIUrl":"https://doi.org/10.3390/agronomy13092341","url":null,"abstract":"The amount of nanoparticles that enters the environment has increased substantially in the last years. How they might affect plant characteristics and the bacterial community structure when they enter the soil, however, is still debated, as there is a continuous interaction between them. In this study, we determined the effect of silver (Ag-NPs) and hematite (α-Fe2O3-NPs) nanoparticles (0.15 g kg−1) on the characteristics of common bean (Phaseolus vulgaris L.) and the rhizosphere, non-rhizosphere and uncultivated soil bacterial community. The application of Ag-NPs or α-Fe2O3-NPs did not affect plant growth but changed the amount of some heavy metals in the roots and aerial parts. The application of nanoparticles had a limited effect on the diversity, structure and functional profile of the soil and rhizosphere bacterial communities, but they were altered by cultivation of the bean plants and changed over time. It was found that application of Ag-NPs or α-Fe2O3-NPs had no effect on bean plant growth and only a small effect on the bacterial community structure and its putative metabolic functions. These findings show that in a complex system, such as a soil, different factors might affect the bacterial community structure and alter the possible effect of nanoparticles on it.","PeriodicalId":56066,"journal":{"name":"Agronomy-Basel","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48356174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Recognition and localization of fruits are key components to achieve automated fruit picking. However, current neural-network-based fruit recognition algorithms have disadvantages such as high complexity. Traditional stereo matching algorithms also have low accuracy. To solve these problems, this study targeting greenhouse tomatoes proposed an algorithm framework based on YOLO-TomatoSeg, a lightweight tomato instance segmentation model improved from YOLOv5n-seg, and an accurate tomato localization approach using RAFT-Stereo disparity estimation and least squares point cloud fitting. First, binocular tomato images were captured using a binocular camera system. The left image was processed by YOLO-TomatoSeg to segment tomato instances and generate masks. Concurrently, RAFT-Stereo estimated image disparity for computing the original depth point cloud. Then, the point cloud was clipped by tomato masks to isolate tomato point clouds, which were further preprocessed. Finally, a least squares sphere fitting method estimated the 3D centroid co-ordinates and radii of tomatoes by fitting the tomato point clouds to spherical models. The experimental results showed that, in the tomato instance segmentation stage, the YOLO-TomatoSeg model replaced the Backbone network of YOLOv5n-seg with the building blocks of ShuffleNetV2 and incorporated an SE attention module, which reduced model complexity while improving model segmentation accuracy. Ultimately, the YOLO-TomatoSeg model achieved an AP of 99.01% with a size of only 2.52 MB, significantly outperforming mainstream instance segmentation models such as Mask R-CNN (98.30% AP) and YOLACT (96.49% AP). The model size was reduced by 68.3% compared to the original YOLOv5n-seg model. In the tomato localization stage, at the range of 280 mm to 480 mm, the average error of the tomato centroid localization was affected by occlusion and sunlight conditions. The maximum average localization error was ±5.0 mm, meeting the localization accuracy requirements of the tomato-picking robots. This study developed a lightweight tomato instance segmentation model and achieved accurate localization of tomato, which can facilitate research, development, and application of fruit-picking robots.
{"title":"Tomato Recognition and Localization Method Based on Improved YOLOv5n-seg Model and Binocular Stereo Vision","authors":"Shuhe Zheng, Yang Liu, Wuxiong Weng, Xuexin Jia, Shilong Yu, Zuoxun Wu","doi":"10.3390/agronomy13092339","DOIUrl":"https://doi.org/10.3390/agronomy13092339","url":null,"abstract":"Recognition and localization of fruits are key components to achieve automated fruit picking. However, current neural-network-based fruit recognition algorithms have disadvantages such as high complexity. Traditional stereo matching algorithms also have low accuracy. To solve these problems, this study targeting greenhouse tomatoes proposed an algorithm framework based on YOLO-TomatoSeg, a lightweight tomato instance segmentation model improved from YOLOv5n-seg, and an accurate tomato localization approach using RAFT-Stereo disparity estimation and least squares point cloud fitting. First, binocular tomato images were captured using a binocular camera system. The left image was processed by YOLO-TomatoSeg to segment tomato instances and generate masks. Concurrently, RAFT-Stereo estimated image disparity for computing the original depth point cloud. Then, the point cloud was clipped by tomato masks to isolate tomato point clouds, which were further preprocessed. Finally, a least squares sphere fitting method estimated the 3D centroid co-ordinates and radii of tomatoes by fitting the tomato point clouds to spherical models. The experimental results showed that, in the tomato instance segmentation stage, the YOLO-TomatoSeg model replaced the Backbone network of YOLOv5n-seg with the building blocks of ShuffleNetV2 and incorporated an SE attention module, which reduced model complexity while improving model segmentation accuracy. Ultimately, the YOLO-TomatoSeg model achieved an AP of 99.01% with a size of only 2.52 MB, significantly outperforming mainstream instance segmentation models such as Mask R-CNN (98.30% AP) and YOLACT (96.49% AP). The model size was reduced by 68.3% compared to the original YOLOv5n-seg model. In the tomato localization stage, at the range of 280 mm to 480 mm, the average error of the tomato centroid localization was affected by occlusion and sunlight conditions. The maximum average localization error was ±5.0 mm, meeting the localization accuracy requirements of the tomato-picking robots. This study developed a lightweight tomato instance segmentation model and achieved accurate localization of tomato, which can facilitate research, development, and application of fruit-picking robots.","PeriodicalId":56066,"journal":{"name":"Agronomy-Basel","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43205225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-08DOI: 10.3390/agronomy13092338
Mingyang Qin, Yu Jin, Mingzhu Cao, Feng Wu, Weiwen Luo, Kai Guo, Hongbo Xu, Fengwei Gu, Zhichao Hu
This study proposes a negative-pressure fruit-soil separating device for peanuts cultivated in hilly and mountainous areas after combined harvesting, and the mechanism of the movement of the material in the process of material screening, fruit-soil separating, and pneumatic conveying of the device was analyzed. In addition, a four-factor, three-level Box-Behnken regression design test was used to explore the optimum operating parameters of the peanut fruit-soil separation device. The results showed that the best fruit-soil separation effect was achieved when the wind speed of the blower was 13.58 m/s, the height of the suction nozzle from the screen surface was 27 mm, the length of the suction port was 64 mm, and the feeding rate was 600 kg/h. Validation tests demonstrated that the impurity rate of 0.16% and the peanut pod loss rate of 0.2% exceeded the industry standard, indicating superior performance.
{"title":"Design and Parameter Optimization of a Negative-Pressure Peanut Fruit-Soil Separating Device","authors":"Mingyang Qin, Yu Jin, Mingzhu Cao, Feng Wu, Weiwen Luo, Kai Guo, Hongbo Xu, Fengwei Gu, Zhichao Hu","doi":"10.3390/agronomy13092338","DOIUrl":"https://doi.org/10.3390/agronomy13092338","url":null,"abstract":"This study proposes a negative-pressure fruit-soil separating device for peanuts cultivated in hilly and mountainous areas after combined harvesting, and the mechanism of the movement of the material in the process of material screening, fruit-soil separating, and pneumatic conveying of the device was analyzed. In addition, a four-factor, three-level Box-Behnken regression design test was used to explore the optimum operating parameters of the peanut fruit-soil separation device. The results showed that the best fruit-soil separation effect was achieved when the wind speed of the blower was 13.58 m/s, the height of the suction nozzle from the screen surface was 27 mm, the length of the suction port was 64 mm, and the feeding rate was 600 kg/h. Validation tests demonstrated that the impurity rate of 0.16% and the peanut pod loss rate of 0.2% exceeded the industry standard, indicating superior performance.","PeriodicalId":56066,"journal":{"name":"Agronomy-Basel","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42249983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lack of soil moisture and phosphorus deficiency limits wheat grain yield in dryland areas. However, the moisture-conserving effect of straw mulching combined with phosphor fertilization on fertile florets per spike (FFS) and grain yield remains unclear. During the 2020–2021 and 2021–2022 growing seasons, we investigated the combined effects of straw mulching (0 and 8000 kg ha−1) and phosphorus fertilization (0, 75, and 120 kg P2O5 ha−1) on spike development, assimilates’ availability, and the photosynthetic properties of flag leaves by conducting a field experiment. Compared with no straw mulch control, straw mulching increased fertile spike, grain number per spike (15.6%), and grain yield (22.6%), and grain number per spike was the most important contribution to increasing wheat grain yield (46%). An increase in grain number per spike is associated with FFS. Compared with no straw mulch control, straw mulching increased FFS by 19.5%, and it increased with increasing phosphorus fertilization levels. Moreover, straw mulching combined with phosphorus fertilization promoted the light compensation point (LCP), light saturation point (LSP), net photosynthetic rate (Pn), Chl b, and the maximal photochemical efficiency of photosystem II (Fv/Fm) of flag leaves to produce carbohydrates. Our study has shown that the primary factor for the divergence in FFS under straw mulching and phosphorus application was the efficiency of assimilate utilization in the spike, which ultimately led to increased grain number per spike and grain yield.
干旱地区缺乏土壤水分和缺磷限制了小麦的产量。然而，秸秆覆盖结合磷肥对每穗可育小花（FFS）和粮食产量的保水效果尚不清楚。在2020-2021和2021-2022生长季节，我们通过田间试验研究了秸秆覆盖（0和8000 kg ha−1）和磷施肥（0、75和120 kg P2O5 ha−1。与无秸秆覆盖对照相比，秸秆覆盖增加了可育穗数、穗粒数（15.6%）和粮食产量（22.6%），穗粒数对小麦产量的贡献最大（46%）。每穗粒数的增加与自由流速度有关。与无秸秆覆盖对照相比，秸秆覆盖使FFS增加了19.5%，并且随着施磷水平的增加而增加。此外，秸秆覆盖与磷肥相结合促进了旗叶的光补偿点（LCP）、光饱和点（LSP）、净光合速率（Pn）、叶绿素b和光系统II最大光化学效率（Fv/Fm）产生碳水化合物。我们的研究表明，秸秆覆盖和施磷条件下自由流速度差异的主要因素是穗部同化物利用效率，这最终导致穗粒数和产量的增加。
{"title":"Straw Mulching Combined with Phosphorus Fertilizer Increases Fertile Florets of Wheat by Enhancing Leaf Photosynthesis and Assimilate Utilization","authors":"Wei Xie, Peng He, Hongliang Ma, Xiulan Huang, Gaoqiong Fan, Hongkun Yang","doi":"10.3390/agronomy13092342","DOIUrl":"https://doi.org/10.3390/agronomy13092342","url":null,"abstract":"Lack of soil moisture and phosphorus deficiency limits wheat grain yield in dryland areas. However, the moisture-conserving effect of straw mulching combined with phosphor fertilization on fertile florets per spike (FFS) and grain yield remains unclear. During the 2020–2021 and 2021–2022 growing seasons, we investigated the combined effects of straw mulching (0 and 8000 kg ha−1) and phosphorus fertilization (0, 75, and 120 kg P2O5 ha−1) on spike development, assimilates’ availability, and the photosynthetic properties of flag leaves by conducting a field experiment. Compared with no straw mulch control, straw mulching increased fertile spike, grain number per spike (15.6%), and grain yield (22.6%), and grain number per spike was the most important contribution to increasing wheat grain yield (46%). An increase in grain number per spike is associated with FFS. Compared with no straw mulch control, straw mulching increased FFS by 19.5%, and it increased with increasing phosphorus fertilization levels. Moreover, straw mulching combined with phosphorus fertilization promoted the light compensation point (LCP), light saturation point (LSP), net photosynthetic rate (Pn), Chl b, and the maximal photochemical efficiency of photosystem II (Fv/Fm) of flag leaves to produce carbohydrates. Our study has shown that the primary factor for the divergence in FFS under straw mulching and phosphorus application was the efficiency of assimilate utilization in the spike, which ultimately led to increased grain number per spike and grain yield.","PeriodicalId":56066,"journal":{"name":"Agronomy-Basel","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42114796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-08DOI: 10.3390/agronomy13092340
Ricardo Israel Ramírez-Gottfried, P. Preciado-Rangel, Mario García Carrillo, Alain Buendía García, Gabriela González-Rodríguez, Bernardo Espinosa-Palomeque
A variety of research reports that compost tea controls plant pathogens and improves plant nutrition and plant growth. Therefore, it can be used to reduce the use of synthetic fertilizers and pesticides. The aim of the study was to characterize and quantify the scientific production in the SCOPUS database on compost tea using bibliometric indicators. A total of 285 published papers related to compost tea were identified. The results show a general increasing trend from 2001 to 2023, with the highest number of publications occurring in 2021. Most of the publications were in the form of original articles, and English was the main language of publication. The top 10 countries with the highest scientific productivity were the United States, Egypt, Spain, Canada, Italy, India, China, Australia, Iran and Malaysia. Zaccardelli, M. and Pane, C. were the authors with the highest productivity with nine articles. In the co-authorship networks, two main networks were registered: the first with Diáñez F., together with Gea F. J., Navarro M.Y. and Santo M., and the second with Zaccardelli M., Celono G., and Pane C. Therefore, the need to adapt more resilient agricultural production systems allows for the consideration of compost tea as an alternative to mitigate environmental problems and soil degradation.
{"title":"Compost Tea as Organic Fertilizer and Plant Disease Control: Bibliometric Analysis","authors":"Ricardo Israel Ramírez-Gottfried, P. Preciado-Rangel, Mario García Carrillo, Alain Buendía García, Gabriela González-Rodríguez, Bernardo Espinosa-Palomeque","doi":"10.3390/agronomy13092340","DOIUrl":"https://doi.org/10.3390/agronomy13092340","url":null,"abstract":"A variety of research reports that compost tea controls plant pathogens and improves plant nutrition and plant growth. Therefore, it can be used to reduce the use of synthetic fertilizers and pesticides. The aim of the study was to characterize and quantify the scientific production in the SCOPUS database on compost tea using bibliometric indicators. A total of 285 published papers related to compost tea were identified. The results show a general increasing trend from 2001 to 2023, with the highest number of publications occurring in 2021. Most of the publications were in the form of original articles, and English was the main language of publication. The top 10 countries with the highest scientific productivity were the United States, Egypt, Spain, Canada, Italy, India, China, Australia, Iran and Malaysia. Zaccardelli, M. and Pane, C. were the authors with the highest productivity with nine articles. In the co-authorship networks, two main networks were registered: the first with Diáñez F., together with Gea F. J., Navarro M.Y. and Santo M., and the second with Zaccardelli M., Celono G., and Pane C. Therefore, the need to adapt more resilient agricultural production systems allows for the consideration of compost tea as an alternative to mitigate environmental problems and soil degradation.","PeriodicalId":56066,"journal":{"name":"Agronomy-Basel","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46295422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Plant viruses can infect various types of plants, including food and oil crops, and ornamental flowers, threatening agricultural production and food supply. Cross-protection is an efficient strategy against severe viral strains. Due to distinct infection mechanisms, cross-protection cases involving RNA viruses and DNA viruses often rely on the utilization of corresponding attenuated strains for control purposes. In this study, we utilized cucumber mosaic virus (CMV), a member of the RNA virus group, as the foundational framework for developing attenuated vaccines. We developed four vaccines by inserting relevant sequences from tomato yellow leaf curl virus (TYLCV), a DNA virus. All vaccines demonstrated effective prevention against TYLCV infection, with relative control efficacies exceeding 80%. Subsequently, we evaluated the preventive effects of these vaccines on mixed infections of CMV and TYLCV. Our findings demonstrated that CMV (R2-2bPTI-TYC1C4), CMV (R2-2bPTII-TYC1C4), and CMV (R2-2bPTIII-TYRep) displayed significant efficacy in preventing mixed infections. Following pre-inoculation with these vaccines, the disease index of tomato plants decreased from 100 to 56. This work provides theoretical foundations and tangible resources for controlling TYLCV through cross-protection while suggesting a feasible strategy for utilizing weak RNA virus vaccines to control DNA viruses.
{"title":"A New Strategy of Cross-Protection Based on Attenuated Vaccines: RNA Viruses Are Used as Vectors to Control DNA Viruses","authors":"Mingjing Zhu, Shanshan Liu, Zhao Wang, Chengming Yu, Xuefeng Yuan","doi":"10.3390/agronomy13092334","DOIUrl":"https://doi.org/10.3390/agronomy13092334","url":null,"abstract":"Plant viruses can infect various types of plants, including food and oil crops, and ornamental flowers, threatening agricultural production and food supply. Cross-protection is an efficient strategy against severe viral strains. Due to distinct infection mechanisms, cross-protection cases involving RNA viruses and DNA viruses often rely on the utilization of corresponding attenuated strains for control purposes. In this study, we utilized cucumber mosaic virus (CMV), a member of the RNA virus group, as the foundational framework for developing attenuated vaccines. We developed four vaccines by inserting relevant sequences from tomato yellow leaf curl virus (TYLCV), a DNA virus. All vaccines demonstrated effective prevention against TYLCV infection, with relative control efficacies exceeding 80%. Subsequently, we evaluated the preventive effects of these vaccines on mixed infections of CMV and TYLCV. Our findings demonstrated that CMV (R2-2bPTI-TYC1C4), CMV (R2-2bPTII-TYC1C4), and CMV (R2-2bPTIII-TYRep) displayed significant efficacy in preventing mixed infections. Following pre-inoculation with these vaccines, the disease index of tomato plants decreased from 100 to 56. This work provides theoretical foundations and tangible resources for controlling TYLCV through cross-protection while suggesting a feasible strategy for utilizing weak RNA virus vaccines to control DNA viruses.","PeriodicalId":56066,"journal":{"name":"Agronomy-Basel","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46066059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-07DOI: 10.3390/agronomy13092333
Yang Xu, Fan Yan, Zhengwei Liang, Ying Wang, Jingwen Li, Lei Zhao, Xuguang Yang, Qingyu Wang, Jingya Liu
Soybean (Glycine max) is the main oilseed crop that provides vegetable oil for human nutrition. The main objective of its breeding research is to increase the total oil content. In the Kennedy pathway, Diacylglycerol acyltransferase (DGAT) is a rate-limiting enzyme that converts diacylglycerol (DAG) to triacylglycerol (TAG). Here, the AhDGAT3 gene was cloned from peanut and overexpressed in the wild-type (WT) Arabidopsis. The total fatty acid content in T3AhDGAT3 transgenic Arabidopsis seeds was 1.1 times higher on average than that of the WT. Therefore, AhDGAT3 was transferred into the WT (JACK), and four T3 transgenic soybean lines were obtained, which proved to be positive using molecular biological detection. Specific T-DNA insertion region location information was also obtained via genome re-sequencing. The results of high-performance gas chromatography showed that the contents of oleic acid (18:1) composition and total fatty acids in transgenic soybean plants were significantly higher than that of the WT. However, linoleic acid (18:2) was much lower compared to the WT. The agronomic trait survey showed that the quantitative and yield traits of AhDGAT3 transgenic soybean were better than those of the WT. These results suggest that fatty acids in transgenic soybeans, especially oleic acid and total fatty acid, are enhanced by the over-expression of AhDGAT3.
{"title":"Overexpression of the Peanut AhDGAT3 Gene Increases the Oil Content in Soybean","authors":"Yang Xu, Fan Yan, Zhengwei Liang, Ying Wang, Jingwen Li, Lei Zhao, Xuguang Yang, Qingyu Wang, Jingya Liu","doi":"10.3390/agronomy13092333","DOIUrl":"https://doi.org/10.3390/agronomy13092333","url":null,"abstract":"Soybean (Glycine max) is the main oilseed crop that provides vegetable oil for human nutrition. The main objective of its breeding research is to increase the total oil content. In the Kennedy pathway, Diacylglycerol acyltransferase (DGAT) is a rate-limiting enzyme that converts diacylglycerol (DAG) to triacylglycerol (TAG). Here, the AhDGAT3 gene was cloned from peanut and overexpressed in the wild-type (WT) Arabidopsis. The total fatty acid content in T3AhDGAT3 transgenic Arabidopsis seeds was 1.1 times higher on average than that of the WT. Therefore, AhDGAT3 was transferred into the WT (JACK), and four T3 transgenic soybean lines were obtained, which proved to be positive using molecular biological detection. Specific T-DNA insertion region location information was also obtained via genome re-sequencing. The results of high-performance gas chromatography showed that the contents of oleic acid (18:1) composition and total fatty acids in transgenic soybean plants were significantly higher than that of the WT. However, linoleic acid (18:2) was much lower compared to the WT. The agronomic trait survey showed that the quantitative and yield traits of AhDGAT3 transgenic soybean were better than those of the WT. These results suggest that fatty acids in transgenic soybeans, especially oleic acid and total fatty acid, are enhanced by the over-expression of AhDGAT3.","PeriodicalId":56066,"journal":{"name":"Agronomy-Basel","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45782138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Water scarcity poses a formidable challenge to agricultural productivity in arid regions, and water retention agents offer promising potential in this regard. Therefore, this study proposes developing and preparing polymers with water retention properties using waste green algae as raw material to explore the effectiveness of enhanced water infiltration and reduce evaporation at different use levels (0%, 0.15%, 0.30%, 0.45% and 0.60%) and maximum mixing depths (10 cm, 20 cm, 30 cm, 40 cm and 50 cm) and determine the optimum management. The results demonstrate that the synthesized polymers exhibited a remarkable swelling rate of 143.6 g/g, along with reusability and excellent temperature stability. The polymer application rate was positively correlated with infiltration duration, with an increase from 161 min to 750 min as the application rate rose from 0% to 0.60%. Concurrently, cumulative infiltration increased from 22.6 cm to 31.1 cm, showcasing the benefits of the polymer in enhancing water retention. Intriguingly, cumulative evapotranspiration initially decreased and then increased with increasing polymer application rates. Moreover, increasing the maximum mixing depth from 10 to 50 cm while maintaining the 0.3% application rate increased the cumulative infiltration (from 22.6 cm to 31.1 cm) and infiltration rate (from 0.03 cm/min to 0.08 cm/min) while decreasing the cumulative evaporation (from 44.4 mm to 31.7 mm). Considering the cumulative infiltration, infiltration rate and evapotranspiration characteristics, an optimized polymer application rate of 0.27% at a mixing depth of 0–50 cm was recommended for efficient soil moisture management. This study highlights the potential of green algae-derived biodegradable polymers as a win–win strategy for achieving waste alleviation of water scarcity in drylands, particularly for maize and wheat cultivation in northern China.
{"title":"Enhanced Soil Moisture Management Using Waste Green Algae-Derived Polymers: Optimization of Application Rate and Mixing Depth","authors":"Zijian He, Jiaping Liang, Yanwei Lu, Qiliang Yang, Chengmei Lu, Die Wu","doi":"10.3390/agronomy13092335","DOIUrl":"https://doi.org/10.3390/agronomy13092335","url":null,"abstract":"Water scarcity poses a formidable challenge to agricultural productivity in arid regions, and water retention agents offer promising potential in this regard. Therefore, this study proposes developing and preparing polymers with water retention properties using waste green algae as raw material to explore the effectiveness of enhanced water infiltration and reduce evaporation at different use levels (0%, 0.15%, 0.30%, 0.45% and 0.60%) and maximum mixing depths (10 cm, 20 cm, 30 cm, 40 cm and 50 cm) and determine the optimum management. The results demonstrate that the synthesized polymers exhibited a remarkable swelling rate of 143.6 g/g, along with reusability and excellent temperature stability. The polymer application rate was positively correlated with infiltration duration, with an increase from 161 min to 750 min as the application rate rose from 0% to 0.60%. Concurrently, cumulative infiltration increased from 22.6 cm to 31.1 cm, showcasing the benefits of the polymer in enhancing water retention. Intriguingly, cumulative evapotranspiration initially decreased and then increased with increasing polymer application rates. Moreover, increasing the maximum mixing depth from 10 to 50 cm while maintaining the 0.3% application rate increased the cumulative infiltration (from 22.6 cm to 31.1 cm) and infiltration rate (from 0.03 cm/min to 0.08 cm/min) while decreasing the cumulative evaporation (from 44.4 mm to 31.7 mm). Considering the cumulative infiltration, infiltration rate and evapotranspiration characteristics, an optimized polymer application rate of 0.27% at a mixing depth of 0–50 cm was recommended for efficient soil moisture management. This study highlights the potential of green algae-derived biodegradable polymers as a win–win strategy for achieving waste alleviation of water scarcity in drylands, particularly for maize and wheat cultivation in northern China.","PeriodicalId":56066,"journal":{"name":"Agronomy-Basel","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46791288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-07DOI: 10.3390/agronomy13092337
Yue Yu, Haiye Yu, Xiaokai Li, Lei Zhang, Yuanyuan Sui
The information acquisition about potassium, which affects the quality and yield of crops, is of great significance for crop nutrient management and intelligent decision making in smart agriculture. This article proposes a method for predicting the rice leaf potassium content (LKC) using spectral characteristics and random forests (RF). The method screens spectral characteristic variables based on the linear correlation analysis results of rice LKC and four transformed spectra (original reflectance (R), first derivative reflectance (FDR), continuum-removed reflectance (CRR), and normalized reflectance (NR)) of leaves and the PCA dimensionality reduction results of vegetation indices. Following a second screening of the correlated single band and vegetation index variables of the four transformed spectra, the RF is used to obtain the mixed variable (MV), and regression models are developed to achieve an accurate prediction of rice LKC. Additionally, the effect of potassium spectral sensitivity bands, indices, spectral transformation form, and different modeling methods on rice LKC prediction accuracy is assessed. The results showed that the mixed variable obtained with the second screening using the random forest feature selection method could effectively improve the prediction accuracy of rice LKC. The regression models based on the single band variables (BV) and the vegetation index variables (IV), FDR–RF and IV–RF, with R2 values of 0.62301 and 0.7387 and RMSE values of 0.24174 and 0.15045, respectively, are the best models. In comparison to the previous two models, the MV–RF validation had a higher R2 and a lower RMSE, reaching 0.77817 and 0.14913, respectively. It can be seen that the RF has a better processing ability for the MV that contains vegetation indices and IV than for the BV. Furthermore, the results of different variable screening and regression analyses also revealed that the single band’s range of 1402–1428 nm and 1871–1907 nm, as well as the vegetation indices constituted of reflectance 1799–1881 nm and 2276–2350 nm, are of great significance for predicting rice LKC. This conclusion can provide a reference for establishing a universal vegetation index related to potassium.
{"title":"Prediction of Potassium Content in Rice Leaves Based on Spectral Features and Random Forests","authors":"Yue Yu, Haiye Yu, Xiaokai Li, Lei Zhang, Yuanyuan Sui","doi":"10.3390/agronomy13092337","DOIUrl":"https://doi.org/10.3390/agronomy13092337","url":null,"abstract":"The information acquisition about potassium, which affects the quality and yield of crops, is of great significance for crop nutrient management and intelligent decision making in smart agriculture. This article proposes a method for predicting the rice leaf potassium content (LKC) using spectral characteristics and random forests (RF). The method screens spectral characteristic variables based on the linear correlation analysis results of rice LKC and four transformed spectra (original reflectance (R), first derivative reflectance (FDR), continuum-removed reflectance (CRR), and normalized reflectance (NR)) of leaves and the PCA dimensionality reduction results of vegetation indices. Following a second screening of the correlated single band and vegetation index variables of the four transformed spectra, the RF is used to obtain the mixed variable (MV), and regression models are developed to achieve an accurate prediction of rice LKC. Additionally, the effect of potassium spectral sensitivity bands, indices, spectral transformation form, and different modeling methods on rice LKC prediction accuracy is assessed. The results showed that the mixed variable obtained with the second screening using the random forest feature selection method could effectively improve the prediction accuracy of rice LKC. The regression models based on the single band variables (BV) and the vegetation index variables (IV), FDR–RF and IV–RF, with R2 values of 0.62301 and 0.7387 and RMSE values of 0.24174 and 0.15045, respectively, are the best models. In comparison to the previous two models, the MV–RF validation had a higher R2 and a lower RMSE, reaching 0.77817 and 0.14913, respectively. It can be seen that the RF has a better processing ability for the MV that contains vegetation indices and IV than for the BV. Furthermore, the results of different variable screening and regression analyses also revealed that the single band’s range of 1402–1428 nm and 1871–1907 nm, as well as the vegetation indices constituted of reflectance 1799–1881 nm and 2276–2350 nm, are of great significance for predicting rice LKC. This conclusion can provide a reference for establishing a universal vegetation index related to potassium.","PeriodicalId":56066,"journal":{"name":"Agronomy-Basel","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47270279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-06DOI: 10.3390/agronomy13092330
Shuxin Chen, Juanjuan Chen, Zhuchou Lu, Yuhan Jia, Yuying Yang, R. Zhuo, Xiaojiao Han
Pleiotropic drug resistance (PDR) transporters, which are part of the ABCG subfamily of ATP-binding cassette (ABC) transporters, have been found to be involved in heavy metal tolerance. Salix species (willow) is widely regarded as a perfect candidate for phytoremediation of heavy metals because of its substantial biomass, strong tolerance, and remarkable capacity to accumulate heavy metals. However, the phylogeny and mechanisms underlying the response to heavy metals within the PDR family in willow have yet to be determined. In this study, we discovered and valuated a total of 21 PDR genes in the genome of Salix purpurea. The phylogenetic relationships of these genes were used to classify them into five major clades. The SpPDRs exhibited variations in exon-intron distribution patterns and gene lengths across different branches. Cis-acting elements linked to stress response, drought induction, low temperature, and defense response were discovered in the promoters of PDRs. Significant variations in the transcription levels of various PDR genes were observed across different tissues under heavy metal stress, with distinct heavy metals regulating different PDR members. In roots, PDR4 and PDR21 exhibited high expression levels. Meanwhile, PDR7 and PDR17 showed similar transcription patterns across all analyzed tissues. Furthermore, there was a significant and positive correlation between PDR5 and PDR16, whereas a significant and negative correlation was detected between PDR3 and PDR9, suggesting that the response of PDR members to heavy metals is complex and multifaceted. These findings will establish a vital basis for comprehending the biological functionalities of PDR genes, specifically their involvement in the regulation of willow’s tolerance to heavy metals.
{"title":"Genome-Wide Identification of Pleiotropic Drug Resistance (PDR) Transporters in Salix purpurea and Expression Analysis in Response to Various Heavy Metal Stresses","authors":"Shuxin Chen, Juanjuan Chen, Zhuchou Lu, Yuhan Jia, Yuying Yang, R. Zhuo, Xiaojiao Han","doi":"10.3390/agronomy13092330","DOIUrl":"https://doi.org/10.3390/agronomy13092330","url":null,"abstract":"Pleiotropic drug resistance (PDR) transporters, which are part of the ABCG subfamily of ATP-binding cassette (ABC) transporters, have been found to be involved in heavy metal tolerance. Salix species (willow) is widely regarded as a perfect candidate for phytoremediation of heavy metals because of its substantial biomass, strong tolerance, and remarkable capacity to accumulate heavy metals. However, the phylogeny and mechanisms underlying the response to heavy metals within the PDR family in willow have yet to be determined. In this study, we discovered and valuated a total of 21 PDR genes in the genome of Salix purpurea. The phylogenetic relationships of these genes were used to classify them into five major clades. The SpPDRs exhibited variations in exon-intron distribution patterns and gene lengths across different branches. Cis-acting elements linked to stress response, drought induction, low temperature, and defense response were discovered in the promoters of PDRs. Significant variations in the transcription levels of various PDR genes were observed across different tissues under heavy metal stress, with distinct heavy metals regulating different PDR members. In roots, PDR4 and PDR21 exhibited high expression levels. Meanwhile, PDR7 and PDR17 showed similar transcription patterns across all analyzed tissues. Furthermore, there was a significant and positive correlation between PDR5 and PDR16, whereas a significant and negative correlation was detected between PDR3 and PDR9, suggesting that the response of PDR members to heavy metals is complex and multifaceted. These findings will establish a vital basis for comprehending the biological functionalities of PDR genes, specifically their involvement in the regulation of willow’s tolerance to heavy metals.","PeriodicalId":56066,"journal":{"name":"Agronomy-Basel","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2023-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45725248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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