Cruciferous vegetables are important edible vegetable crops.However,they are susceptible to various pests during their growth process,which requires real-time and accurate monitoring of these pests for pest forecastin...Cruciferous vegetables are important edible vegetable crops.However,they are susceptible to various pests during their growth process,which requires real-time and accurate monitoring of these pests for pest forecasting and scientific control.Hanging yellow sticky boards is a common way to monitor and trap those pests which are attracted to the yellow color.To achieve real-time,low-cost,intelligent monitoring of these vegetable pests on the boards,we established an intelligent monitoring system consisting of a smart camera,a web platform and a pest detection algorithm deployed on a server.After the operator sets the monitoring preset points and shooting time of the camera on the system platform,the camera in the field can automatically collect images of multiple yellow sticky boards at fixed places and times every day.The pests trapped on the yellow sticky boards in vegetable fields,Plutella xylostella,Phyllotreta striolata and flies,are very small and susceptible to deterioration and breakage,which increases the difficulty of model detection.To solve the problem of poor recognition due to the small size and breaking of the pest bodies,we propose an intelligent pest detection algorithm based on an improved Cascade R-CNN model for three important cruciferous crop pests.The algorithm uses an overlapping sliding window method,an improved Res2Net network as the backbone network,and a recursive feature pyramid network as the neck network.The results of field tests show that the algorithm achieves good detection results for the three target pests on the yellow sticky board images,with precision levels of 96.5,92.2 and 75.0%,and recall levels of 96.6,93.1 and 74.7%,respectively,and an F_(1) value of 0.880.Compared with other algorithms,our algorithm has a significant advantage in its ability to detect small target pests.To accurately obtain the data for the newly added pests each day,a two-stage pest matching algorithm was proposed.The algorithm performed well and achieved results that were highly consistent with manual counting,with a mean error of only 2.2%.This intelligent monitoring system realizes precision,good visualization,and intelligent vegetable pest monitoring,which is of great significance as it provides an effective pest prevention and control option for farmers.展开更多
Background:Tomato quality is a complex trait influenced by multiple genes involved in various complicated metabolic pathways.Materials and Methods:This study sought to improve tomato taste and quality by grafting on g...Background:Tomato quality is a complex trait influenced by multiple genes involved in various complicated metabolic pathways.Materials and Methods:This study sought to improve tomato taste and quality by grafting on goji rootstock.We integrated physiological and biochemical indicators,as wellas metabolic and transcriptomic analysis,to evaluate tomato quality.Results:The grafted tomatoes showed significant increases in soluble solids(51.48%),vitamin C(16.86%),soluble protein(16.19%),titratable acid(11.73%),anthocyanin(11.43%),and polysaccharide(9.43%)content compared to those of the control.Metabolomics analysis identified 234 differentially accumulated metabolites and transcriptome analysis identified 4213 differentially expressed genes between grafted and control tomatoes at three ripening stages(mature green,turning,and fully red).A total of 93 phenolic compounds,including flavonoids and phenolic acids,showed differential accumulation patterns between grafted and control tomatoes at the fully red stage.These changes were attributed to the upregulation of key genes(F3'H,F3'5'H,DFR,and ANS)associated with flavonoids and anthocyanin synthesis in the goji rootstock compared to those of the control.The expression of genes involved in sucrose hydrolysis and starch synthesis,including invertase(INV),sucrase synthase(SUS),and beta-amylase(BAM)genes,were suppressed by goji grafting,resulting in increased levels of sugars.In addition,the consistency between the transcriptomic and metabolomic data provided a robust validation of the observed quality changes.Conclusions:Taken together,our results demonstrate that grafting onto goji rootstock improves tomato quality by modulating multiple genes involved in phenylpropanoid,sucrose,and starch pathways during fruit development,providing valuable insights for improving the quality and tasteof tomato.展开更多
基金supported by the Collaborative Innovation Center Project of Guangdong Academy of Agricultural Sciences,China(XTXM202202).
文摘Cruciferous vegetables are important edible vegetable crops.However,they are susceptible to various pests during their growth process,which requires real-time and accurate monitoring of these pests for pest forecasting and scientific control.Hanging yellow sticky boards is a common way to monitor and trap those pests which are attracted to the yellow color.To achieve real-time,low-cost,intelligent monitoring of these vegetable pests on the boards,we established an intelligent monitoring system consisting of a smart camera,a web platform and a pest detection algorithm deployed on a server.After the operator sets the monitoring preset points and shooting time of the camera on the system platform,the camera in the field can automatically collect images of multiple yellow sticky boards at fixed places and times every day.The pests trapped on the yellow sticky boards in vegetable fields,Plutella xylostella,Phyllotreta striolata and flies,are very small and susceptible to deterioration and breakage,which increases the difficulty of model detection.To solve the problem of poor recognition due to the small size and breaking of the pest bodies,we propose an intelligent pest detection algorithm based on an improved Cascade R-CNN model for three important cruciferous crop pests.The algorithm uses an overlapping sliding window method,an improved Res2Net network as the backbone network,and a recursive feature pyramid network as the neck network.The results of field tests show that the algorithm achieves good detection results for the three target pests on the yellow sticky board images,with precision levels of 96.5,92.2 and 75.0%,and recall levels of 96.6,93.1 and 74.7%,respectively,and an F_(1) value of 0.880.Compared with other algorithms,our algorithm has a significant advantage in its ability to detect small target pests.To accurately obtain the data for the newly added pests each day,a two-stage pest matching algorithm was proposed.The algorithm performed well and achieved results that were highly consistent with manual counting,with a mean error of only 2.2%.This intelligent monitoring system realizes precision,good visualization,and intelligent vegetable pest monitoring,which is of great significance as it provides an effective pest prevention and control option for farmers.
基金supported by the Zhejiang Province‘Three Rural Nine Parties’Science and Technology Cooperation Plan Project(No.2022SNJF027)the Headquarters Administration of Zhejiang Pairing-up Support for Qinghai Haixi Mongolian and Tibetan Autonomous Prefecture,China.
文摘Background:Tomato quality is a complex trait influenced by multiple genes involved in various complicated metabolic pathways.Materials and Methods:This study sought to improve tomato taste and quality by grafting on goji rootstock.We integrated physiological and biochemical indicators,as wellas metabolic and transcriptomic analysis,to evaluate tomato quality.Results:The grafted tomatoes showed significant increases in soluble solids(51.48%),vitamin C(16.86%),soluble protein(16.19%),titratable acid(11.73%),anthocyanin(11.43%),and polysaccharide(9.43%)content compared to those of the control.Metabolomics analysis identified 234 differentially accumulated metabolites and transcriptome analysis identified 4213 differentially expressed genes between grafted and control tomatoes at three ripening stages(mature green,turning,and fully red).A total of 93 phenolic compounds,including flavonoids and phenolic acids,showed differential accumulation patterns between grafted and control tomatoes at the fully red stage.These changes were attributed to the upregulation of key genes(F3'H,F3'5'H,DFR,and ANS)associated with flavonoids and anthocyanin synthesis in the goji rootstock compared to those of the control.The expression of genes involved in sucrose hydrolysis and starch synthesis,including invertase(INV),sucrase synthase(SUS),and beta-amylase(BAM)genes,were suppressed by goji grafting,resulting in increased levels of sugars.In addition,the consistency between the transcriptomic and metabolomic data provided a robust validation of the observed quality changes.Conclusions:Taken together,our results demonstrate that grafting onto goji rootstock improves tomato quality by modulating multiple genes involved in phenylpropanoid,sucrose,and starch pathways during fruit development,providing valuable insights for improving the quality and tasteof tomato.
