In recent years,peanut yield and quality are more seriously affected by pod rot disease in China.However,managing this disease has proven challenging due to the wide host range of its pathogens.In this study,four soil...In recent years,peanut yield and quality are more seriously affected by pod rot disease in China.However,managing this disease has proven challenging due to the wide host range of its pathogens.In this study,four soil samples were collected from fields with pod rot disease in Hebei Province,and 454 pyrosequencing was used to analyze the fungal communities structure within them.All 38490 ITS high-quality sequences were grouped into 1203 operational taxonomic units,the fungal community diversity of four soil samples was evaluated and compared using Shannon index and Simpson index.The results showed that members of Ascomycota were dominant,followed by Basidiomycota.According to the BLAST results at the species level,Guehomyces had the highest abundance,accounting for about 7.27%,followed by Alternaria,Fusarium,and Davidiella.The relative abundance of Fusarium oxysporum isolated from rotting peanuts in soil with peanut rot was higher than that in the control,indicating that Fusarium oxysporum might be one of the main pathogenic fungus of peanut rot in this area.This study delved into the broader fungal community associated with peanut pod rot,providing a theoretical foundation for preventing and treating this disease in agriculture.展开更多
In this study,a simulation model of peanut pod particles during harvest in saline soil was tested to calibrate contact parameters.Discrete meta-fill models of peanut pods were generated by a 3D meter and EDEM software...In this study,a simulation model of peanut pod particles during harvest in saline soil was tested to calibrate contact parameters.Discrete meta-fill models of peanut pods were generated by a 3D meter and EDEM software.The range of values of contact parameters for peanut pods was measured by conducting collision and other tests using a homemade test rig.The parameters that affect the significance of the simulation process of stacking angle were screened by the Plackett-Burman experiment,the steepest ascent experiment,and the Box-Behnken experiment.An optimization test determined the optimal simulation model parameters:The peanut pods had a Poisson’s ratio of 0.386 and a shear modulus of 3.04 MPa.The coefficient of recovery for pods-pods collisions was 0.335,the coefficient of static friction was 0.854,and the coefficient of rolling friction was 0.346.The coefficient of recovery of collision between the pods-65Mn steel was 0.339,the coefficient of static friction was 0.589,and the coefficient of rolling friction was 0.159.The test results showed a relative error of 0.42%between the stacking angle bench and simulation tests.The results can provide data support for studying the discrete metamaterial characterization of peanut pods.展开更多
Research interest in pneumatic conveying technologies in processes such as peanut harvesting and shelling has grown rapidly in recent years.However,the use of pneumatic conveyors in this application suffers from high ...Research interest in pneumatic conveying technologies in processes such as peanut harvesting and shelling has grown rapidly in recent years.However,the use of pneumatic conveyors in this application suffers from high pod damage rates and duct obstruction.To address these issues,we analyzed the critical speed of pneumatic transport for conveying the peanut pods and measured the angle of friction and coefficient of restitution of peanut pods on a variety of material surfaces.Based on the results of these tests,optimizations and improvements were made to the separator bowl,air supply duct,and conveying duct.A pneumatic conveying experiment was then performed using peanut pods.In the factorial experiment,it was found that increases in fan speed increase the pod damage rate and transport efficiency,while increases in the thickness of the cushioning/anti-obstruction layer decrease the rate of pod damage and transport efficiency.Pod damage rates were significantly affected by fan speed,the thickness of the cushioning/obstruction prevention layer,and interaction between these factors,while transport efficiency was only significantly affected by fan speed.It is proved by the machine verification test,the optimal parameters for the pneumatic transport of Baisha peanut pods with a moisture content of 7.24%was a fan speed of 2700 r/min and a cushioning/anti-obstruction layer thickness of 6 mm.A pod damage rate of 5.19%and transport efficiency of 92.03%were achieved using these parameters,which are sufficient for meeting the requirements of industrial applications.展开更多
The inheritance of pod-and seed-number traits(PSNT) in peanut(Arachis hypogaea L.) is poorly understood. In the present study, a recombinant inbred line(RIL) population of 188 lines was used to map quantitative trait ...The inheritance of pod-and seed-number traits(PSNT) in peanut(Arachis hypogaea L.) is poorly understood. In the present study, a recombinant inbred line(RIL) population of 188 lines was used to map quantitative trait loci(QTL) for number of seeds per pod(NSP),number of pods per plant(NPP), and numbers of one-, two-, and three-seeded pods per plant(N1 PP, N2 PP, and N3 PP) in four environments. A total of 28 consensus QTL and 14 single QTL were identified, including 11 major and stable QTL. Four major and stable QTL including qN3 PPA5.2, q N3 PPA5.4, qN3 PPA5.5, and qN3 PPA5.7 each explained 12.3%–33.0% of phenotype variation. By use of another integrated linkage map for the A5 group(hereafter referred to as INT A5 group), QTL for PSNT were located in seven intervals of 0.73–9.68 Mb in length on chromosome A05, and candidate genes underlying N3 PP were suggested. These findings shed light on the genetic basis of PSNT. Major QTL for N3 PP could be used as candidates for further positional cloning.展开更多
Peanut (Arachis hypogaea L.) is a highly nutritious food that is an excellent source of protein and is associated with increased coronary health, lower risk of type-2 diabetes, lower risk of breast cancer and a health...Peanut (Arachis hypogaea L.) is a highly nutritious food that is an excellent source of protein and is associated with increased coronary health, lower risk of type-2 diabetes, lower risk of breast cancer and a healthy profile of inflammatory biomarkers. The domestic demand for organic peanuts has significantly increased, requiring new breeding efforts to develop peanut varieties adapted to the organic farming system. The use of unmanned aerial system (UAS) has gained scientific attention because of the ability to generate high-throughput phenotypic data. However, it has not been fully investigated for phenotyping agronomic traits of organic peanuts. Peanuts are beneficial for cardio system protection and are widely used. Within the U.S., peanuts are grown in 11 states on roughly 600,000 hectares and averaging 4500 kg/ha. This study’s objective was to test the accuracy of UAS data in the phenotyping pod and seed yield of organic peanuts. UAS data was collected from a field plot with 20 Spanish peanut breeding lines on July 07, 2021 and September 27, 2021. The study was a randomized complete block design (RCBD) with 3 blocks. Twenty-five vegetation indices (VIs) were calculated. The analysis of variance showed significant genotypic effects on all 25 vegetation indices for both flights (p < 0.05). The vegetation index Red edge (RE) from the first flight was the most significantly correlated with both pod (r = 0.44) and seed yield (r = 0.64). These results can be used to further advance organic peanut breeding efforts with high-throughput data collection.展开更多
Peanut(Arachis hypogaea)is widely cultivated worldwide as an important source of edible vegetable oil and protein.Peanut seed pods develop below ground from a gynophore that forms above ground and then penetrates the ...Peanut(Arachis hypogaea)is widely cultivated worldwide as an important source of edible vegetable oil and protein.Peanut seed pods develop below ground from a gynophore that forms above ground and then penetrates the soil surface to bury the developing pod.Numerous studies have explored transcriptional regulation during peanut pod development.Here,we explored post-transcriptional regulation,including polyadenylation,alternative splicing,and RNA adenosine methylation(m6A),in peanut pods across four developmental stages by performing direct RNA sequencing.This produced 70.43 million long reads with average lengths of 890–1,136 nucleotides(nt)from 12 samples across four developmental stages,yielding a total of 14,627 newly identified transcripts.We detected a negative relationship between poly(A)tail lengths and transcript abundance,with the shortest poly(A)tails at the subterranean peg and expanded pod 1 stages,and longest poly(A)tails at the aerial gynophore and expanded pod 2 stages.Moreover,throughout pod development,from the penetration of the gynophore into the soil to pod enlargement,the splicing machinery utilized more proximal than distal alternative polyadenylation sites in the transcripts.The date showed no correlation between m6A modification and gene expression in peanut,but found more transcripts with alternative first and last exon types of alternative splicing events.Transcripts that were differentially abundant across developmental stages were primarily enriched in the Gene Ontology terms photosynthesis,response to oxidative stress,response to auxin,plant-type cell wall organization,and lignin catabolism.This study lays a foundation for revealing the roles of epigenetics and post-transcriptional regulation in pod development in peanut.展开更多
传统CNN算法在花生荚果外观识别任务中存在内存密集型和计算密集型问题,以及其在资源受限的边缘终端上部署困难,基于此,该研究提出了一种高效的花生荚果识别模型——PPINET(peanut pod identification network),以适应嵌入式设备的资源...传统CNN算法在花生荚果外观识别任务中存在内存密集型和计算密集型问题,以及其在资源受限的边缘终端上部署困难,基于此,该研究提出了一种高效的花生荚果识别模型——PPINET(peanut pod identification network),以适应嵌入式设备的资源限制需求。该模型通过结合深度可分离卷积和倒残差结构显著降低参数量和计算量,同时保留特征提取能力,并引入MQA(multi-query attention)模块增强关键特征提取,并利用TuNAS(easy-to-tune and scalable implementation of efficient neural architecture search with weight sharing)策略优化模型结构,使其在资源受限设备上表现优异。此外,采用ResNet(residual neural network)进行知识蒸馏配合三折交叉验证训练提升精度,最终量化为RKNN格式并在瑞芯微RK3588上实现NPU加速部署。PPINET模型尺寸仅为1.85 MB,参数量为0.49 M,浮点运算数为0.30G。PPINET在花生荚果分类中表现优异,准确率达98.65%,在RK3588上推理速度达321 fps。该模型具备较高的识别准确率和快速的识别速度,能够实现花生荚果的实时精准检测。展开更多
基金supported by General project of Shandong Provincial Natural Science Foundation(ZR2020MC103,ZR2021MC040)Agricultural Innovation Project of Shandong Academy of Agricultural Sciences(CXGC2022B06,CXGC2022F33).
文摘In recent years,peanut yield and quality are more seriously affected by pod rot disease in China.However,managing this disease has proven challenging due to the wide host range of its pathogens.In this study,four soil samples were collected from fields with pod rot disease in Hebei Province,and 454 pyrosequencing was used to analyze the fungal communities structure within them.All 38490 ITS high-quality sequences were grouped into 1203 operational taxonomic units,the fungal community diversity of four soil samples was evaluated and compared using Shannon index and Simpson index.The results showed that members of Ascomycota were dominant,followed by Basidiomycota.According to the BLAST results at the species level,Guehomyces had the highest abundance,accounting for about 7.27%,followed by Alternaria,Fusarium,and Davidiella.The relative abundance of Fusarium oxysporum isolated from rotting peanuts in soil with peanut rot was higher than that in the control,indicating that Fusarium oxysporum might be one of the main pathogenic fungus of peanut rot in this area.This study delved into the broader fungal community associated with peanut pod rot,providing a theoretical foundation for preventing and treating this disease in agriculture.
基金financially sponsored by the National Key Research and Development Program of China(Grant No.2022YFD2300100)Shandong Province Agricultural Major Technology Collaborative Extension Program Project(Grant No.SDNYXTTG-2024-15)the National Saline and Alkaline Land Comprehensive Utilization Technology Innovation Center Core Research Team Project(Grant No.NSALCUIC-2024).
文摘In this study,a simulation model of peanut pod particles during harvest in saline soil was tested to calibrate contact parameters.Discrete meta-fill models of peanut pods were generated by a 3D meter and EDEM software.The range of values of contact parameters for peanut pods was measured by conducting collision and other tests using a homemade test rig.The parameters that affect the significance of the simulation process of stacking angle were screened by the Plackett-Burman experiment,the steepest ascent experiment,and the Box-Behnken experiment.An optimization test determined the optimal simulation model parameters:The peanut pods had a Poisson’s ratio of 0.386 and a shear modulus of 3.04 MPa.The coefficient of recovery for pods-pods collisions was 0.335,the coefficient of static friction was 0.854,and the coefficient of rolling friction was 0.346.The coefficient of recovery of collision between the pods-65Mn steel was 0.339,the coefficient of static friction was 0.589,and the coefficient of rolling friction was 0.159.The test results showed a relative error of 0.42%between the stacking angle bench and simulation tests.The results can provide data support for studying the discrete metamaterial characterization of peanut pods.
文摘Research interest in pneumatic conveying technologies in processes such as peanut harvesting and shelling has grown rapidly in recent years.However,the use of pneumatic conveyors in this application suffers from high pod damage rates and duct obstruction.To address these issues,we analyzed the critical speed of pneumatic transport for conveying the peanut pods and measured the angle of friction and coefficient of restitution of peanut pods on a variety of material surfaces.Based on the results of these tests,optimizations and improvements were made to the separator bowl,air supply duct,and conveying duct.A pneumatic conveying experiment was then performed using peanut pods.In the factorial experiment,it was found that increases in fan speed increase the pod damage rate and transport efficiency,while increases in the thickness of the cushioning/anti-obstruction layer decrease the rate of pod damage and transport efficiency.Pod damage rates were significantly affected by fan speed,the thickness of the cushioning/obstruction prevention layer,and interaction between these factors,while transport efficiency was only significantly affected by fan speed.It is proved by the machine verification test,the optimal parameters for the pneumatic transport of Baisha peanut pods with a moisture content of 7.24%was a fan speed of 2700 r/min and a cushioning/anti-obstruction layer thickness of 6 mm.A pod damage rate of 5.19%and transport efficiency of 92.03%were achieved using these parameters,which are sufficient for meeting the requirements of industrial applications.
基金supported by the National Natural Science Foundation of China(31271764,31371662,31471534,31601340,31461143022)the China's Agricultural Research System(CARS-14)+1 种基金the National Key Technology R&D Program of China(2013BAD01B03)the National Infrastructure for Crop Germplasm Resources(NICGR2017-036)
文摘The inheritance of pod-and seed-number traits(PSNT) in peanut(Arachis hypogaea L.) is poorly understood. In the present study, a recombinant inbred line(RIL) population of 188 lines was used to map quantitative trait loci(QTL) for number of seeds per pod(NSP),number of pods per plant(NPP), and numbers of one-, two-, and three-seeded pods per plant(N1 PP, N2 PP, and N3 PP) in four environments. A total of 28 consensus QTL and 14 single QTL were identified, including 11 major and stable QTL. Four major and stable QTL including qN3 PPA5.2, q N3 PPA5.4, qN3 PPA5.5, and qN3 PPA5.7 each explained 12.3%–33.0% of phenotype variation. By use of another integrated linkage map for the A5 group(hereafter referred to as INT A5 group), QTL for PSNT were located in seven intervals of 0.73–9.68 Mb in length on chromosome A05, and candidate genes underlying N3 PP were suggested. These findings shed light on the genetic basis of PSNT. Major QTL for N3 PP could be used as candidates for further positional cloning.
文摘Peanut (Arachis hypogaea L.) is a highly nutritious food that is an excellent source of protein and is associated with increased coronary health, lower risk of type-2 diabetes, lower risk of breast cancer and a healthy profile of inflammatory biomarkers. The domestic demand for organic peanuts has significantly increased, requiring new breeding efforts to develop peanut varieties adapted to the organic farming system. The use of unmanned aerial system (UAS) has gained scientific attention because of the ability to generate high-throughput phenotypic data. However, it has not been fully investigated for phenotyping agronomic traits of organic peanuts. Peanuts are beneficial for cardio system protection and are widely used. Within the U.S., peanuts are grown in 11 states on roughly 600,000 hectares and averaging 4500 kg/ha. This study’s objective was to test the accuracy of UAS data in the phenotyping pod and seed yield of organic peanuts. UAS data was collected from a field plot with 20 Spanish peanut breeding lines on July 07, 2021 and September 27, 2021. The study was a randomized complete block design (RCBD) with 3 blocks. Twenty-five vegetation indices (VIs) were calculated. The analysis of variance showed significant genotypic effects on all 25 vegetation indices for both flights (p < 0.05). The vegetation index Red edge (RE) from the first flight was the most significantly correlated with both pod (r = 0.44) and seed yield (r = 0.64). These results can be used to further advance organic peanut breeding efforts with high-throughput data collection.
基金supported by the Taishan Scholars Program,and Key R&D Program of Shandong Province,China(2024LZGC035)the Weifang Science and Technology Development Plan(2024JZ001)the Natural Science Foundation of Shandong Province(ZR202103010405)to Xiaoqin Liu.
文摘Peanut(Arachis hypogaea)is widely cultivated worldwide as an important source of edible vegetable oil and protein.Peanut seed pods develop below ground from a gynophore that forms above ground and then penetrates the soil surface to bury the developing pod.Numerous studies have explored transcriptional regulation during peanut pod development.Here,we explored post-transcriptional regulation,including polyadenylation,alternative splicing,and RNA adenosine methylation(m6A),in peanut pods across four developmental stages by performing direct RNA sequencing.This produced 70.43 million long reads with average lengths of 890–1,136 nucleotides(nt)from 12 samples across four developmental stages,yielding a total of 14,627 newly identified transcripts.We detected a negative relationship between poly(A)tail lengths and transcript abundance,with the shortest poly(A)tails at the subterranean peg and expanded pod 1 stages,and longest poly(A)tails at the aerial gynophore and expanded pod 2 stages.Moreover,throughout pod development,from the penetration of the gynophore into the soil to pod enlargement,the splicing machinery utilized more proximal than distal alternative polyadenylation sites in the transcripts.The date showed no correlation between m6A modification and gene expression in peanut,but found more transcripts with alternative first and last exon types of alternative splicing events.Transcripts that were differentially abundant across developmental stages were primarily enriched in the Gene Ontology terms photosynthesis,response to oxidative stress,response to auxin,plant-type cell wall organization,and lignin catabolism.This study lays a foundation for revealing the roles of epigenetics and post-transcriptional regulation in pod development in peanut.
