Fruit diseases seriously affect the production of the agricultural sector,which builds financial pressure on the country’s economy.The manual inspection of fruit diseases is a chaotic process that is both time and co...Fruit diseases seriously affect the production of the agricultural sector,which builds financial pressure on the country’s economy.The manual inspection of fruit diseases is a chaotic process that is both time and cost-consuming since it involves an accurate manual inspection by an expert.Hence,it is essential that an automated computerised approach is developed to recognise fruit diseases based on leaf images.According to the literature,many automated methods have been developed for the recognition of fruit diseases at the early stage.However,these techniques still face some challenges,such as the similar symptoms of different fruit diseases and the selection of irrelevant features.Image processing and deep learning techniques have been extremely successful in the last decade,but there is still room for improvement due to these challenges.Therefore,we propose a novel computerised approach in this work using deep learning and featuring an ant colony optimisation(ACO)based selection.The proposed method consists of four fundamental steps:data augmentation to solve the imbalanced dataset,fine-tuned pretrained deep learning models(NasNetMobile andMobileNet-V2),the fusion of extracted deep features using matrix length,and finally,a selection of the best features using a hybrid ACO and a Neighbourhood Component Analysis(NCA).The best-selected features were eventually passed to many classifiers for final recognition.The experimental process involved an augmented dataset and achieved an average accuracy of 99.7%.Comparison with existing techniques showed that the proposed method was effective.展开更多
The design of efficient heterogeneous catalysts in bicarbonate-activated hydrogen peroxide systems(BAP)is a hot topic in wastewater treatment.In this work,Cu_(2)O nanoparticles with different morphologies including cu...The design of efficient heterogeneous catalysts in bicarbonate-activated hydrogen peroxide systems(BAP)is a hot topic in wastewater treatment.In this work,Cu_(2)O nanoparticles with different morphologies including cubic shape(c-Cu_(2)O),octahedron shape(o-Cu_(2)O)and spherical shape(s-Cu_(2)O),were applied in BAP for the first time to degrade tetracycline hydrochloride(TC).Compared with Cu^(2+)ions and CuO,TC degradation was boosted in the presence of Cu_(2)O in the BAP system,with the degradation rate following the order c-Cu_(2)O>o-Cu_(2)O>s-Cu_(2)O.The morphology-dependent effects could be linearly correlated with the ratio of surface oxygen species(O_S),but not with the surface area or Cu(Ⅰ)ratio.The c-Cu_(2)O catalyst with exposure of(100)facets contained 76.6%O_Sas the active site for H_(2)O_(2)adsorption and activation,while the value was much lower for o-Cu_(2)O and s-Cu_(2)O with dominant(111)facets.The presence of HCO_(3)-enhanced the interactions among Cu_(2)O,H_(2)O_(2)and TC,leading to facile oxidation of Cu(Ⅰ)to Cu(Ⅱ)by H_(2)O_(2),and the formation of various reactive species such as hydroxyl radicals and Cu(Ⅲ)contributed to TC degradation.This work provides a new method for enhancing H_(2)O_(2)activation with heterogeneous catalysts by crystal facet engineering.展开更多
Bird predation during seed maturation causes great loss to agricultural production.In this study,through GWAS analysis of a large-scale sorghum germplasm diversity panel,we identified that Tannin1,which encodes a WD40...Bird predation during seed maturation causes great loss to agricultural production.In this study,through GWAS analysis of a large-scale sorghum germplasm diversity panel,we identified that Tannin1,which encodes a WD40 protein functioning in the WD40/MYB/bHLH complex,controls bird feeding behavior in sorghum.Metabolic profiling analysis showed that a group of sorghum accessions preferred by birds contain mutated tan1-a/b alleles and accumulate significantly lower levels of anthocyanins and condensed tannin compounds.In contrast,a variety of aromatic and fatty acid-derived volatiles accumulate at significantly higher levels in these bird-preference accessions.We subsequently conducted both sparrow feeding and sparrow volatile attractant assays,which confirmed,respectively,the antifeedant and attractant functions of these differentially accumulated metabolites.In addition,the connection between the biosynthesis pathway of anthocyanin and proanthocyanidin and the pathway of fatty acid–derived volatile biosynthesis was demonstrated by discovering that Tannin1 complex modulates fatty acid biosynthesis by regulating the expression of SbGL2 in sorghum,thus affecting the accumulation of fatty acid-derived volatiles.Taken together,our study identified Tannin1 as the gene underlying the major locus controlling bird feeding behavior in sorghum,illustrating an example of the identification of an ecologically impactful molecular mechanism from field observation and providing significant insights into the chemistry of bird–plant ecological interactions.展开更多
基金This research work was partially supported by Chiang Mai University.
文摘Fruit diseases seriously affect the production of the agricultural sector,which builds financial pressure on the country’s economy.The manual inspection of fruit diseases is a chaotic process that is both time and cost-consuming since it involves an accurate manual inspection by an expert.Hence,it is essential that an automated computerised approach is developed to recognise fruit diseases based on leaf images.According to the literature,many automated methods have been developed for the recognition of fruit diseases at the early stage.However,these techniques still face some challenges,such as the similar symptoms of different fruit diseases and the selection of irrelevant features.Image processing and deep learning techniques have been extremely successful in the last decade,but there is still room for improvement due to these challenges.Therefore,we propose a novel computerised approach in this work using deep learning and featuring an ant colony optimisation(ACO)based selection.The proposed method consists of four fundamental steps:data augmentation to solve the imbalanced dataset,fine-tuned pretrained deep learning models(NasNetMobile andMobileNet-V2),the fusion of extracted deep features using matrix length,and finally,a selection of the best features using a hybrid ACO and a Neighbourhood Component Analysis(NCA).The best-selected features were eventually passed to many classifiers for final recognition.The experimental process involved an augmented dataset and achieved an average accuracy of 99.7%.Comparison with existing techniques showed that the proposed method was effective.
基金supported by the National Natural Science Foundation of China (No.51978542)the Opening Project of Hubei Key Laboratory of Biomass Fibers and Eco-Dyeing&Finishing (No.STRZ202113)。
文摘The design of efficient heterogeneous catalysts in bicarbonate-activated hydrogen peroxide systems(BAP)is a hot topic in wastewater treatment.In this work,Cu_(2)O nanoparticles with different morphologies including cubic shape(c-Cu_(2)O),octahedron shape(o-Cu_(2)O)and spherical shape(s-Cu_(2)O),were applied in BAP for the first time to degrade tetracycline hydrochloride(TC).Compared with Cu^(2+)ions and CuO,TC degradation was boosted in the presence of Cu_(2)O in the BAP system,with the degradation rate following the order c-Cu_(2)O>o-Cu_(2)O>s-Cu_(2)O.The morphology-dependent effects could be linearly correlated with the ratio of surface oxygen species(O_S),but not with the surface area or Cu(Ⅰ)ratio.The c-Cu_(2)O catalyst with exposure of(100)facets contained 76.6%O_Sas the active site for H_(2)O_(2)adsorption and activation,while the value was much lower for o-Cu_(2)O and s-Cu_(2)O with dominant(111)facets.The presence of HCO_(3)-enhanced the interactions among Cu_(2)O,H_(2)O_(2)and TC,leading to facile oxidation of Cu(Ⅰ)to Cu(Ⅱ)by H_(2)O_(2),and the formation of various reactive species such as hydroxyl radicals and Cu(Ⅲ)contributed to TC degradation.This work provides a new method for enhancing H_(2)O_(2)activation with heterogeneous catalysts by crystal facet engineering.
文摘Bird predation during seed maturation causes great loss to agricultural production.In this study,through GWAS analysis of a large-scale sorghum germplasm diversity panel,we identified that Tannin1,which encodes a WD40 protein functioning in the WD40/MYB/bHLH complex,controls bird feeding behavior in sorghum.Metabolic profiling analysis showed that a group of sorghum accessions preferred by birds contain mutated tan1-a/b alleles and accumulate significantly lower levels of anthocyanins and condensed tannin compounds.In contrast,a variety of aromatic and fatty acid-derived volatiles accumulate at significantly higher levels in these bird-preference accessions.We subsequently conducted both sparrow feeding and sparrow volatile attractant assays,which confirmed,respectively,the antifeedant and attractant functions of these differentially accumulated metabolites.In addition,the connection between the biosynthesis pathway of anthocyanin and proanthocyanidin and the pathway of fatty acid–derived volatile biosynthesis was demonstrated by discovering that Tannin1 complex modulates fatty acid biosynthesis by regulating the expression of SbGL2 in sorghum,thus affecting the accumulation of fatty acid-derived volatiles.Taken together,our study identified Tannin1 as the gene underlying the major locus controlling bird feeding behavior in sorghum,illustrating an example of the identification of an ecologically impactful molecular mechanism from field observation and providing significant insights into the chemistry of bird–plant ecological interactions.
