Environment-Friendly Control of Cucumber Downy Mildew Using Chlorine Dioxide

Pseudoperonospora cubensis (downy mildew) is highly virulent to various Cucurbitaceae crops, including cucumber (Cucumis sativus). We tested chlorine dioxide application in a plastic greenhouse for environmentfriendly control of downy mildew disease. Spraying diluted chlorine dioxide suppressed downy mildew disease with 41.2% control efficacy. Thermal fogging with chlorine dioxide had a high control efficacy of 80.9%, confirming that this approach is useful for environment-friendly downy mildew control. Using thermal fogging to control diseases that are greatly affected by humidity, such as downy mildew, may be more effective compared with conventional dilution spray control methods.

Identification of Novel Loci and Candidate Genes for Cucumber Downy Mildew Resistance Using GWAS

Downy mildew (DM) is one of the most serious diseases in cucumber. Multiple quantitative trait loci (QTLs) for DM resistance have been detected in a limited number of cucumber accessions. In this study we applied genome-wide association analysis (GWAS) to detected genetic loci for DM resistance in a core germplasm (CG) of cucumber lines that represent diverse origins and ecotypes. Phenotypic data on responses to DM infection were collected in four field trials across three years, 2014, 2015, and 2016. With the resequencing data of these CG lines, GWAS for DM resistance was performed and detected 18 loci that were distributed on all the seven cucumber chromosomes. Of these 18 loci, only six (dmG1.4, dmG4.1, dmG4.3, dmG5.2, dmG7.1, and dmG7.2) were detected in two experiments, and were considered as loci with a stable effect on DM resistance. Further, 16 out of the 18 loci colocalized with the QTLs that were reported in previous studies and two loci, dmG2.1 and dmG7.1, were novel ones identified only in this study. Based on the annotation of homologous genes in Arabidopsis and pairwise LD correlation analysis, several candidate genes were identified as potential causal genes underlying the stable and novel loci, including Csa1G575030 for dmG1.4, Csa2G060360 for dmG2.1, Csa4G064680 for dmG4.1, Csa5G606470 for dmG5.2, and Csa7G004020 for dmG7.1. This study shows that the CG germplasm is a very valuable resource carrying known and novel QTLs for DM resistance. The potential of using these CG lines for future allele-mining of candidate genes was discussed in the context of breeding cucumber with resistance to DM.

Identification of novel loci and candidate genes for cucumber downy mildew resistance using GWAS

Background Downy mildew (DM) is one of the most serious diseases in cucumber and brings the loss of yield and profit. Multiple QTLs for DM resistance have been detected, however, no loci related to resistance was reported using genome-wide association analysis (GWAS). In this study, the core germplasm (CG) of cucumber lines that had been constructed and resequenced were used to identify DM resistance Loci using GWAS technology. Results Thirteen loci (dmG1.1, dmG1.2, dmG2.1, dmG2.2, dmG3.1, dmG4.1, dmG4.2, dmG5.1, dmG5.2, dmG6.1, dmG6.2, dmG7.1 and dmG7.2) associated with DM resistance were detected on all the seven chromosomes. Among these loci, dmG2.1 and dmG7.1 were novel loci compared with previous studies. Based on the annotation of homologous genes in Arabidopsis and pairwise LD correlations, Csa1G575030 could be the most likely candidate gene of dmG1.2; Csa2G059820 and Csa2G060360 could be the candidate gene of dmG2.1. A WRKY transcription factor Csa5G606470 could be the candidate gene of dmG5.2. Csa7G004020 could be the candidate gene of dmG7.1. Conclusions These results identify five candidate genes for four loci related to DM resistance in cucumber which provide theoretical basis for gene cloning and genetic breeding of DM resistance in cucumber.

A Rapid Diagnostic Grading System for Cucumber Downy Mildew Based on Visible Light - Hyperspectral Imaging System

Downy mildew, a kind of cucumber disease with a high spread rate and harmfulness that is more common in the world, has a great influence on the yield of cucumbers. The rapid identification of its symptoms and the rapid classification of the post-disease characters are of great significance to the rapid diagnosis of cucumber frost mold and the proper treatment of medicine after the disease. In order to quickly and accurately classify the occurrence and the degree of cucumber downy mildew, a rapid diagnosis and classification method of cucumber downy mildew based on visible light - high spectral imaging technology was proposed in this paper. In addition, the stepwise regression method and PCA were used to reduce and extract the feature information of sensitive bands. Two kinds of acquired feature information are used as the input of the model to construct the disease degree classification detection model of the SVM classification model. The model based on the stepwise regression method is used to classify and identify downy mildew and normal leaves. In this model, the accuracy of the Sigmoid kernel function classification test is the highest, reaching 95.00%, and the recognition rate of different degrees of cucumber downy mildew disease leaves as high as 93.88, which has a high classification detection accuracy. The results show that the rapid diagnosis and classification of cucumber downy mildew can be realized by using the visible light spectral imaging system combined with the automatic classification model of SVM, which provides a new method and reference for solving the problem of cucumber downy mildew in time.