“…A foliar disease, downy mildew, caused by Hyaloperonospora brassicae , is a major disease in B. oleracea . After infection, chlorotic and necrotic spots develop on the leaves ( Figure 1 ), which impact both crop yield and overall plant vitality [ 1 , 2 ], making the leaves unmarketable [ 3 , 4 ]. On the underside of the infected leaves, hyaline sporangiophores are produced, and hyaline sporangia will be produced from the sporangiophores [ 3 ].…”
Section: Introductionmentioning
confidence: 99%
“…After infection, chlorotic and necrotic spots develop on the leaves ( Figure 1 ), which impact both crop yield and overall plant vitality [ 1 , 2 ], making the leaves unmarketable [ 3 , 4 ]. On the underside of the infected leaves, hyaline sporangiophores are produced, and hyaline sporangia will be produced from the sporangiophores [ 3 ]. The sporangia can be disseminated by wind and water splashes and cause epidemics in the field [ 5 , 6 ].…”
Downy mildew caused by Hyaloperonospora brassicae is a severe disease in Brassica oleracea that significantly reduces crop yield and marketability. This study aims to evaluate different vegetation indices to assess different downy mildew infection levels in the Brassica variety Mildis using hyperspectral data. Artificial inoculation using H. brassicae sporangia suspension was conducted to induce different levels of downy mildew disease. Spectral measurements, spanning 350 nm to 1050 nm, were conducted on the leaves using an environmentally controlled setup, and the reflectance data were acquired and processed. The Successive Projections Algorithm (SPA) and signal sensitivity calculation were used to extract the most informative wavelengths that could be used to develop downy mildew indices (DMI). A total of 37 existing vegetation indices and three proposed DMIs were evaluated to indicate downy mildew (DM) infection levels. The results showed that the classification using a support vector machine achieved accuracies of 71.3%, 80.7%, and 85.3% for distinguishing healthy leaves from DM1 (early infection), DM2 (progressed infection), and DM3 (severe infection) leaves using the proposed downy mildew index. The proposed new downy mildew index potentially enables the development of an automated DM monitoring system and resistance profiling in Brassica breeding lines.
“…A foliar disease, downy mildew, caused by Hyaloperonospora brassicae , is a major disease in B. oleracea . After infection, chlorotic and necrotic spots develop on the leaves ( Figure 1 ), which impact both crop yield and overall plant vitality [ 1 , 2 ], making the leaves unmarketable [ 3 , 4 ]. On the underside of the infected leaves, hyaline sporangiophores are produced, and hyaline sporangia will be produced from the sporangiophores [ 3 ].…”
Section: Introductionmentioning
confidence: 99%
“…After infection, chlorotic and necrotic spots develop on the leaves ( Figure 1 ), which impact both crop yield and overall plant vitality [ 1 , 2 ], making the leaves unmarketable [ 3 , 4 ]. On the underside of the infected leaves, hyaline sporangiophores are produced, and hyaline sporangia will be produced from the sporangiophores [ 3 ]. The sporangia can be disseminated by wind and water splashes and cause epidemics in the field [ 5 , 6 ].…”
Downy mildew caused by Hyaloperonospora brassicae is a severe disease in Brassica oleracea that significantly reduces crop yield and marketability. This study aims to evaluate different vegetation indices to assess different downy mildew infection levels in the Brassica variety Mildis using hyperspectral data. Artificial inoculation using H. brassicae sporangia suspension was conducted to induce different levels of downy mildew disease. Spectral measurements, spanning 350 nm to 1050 nm, were conducted on the leaves using an environmentally controlled setup, and the reflectance data were acquired and processed. The Successive Projections Algorithm (SPA) and signal sensitivity calculation were used to extract the most informative wavelengths that could be used to develop downy mildew indices (DMI). A total of 37 existing vegetation indices and three proposed DMIs were evaluated to indicate downy mildew (DM) infection levels. The results showed that the classification using a support vector machine achieved accuracies of 71.3%, 80.7%, and 85.3% for distinguishing healthy leaves from DM1 (early infection), DM2 (progressed infection), and DM3 (severe infection) leaves using the proposed downy mildew index. The proposed new downy mildew index potentially enables the development of an automated DM monitoring system and resistance profiling in Brassica breeding lines.
As plant pathogens cause significant yield losses in all crops, much effort is put into diseases prevention and control. The importance of rocket has increased in many countries, and also in Serbia interest in cultivation this species is raising. Rocket production is threatened by various pathogenic microorganisms, fung-like, fungi and bacteria being among the most significant ones. For successful rocket production, knowledge on possible pathogenic causers of the diseases is of high importance. In this paper, a review of the literature of diseases caused by fungi and fungi-like organisms of rocket known so far, is presented.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.