Non-Chemical Approaches to Control Postharvest Gray Mold Disease in Bell Peppers

Bell pepper (Capsicum annuum) is a widely grown vegetable crop that is nutritious and flavorful and economically important for growers worldwide. A significant limiting factor in the postharvest storage and long-distance transport of peppers is gray mold caused by Botrytis cinerea. The pathogen is widespread in nature, highly aggressive, and able to cause disease at cool refrigerated temperatures during transport and storage. Fungicides have been relied on in the past to reduce bell pepper rots in storage; however, concern over residues on the fruit and environmental degradation have heightened the importance of natural and generally recognized as safe (GRAS) solutions that effectively limit disease. Essential oils, plant extracts, inorganic chemicals, biocontrols, defense activators, hot water treatments, and modified storage conditions have been tested to reduce losses from gray mold. Despite significant amounts of research on natural methods of control of B. cinerea postharvest, research specific to gray mold in peppers is limited. The objective of this review is to summarize the research conducted with environmentally friendly alternatives to chemical fungicides to control this important pathogen of peppers postharvest. To ensure a steady supply of healthy and nutritious produce, more research is needed on the development, use, and application of non-hazardous Botrytis control methods. Until an effective solution is found, using a combined approach including environmental controls, sanitation, and GRAS products remain paramount to limit Botrytis fruit rot of peppers postharvest.

Synthesis, Characterization and Properties of Antibacterial Polyurethanes

Novel physically crosslinked polyurethane (PUII), based on isophorone diisocyanates, was prepared by a conventional two-step method. The chemical structures of the PUII were characterized by fourier transform infrared (FTIR), proton nuclear magnetic resonance (1H NMR), gel permeation chromatography (GPC), scanning electron microscopy (SEM) and DSC. The PUII hydrogels were subjected to solvent-induced self-assembly in THF + water to construct a variety of morphologies. The self-assembly morphology of the PUII was observed by scanning electron microscopy (SEM). The PUII films with different amounts (0.2%, 0.4%, 0.6%, 0.8%, 1.0%) of 1,3,5-Tris(2-hydroxyethyl)hexahydro-1,3,5-triazine (TNO) were challenged with Escherichia coli, Staphylococcus aureus, Bacillus subtilis and Gray mold. The results showed that when a small amount of antibacterial agent were added, the antibacterial effect of films on Botrytis cinerea was more obvious. The mechanical evaluation shows that the antimicrobial polyurethane films exhibit good mechanical properties.

An Insight Into Research and Investigations of Gray Mold Focused on Botrytis cinerea

Modern day agriculture focuses on the crop yield, cost, and space. Most of the investigations in the agricultural sector are aimed at rendering environmental friendliness to the application method and synthesizing new varieties of crops that are resistant to the attacks of microorganisms. Also, new fertilizers and pesticides are being developed. Plants such as grapes, raspberries, and strawberries are considered cash crops. Many useful compounds are synthesized from them. Pharmaceutical intermediates and products are synthesized from plants which have medicinal properties. Climatic conditions and soil properties are manipulated for confined and safe cultivation of these plants. It results in reduction in temperature and change in humidity, which in turn causes growth of undesirable species and diseases in the plants. The most common among these species is the fungi Botrytis cinerea. Many crops are affected adversely due to Botrytis cinerea (B. cinerea). In this chapter, a review on studies and investigations on gray mold for its effects on plants and control is carried with focus on Botrytis cinerea.

Predicting symptoms of downy mildew, powdery mildew, and gray mold diseases of grapevine through machine learning

Downy mildew, powdery mildew, and gray mold are major diseases of grapevine with a strong negative impact on fruit yield and fruit quality. These diseases are controlled by the application of chemicals, which may cause undesirable effects on the environment and on human health. Thus, monitoring and forecasting crop disease is essential to support integrated pest management (IPM) measures. In this study, two tree-based machine learning (ML) algorithms, random forest and C5.0, were compared to test their capability to predict the appearance of symptoms of grapevine diseases, considering meteorological conditions, spatial indices, the number of crop protection treatments and the frequency of monitoring days in which symptoms were recorded in the previous year. Data collected in Tuscany region (Italy), on the presence of symptoms on grapevine, from 2006 to 2017 were divided with an 80/20 proportion in training and test set, data collected in 2018 and 2019 were tested as independent years for downy mildew and powdery mildew. The frequency of symptoms in the previous year and the cumulative precipitation from April to seven days before the monitoring day were the most important variables among those considered in the analysis for predicting the occurrence of disease symptoms. The best performance in predicting the presence of symptoms of the three diseases was obtained with the algorithm C5.0 by applying (i) a technique to deal with imbalanced dataset (i.e., symptoms were detected in the minority of observations) and (ii) an optimized cut-off for predictions. The balanced accuracy achieved in the test set was 0.8 for downy mildew, 0.7 for powdery mildew and 0.9 for gray mold. The application of the models for downy mildew and powdery mildew in the two independent years (2018 and 2019) achieved a lower balanced accuracy, around 0.7 for both the diseases. Machine learning models were able to select the best predictors and to unravel the complex relationships among geographic indices, bioclimatic indices, protection treatments and the frequency of symptoms in the previous year.