Changes in the Fungal Community Assembly of Apple Fruit Following Postharvest Application of the Yeast Biocontrol Agent Metschnikowia fructicola

Microbial antagonists to biologically control postharvest decay and preserve fruit quality

Postharvest waste due to decay of fruits and vegetables negatively affects food security, while at the same time control of decay and therefore waste can be limited because of consumer concerns about use of synthetic chemicals. Use of antagonistic microorganisms is an eco-friendly technique that represents a promising alternative approach to the use of chemical methods. Understanding the interactions between antagonists and the fruit microbiome will enable the discovery of new methods to reduce postharvest waste. This article reviews different microbial agents, fungi, bacteria and yeasts that could control decay. Recent developments in the use of microorganisms for preserving postharvest fruit quality, formulation of effective antagonists, and the commercialization steps are also discussed. Antagonists control decay through either direct or indirect mechanisms while preserving the appearance, flavor, texture and nutritional value of horticultural products. Microorganisms do not fully control pathogens, and therefore they are usually used with other treatments or have their biocontrol ability modified through genetic manipulations. Despite of these limitations, commercialization of biocontrol products based on antagonists with required stability and biocontrol potential is occurring. Biocontrol of postharvest decay and waste agent is promising technology for fruit and vegetable industries. Further study is necessary to better understand mechanisms and increasing efficiency of this method.

Glycine Enhances Oxidative Stress Tolerance and Biocontrol Efficacy of Sporidiobolus pararoseus against Aspergillus niger Decay of Apples

Apples are deeply loved by people because of their rich nutritional value, but they are susceptible to rotting. The use of antagonistic yeast is a promising method for controlling postharvest fruit diseases, but biocontrol efficacy of yeast will be weakened in environmental stress. In this study, the effects of glycine (Gly) on the oxidative stress tolerance and the biocontrol efficacy of Sporidiobolus pararoseus (S. pararoseus) against Aspergillus niger (A. niger) are discussed. Under the stimulation of H2O2, the yeast cells treated with Gly (1 mM) showed lower ROS content, less mitochondrial impairment and cellular oxidative damage, and the cell survival rate was significantly higher than Gly-untreated yeast. The yeast cells exposed to Gly significantly increased the activities of antioxidant enzymes superoxide dismutase (SOD), catalase (CAT), and the content of glutathione (GSH). Notably, Gly-treated yeast cells had better biocontrol efficacy against A. niger in postharvest apples. The lesion diameter and decay incidence were reduced by 17.67 mm and 79.63% compared to the control, respectively, when S. pararoseus was treated with 1 mM Gly. Moreover, Gly-treated yeast increased the antioxidant enzymes activities and their gene expression were up-regulated in apples. These results indicated that 1 mM Gly not only reduced the oxidative damage of yeast, but also induced resistance-related enzymes of apples under oxidative stress, which contributed to enhancing the biocontrol efficacy of S. pararoseus against A. niger in apples.

Deep Learning in Precision Agriculture: Artificially Generated VNIR Images Segmentation for Early Postharvest Decay Prediction in Apples

Food quality control is an important task in the agricultural domain at the postharvest stage for avoiding food losses. The latest achievements in image processing with deep learning (DL) and computer vision (CV) approaches provide a number of effective tools based on the image colorization and image-to-image translation for plant quality control at the postharvest stage. In this article, we propose the approach based on Generative Adversarial Network (GAN) and Convolutional Neural Network (CNN) techniques to use synthesized and segmented VNIR imaging data for early postharvest decay and fungal zone predictions as well as the quality assessment of stored apples. The Pix2PixHD model achieved higher results in terms of VNIR images translation from RGB (SSIM = 0.972). Mask R-CNN model was selected as a CNN technique for VNIR images segmentation and achieved 58.861 for postharvest decay zones, 40.968 for fungal zones and 94.800 for both the decayed and fungal zones detection and prediction in stored apples in terms of F1-score metric. In order to verify the effectiveness of this approach, a unique paired dataset containing 1305 RGB and VNIR images of apples of four varieties was obtained. It is further utilized for a GAN model selection. Additionally, we acquired 1029 VNIR images of apples for training and testing a CNN model. We conducted validation on an embedded system equipped with a graphical processing unit. Using Pix2PixHD, 100 VNIR images from RGB images were generated at a rate of 17 frames per second (FPS). Subsequently, these images were segmented using Mask R-CNN at a rate of 0.42 FPS. The achieved results are promising for enhancing the food study and control during the postharvest stage.

Microbial Intervention: An Approach to Combat the Postharvest Pathogens of Fruits

Plants host diverse microbial communities, which undergo a complex interaction with each other. Plant-associated microbial communities provide various benefits to the host directly or indirectly, viz. nutrient acquisition, protection from pathogen invaders, mitigation from different biotic and abiotic stress. Presently, plant-associated microbial strains are frequently utilized as biofertilizers, biostimulants and biocontrol agents in greenhouse and field conditions and have shown satisfactory results. Nowadays, the plant/fruit microbiome has been employed to control postharvest pathogens and postharvest decay, and to maintain the quality or shelf life of fruits. In this context, the intervention of the natural fruit microbiome or the creation of synthetic microbial communities to modulate the functional attributes of the natural microbiome is an emerging aspect. In this regard, we discuss the community behavior of microbes in natural conditions and how the microbiome intervention plays a crucial role in the postharvest management of fruits.

Recent advances in research on biocontrol of postharvest fungal decay in apples

Apple is the largest fruit crop produced in temperate regions and is a popular fruit worldwide. It is, however, susceptible to a variety of postharvest fungal pathogens, including Penicillium expansum, Botrytis cinerea, Botryosphaeria dothidea, Monilia spp., and Alternaria spp. Decays resulting from fungal infections severely reduce apple quality and marketable yield. Biological control utilizing bacterial and fungal antagonists is an eco-friendly and effective method of managing postharvest decay in horticultural crops. In the current review, research on the pathogenesis of major decay fungi and isolation of antagonists used to manage postharvest decay in apple is presented. The mode of action of postharvest biocontrol agents (BCAs), including recent molecular and genomic studies, is also discussed. Recent research on the apple microbiome and its relationship to disease management is highlighted, and the use of additives and physical treatments to enhance biocontrol efficacy of BCAs is reviewed. Biological control is a critical component of an integrated management system for the sustainable approaches to apple production. Additional research will be required to explore the feasibility of developing beneficial microbial consortia and novel antimicrobial compounds derived from BCAs for postharvest disease management, as well as genetic approaches, such as the use of CRISPR/Cas9 technology.