Antifungal Activities of Sulfur and Copper Nanoparticles against Cucumber Postharvest Diseases Caused by Botrytis cinerea and Sclerotinia sclerotiorum

Effect of different sizes of nanocopper particles on rainbow trout (Oncorhynchus mykiss W.) spermatozoa motility kinematics

In recent years, nanocopper (Cu NPs) has gained attention due to its antimicrobial properties and potential for industrial, agricultural, and consumer applications. But it also has several effects on the aquatic environment. Widespread use of various nanoproducts has raised concerns about impacts of different nanoparticle size on environment and biological objects. Spermatozoa is a model for studying the ecotoxic effects of pollutants on cells and organisms. This study aimed to investigate the effects of different sizes of copper nanoparticles on rainbow trout spermatozoa motility, and to compare their effects with copper ionic solution. Computer assisted sperm analysis (CASA) was used to detect movement parameters at activation of gametes (direct effect) with milieu containing nanocopper of primary particle size of 40-60, 60-80 and 100 nm. The effect of the elements ions was also tested using copper sulfate solution. All products was prepared in concentration of 0, 1, 5, 50, 125, 250, 350, 500, 750, and 1000 mg Cu L-1. Six motility parameters were selected for analysis. The harmful effect of Cu NPS nanoparticle was lower than ionic form of copper but the effect depends on the motility parameters. Ionic form caused complete immobilization (MOT = 0 %, IC100) at 350 mg Cu L-1 whilst Cu NPs solution only decreased the percentage of motile sperm (MOT) up to 76.4 % at highest concentration tested of 1000 mg Cu L-1 of 40-60 nm NPs. Cu NPs of smaller particles size had more deleterious effect than the bigger one particularly in percentage of MOT and for curvilinear velocity (VCL). Moreover, nanoparticles decrease motility duration (MD). This may influence fertility because the first two parameters positively correlate with fertilization rate. However, the ionic form of copper has deleterious effect on the percentage of MOT and linearity (LIN), but in some concentrations it slightly increases VCL and MD.

Exploitation of functionalized green nanomaterials for plant disease management

A crucial determining factor in agricultural productivity is biotic stress. In addition, supply of quality food to the ever-increasing world's population has raised the food demand tremendously. Therefore, enhanced agricultural crop productivity is the only option to mitigate these concerns. It ultimately demanded the often and indiscriminate use of synthetic agrochemicals such as chemical fertilizers, pesticides, insecticides, herbicides, etc. for the management of various biotic stresses including a variety of plant pathogens. However, the food chain and biosphere are severely impacted due to the use of such harmful agrochemicals and their byproducts. Hence, it is need of hour to search for novel, effective and ecofriendly approaches for the management of biotic stresses in crop plants. Particularly, in plant disease management, efforts are being made to take advantage of newly emerged science i.e. nanotechnology for the creation of inorganic nanoparticles (NPs) such as metallic, oxide, sulphide, etc. through different routes and their application in plant disease management. Among these, green nanomaterials which are synthesized using environmentally friendly methods and materials reported to possess unique properties (such as high surface area, adjustable size and shape, and specific functionalities) making them ideal candidates for targeted disease control. Nanotechnology can stop crop losses by managing specific diseases from soil, plants, and hydroponic systems. This review mainly focuses on the application of biologically produced green NPs in the treatment of plant diseases caused due to bacteria, viruses, and fungi. The utilization of green synthesis of NPs in the creation of intelligent targeted pesticide and biomolecule control delivery systems, for disease management is considered environmentally friendly due to its pursuit of less hazardous, sustainable, and environmentally friendly methods.

Potential Antifungal Effect of Copper Oxide Nanoparticles Combined with Fungicides against Botrytis cinerea and Fusarium oxysporum

Copper oxide nanoparticles (NCuO) have emerged as an alternative to pesticides due to their antifungal effect against various phytopathogens. Combining them with fungicides represents an advantageous strategy for reducing the necessary amount of both agents to inhibit fungal growth, simultaneously reducing their environmental release. This study aimed to evaluate the antifungal activity of NCuO combined with three fungicide models separately: Iprodione (IPR), Tebuconazole (TEB), and Pyrimethanil (PYR) against two phytopathogenic fungi: Botrytis cinerea and Fusarium oxysporum. The fractional inhibitory concentration (FIC) was calculated as a synergism indicator (FIC ≤ 0.5). The NCuO interacted synergistically with TEB against both fungi and with IPR only against B. cinerea. The interaction with PYR was additive against both fungi (FIC > 0.5). The B. cinerea biomass was inhibited by 80.9% and 93% using 20 mg L-1 NCuO + 1.56 mg L-1 TEB, and 40 mg L-1 NCuO + 12 µg L-1 IPR, respectively, without significant differences compared to the inhibition provoked by 160 mg L-1 NCuO. Additionally, the protein leakage and nucleic acid release were also evaluated as mechanisms associated with the synergistic effect. The results obtained in this study revealed that combining nanoparticles with fungicides can be an adequate strategy to significantly reduce the release of metals and agrochemicals into the environment after being used as antifungals.

Double- or Triple-Tiered Protection: Prospects for the Sustainable Application of Copper-Based Antimicrobial Compounds for Another Fourteen Decades

Copper (Cu)-based antimicrobial compounds (CBACs) have been widely used to control phytopathogens for nearly fourteen decades. Since the first commercialized Bordeaux mixture was introduced, CBACs have been gradually developed from highly to slightly soluble reagents and from inorganic to synthetic organic, with nanomaterials being a recent development. Traditionally, slightly soluble CBACs form a physical film on the surface of plant tissues, separating the micro-organisms from the host, then release divalent or monovalent copper ions (Cu²⁺ or Cu⁺) to construct a secondary layer of protection which inhibits the growth of pathogens. Recent progress has demonstrated that the release of a low concentration of Cu²⁺ may elicit immune responses in plants. This supports a triple-tiered protection role of CBACs: break contact, inhibit microorganisms, and stimulate host immunity. This spatial defense system, which is integrated both inside and outside the plant cell, provides long-lasting and broad-spectrum protection, even against emergent copper-resistant strains. Here, we review recent findings and highlight the perspectives underlying mitigation strategies for the sustainable utilization of CBACs.

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.

Metabolomics as a Tool to Understand Nano-Plant Interactions: The Case Study of Metal-Based Nanoparticles

Metabolomics is a powerful tool in diverse research areas, enabling an understanding of the response of organisms, such as plants, to external factors, their resistance and tolerance mechanisms against stressors, the biochemical changes and signals during plant development, and the role of specialized metabolites. Despite its advantages, metabolomics is still underused in areas such as nano-plant interactions. Nanoparticles (NPs) are all around us and have a great potential to improve and revolutionize the agri-food sector and modernize agriculture. They can drive precision and sustainability in agriculture as they can act as fertilizers, improve plant performance, protect or defend, mitigate environmental stresses, and/or remediate soil contaminants. Given their high applicability, an in-depth understanding of NPs' impact on plants and their mechanistic action is crucial. Being aware that, in nano-plant interaction work, metabolomics is much less addressed than physiology, and that it is lacking a comprehensive review focusing on metabolomics, this review gathers the information available concerning the metabolomic tools used in studies focused on NP-plant interactions, highlighting the impact of metal-based NPs on plant metabolome, metabolite reconfiguration, and the reprogramming of metabolic pathways.