Contamination, Detection and Control of Mycotoxins in Fruits and Vegetables

Nan, Mina; Xue, Huali; Bi, Yang

doi:10.3390/toxins14050309

Cited by 38 publications

(30 citation statements)

References 196 publications

(223 reference statements)

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“…PAT-induced intestinal barrier disruption is associated with endotoxemia, systemic inflammation, and tissue damage (Zhai et al, 2019). PAT may be sex-dependent men are more sensitive than women and endocrine-disrupting activity (Saleh & Goktepe, 2019;Nan et al, 2022;Soler & Oswald, 2018).The carcinogenic intensity of PAT is controversial. WHO considers PAT to be a strong genotoxic substance.…”

Section: Patulinmentioning

confidence: 99%

Discussion on emergency management of food safety from the perspective of foodborne diseases caused by mycotoxins

Liu

2023

Food Sci. Technol

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Mycotoxins exists in foods such as grains, vegetables, fruits, milk, nuts, and meat, which can cause foodborne illnesses seriously harmful to human health. However, people have not paid enough attention to foodborne mycotoxin poisoning. This paper reviews the food in some common mycotoxin cause foodborne disease, the potential danger of mycotoxin contaminated food to human body and other issues related to food science were revealed from the clinical point of view, also concerned with the immunomodulatory effects of mycotoxin and the antitumor properties of patulin, the applicable conditions of several risk assessment models are briefly compared the emergency management measures of food safety problems caused by mycotoxin were also discussed from the perspective of prevention.

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Section: Patulinmentioning

confidence: 99%

Discussion on emergency management of food safety from the perspective of foodborne diseases caused by mycotoxins

Liu

2023

Food Sci. Technol

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“…Microorganisms, especially ascomycetous fungi, are often found in contaminated agricultural products like food crops including corns, grain, fruits, and vegetables as well as poorly conserved foods. They produce diverse mycotoxins which are hazardous to human and animal health (Dey et al 2022 ; Nan et al 2022 ; Pallares et al 2022 ). On the other hand, the microbial natural products including mycotoxins are important drug candidates (Newman 2021 ) and the enzymes involved in the biosynthesis of these compounds are valuable biocatalysts for structural modification and construction of new biosynthetic pathways (Yi et al 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Diprenylated cyclodipeptide production by changing the prenylation sequence of the nature’s synthetic machinery

Coby

Zhou

et al. 2022

Appl Microbiol Biotechnol

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Ascomycetous fungi are often found in agricultural products and foods as contaminants. They produce hazardous mycotoxins for human and animals. On the other hand, the fungal metabolites including mycotoxins are important drug candidates and the enzymes involved in the biosynthesis of these compounds are valuable biocatalysts for production of designed compounds. One of the enzyme groups are members of the dimethylallyl tryptophan synthase superfamily, which mainly catalyze prenylations of tryptophan and tryptophan-containing cyclodipeptides (CDPs). Decoration of CDPs in the biosynthesis of multiple prenylated metabolites in nature is usually initiated by regiospecific C2-prenylation at the indole ring, followed by second and third ones as well as by other modifications. However, the strict substrate specificity can prohibit the further prenylation of unnatural C2-prenylated compounds. To overcome this, we firstly obtained C4-, C5-, C6-, and C7-prenylated cyclo-l-Trp-l-Pro. These products were then used as substrates for the promiscuous C2-prenyltransferase EchPT1, which normally uses the unprenylated CDPs as substrates. Four unnatural diprenylated cyclo-l-Trp-l-Pro including the unique unexpected N1,C6-diprenylated derivative with significant yields were obtained in this way. Our study provides an excellent example for increasing structural diversity by reprogramming the reaction orders of natural biosynthetic pathways. Furthermore, this is the first report that EchPT1 can also catalyze N1-prenylation at the indole ring. Key points • Prenyltransferases as biocatalysts for unnatural substrates. • Chemoenzymatic synthesis of designed molecules. • A cyclodipeptide prenyltransferase as prenylating enzyme of already prenylated products. Graphical Abstract

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“…With the advancement of science, it became clear that plants were living organisms capable of respiration, reproduction, and susceptible to certain diseases. These diseases, caused by many microorganisms, including bacteria, viruses, and fungi, diseases can cause significant damage to crops and can harm humans, as it is the case with pathogen-produced mycotoxins and other toxicants ( Nan et al., 2022 ). Furthermore, destruction of crops by pathogens can cause human starvation.…”

Section: Introductionmentioning

confidence: 99%

A deep learning-based model for plant lesion segmentation, subtype identification, and survival probability estimation

Shoaib

Shah²,

Hussain³

et al. 2022

Front. Plant Sci.

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Plants are the primary source of food for world’s population. Diseases in plants can cause yield loss, which can be mitigated by continual monitoring. Monitoring plant diseases manually is difficult and prone to errors. Using computer vision and artificial intelligence (AI) for the early identification of plant illnesses can prevent the negative consequences of diseases at the very beginning and overcome the limitations of continuous manual monitoring. The research focuses on the development of an automatic system capable of performing the segmentation of leaf lesions and the detection of disease without requiring human intervention. To get lesion region segmentation, we propose a context-aware 3D Convolutional Neural Network (CNN) model based on CANet architecture that considers the ambiguity of plant lesion placement in the plant leaf image subregions. A Deep CNN is employed to recognize the subtype of leaf lesion using the segmented lesion area. Finally, the plant’s survival is predicted using a hybrid method combining CNN and Linear Regression. To evaluate the efficacy and effectiveness of our proposed plant disease detection scheme and survival prediction, we utilized the Plant Village Benchmark Dataset, which is composed of several photos of plant leaves affected by a certain disease. Using the DICE and IoU matrices, the segmentation model performance for plant leaf lesion segmentation is evaluated. The proposed lesion segmentation model achieved an average accuracy of 92% with an IoU of 90%. In comparison, the lesion subtype recognition model achieves accuracies of 91.11%, 93.01 and 99.04 for pepper, potato and tomato plants. The higher accuracy of the proposed model indicates that it can be utilized for real-time disease detection in unmanned aerial vehicles and offline to offer crop health updates and reduce the risk of low yield.

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Contamination, Detection and Control of Mycotoxins in Fruits and Vegetables

Cited by 38 publications

References 196 publications

Discussion on emergency management of food safety from the perspective of foodborne diseases caused by mycotoxins

Discussion on emergency management of food safety from the perspective of foodborne diseases caused by mycotoxins

Diprenylated cyclodipeptide production by changing the prenylation sequence of the nature’s synthetic machinery

A deep learning-based model for plant lesion segmentation, subtype identification, and survival probability estimation

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