The health benefits associated with consumption of fresh produce have been clearly demonstrated and encouraged by international nutrition and health authorities. However, since fresh produce is usually minimally processed, increased consumption of fresh fruits and vegetables has also led to a simultaneous escalation of foodborne illness cases. According to the report by the World Health Organization (WHO), 1 in 10 people suffer from foodborne diseases and 420,000 die every year globally. In comparison to other processed foods, fresh produce can be easily contaminated by various routes at different points in the supply chain from farm to fork. This review is focused on the identification and characterization of possible sources of foodborne illnesses from chemical, biological, and physical hazards and the applicable methodologies to detect potential contaminants. Agro-chemicals (pesticides, fungicides and herbicides), natural toxins (mycotoxins and plant toxins), and heavy metals (mercury and cadmium) are the main sources of chemical hazards, which can be detected by several methods including chromatography and nano-techniques based on nanostructured materials such as noble metal nanoparticles (NMPs), quantum dots (QDs) and magnetic nanoparticles or nanotube. However, the diversity of chemical structures complicates the establishment of one standard method to differentiate the variety of chemical compounds. In addition, fresh fruits and vegetables contain high nutrient contents and moisture, which promote the growth of unwanted microorganisms including bacterial pathogens (Salmonella, E. coli O157: H7, Shigella, Listeria monocytogenes, and Bacillus cereus) and non-bacterial pathogens (norovirus and parasites). In order to detect specific pathogens in fresh produce, methods based on molecular biology such as PCR and immunology are commonly used. Finally, physical hazards including contamination by glass, metal, and gravel in food can cause serious injuries to customers. In order to decrease physical hazards, vision systems such as X-ray inspection have been adopted to detect physical contaminants in food, while exceptional handling skills by food production employees are required to prevent additional contamination.

MADS-box genes encode a family of transcription factors which involve in diverse developmental processes in flowering plants. Because flowering time determines the timing of transition from vegetative to reproductive stage and time to harvest, it would be a significant trait not only to plant it-self but also to breeders. The sequences and gene structures of Arabidopsis MADS-box genes are conserved in model legumes. However, complex genome structure, in soybean, makes it difficult to identify actual genes related to flowering and maturity, although QTL researches have been generally conducted. Therefore, we hypothesized that putative MADS-box genes around the flowering time and maturity QTLs would be candidate genes for those loci. In this study, after surveying 84 QTLs highly associated with maturity and flowering, the QTLs were selected if they were located near 473 putative MADS-box genes. Finally, we found the highly associated 16 SNPs at non-coding region of the putative MADS-box gene around the QTL in 28 late maturity cultivars and 28 early maturity cultivars. Furthermore, by comparing genetic diversity in the cultivated soybeans of late and early maturity groups as well as 20 wild soybeans, selection pattern during domestication was predicted.