Near-infrared spectroscopy (NIRS) has become a more popular approach for quantitative and qualitative analysis of feeds, foods and medicine in conjunction with an arsenal of chemometric tools. This was the foundation for the increased importance of NIRS in other fields, like genetics and transgenic monitoring. A considerable number of studies have utilized NIRS for the effective identification and discrimination of plants and foods, especially for the identification of genetically modified crops. Few previous reviews have elaborated on the applications of NIRS in agriculture and food, but there is no comprehensive review that compares the use of NIRS in the detection of genetically modified organisms (GMOs). This is particularly important because, in comparison to previous technologies such as PCR and ELISA, NIRS offers several advantages, such as speed (eliminating time-consuming procedures), non-destructive/non-invasive analysis, and is inexpensive in terms of cost and maintenance. More importantly, this technique has the potential to measure multiple quality components in GMOs with reliable accuracy. In this review, we brief about the fundamentals and versatile applications of NIRS for the effective identification of GMOs in the agricultural and food systems.

Although many studies on the effects of genetically modified (GM) crops on soil microorganisms have been carried out over the past decades, they have provided contradictory information, even for the same GM crop, owing to the diversity of the soil environments in which they were conducted. This inconsistency in results suggests that the effects of GM crops on soil microorganisms should be considered from many aspects. In this study, we investigated the effects of the GM drought-tolerant rice MSRB2-Bar-8, which expresses the CaMSRB2 gene, on soil microorganisms based on the culture-dependent and culture-independent methods. To this end, rhizosphere soils of GM and non-GM (IM) rice were analyzed for soil chemistry, population densities of soil microorganisms, and microbial community structure (using pyrosequencing technology) at three growth stages (seedling, tillering, and maturity). There was no significant difference in the soil chemistry between GM and non-GM rice. The microbial densities of the GM soils were found to be within the range of those of the non-GM rice. In the pyrosequencing analyses, Proteobacteria and Chloroflexi were dominant at the seedling stage, while Chloroflexi showed dominance over Proteobacteria at the maturity stage in both the GM and non-GM soils. An UPGMA dendrogram showed that the soil microbial communities were clustered by growth stage. Taken together, the results from this study suggest that the effects of MSRB2-Bar-8 cultivation on soil microorganisms are not significant.

A number of studies have been conducted on hybridization between transgenic Brassica napus and B. rapa or backcross of F1 hybrid to their parents. However, trait changes must be analyzed to evaluate hybrid sustainability in nature. In the present study, B. rapa and transgenic (BrAGL20) B. napus were hybridized to verify the early flowering phenomenon of F1 hybrids, and F1 hybrid traits were analyzed to predict their impact on sustainability. Flowering of F1 hybrid has been induced slightly later than that of the transgenic B. napus, but flowering was available in the greenhouse without low temperature treatment to young plant, similar to the transgenic B. napus. It is because the BrAGL20 gene has been transferred from transgenic B. napus to F1 hybrid. The size of F1 hybrid seeds was intermediate between those of B. rapa and transgenic B. napus, and ~40% of F1 pollen exhibited abnormal size and morphology. The form of the F1 stomata was also intermediate between that of B. rapa and transgenic B. napus, and the number of stomata was close to the parental mean. Among various fatty acids, the content of erucic acid exhibited the greatest change, owing to the polymorphism of parental FATTY ACID ELONGASE 1 alleles. Furthermore, F2 hybrids could not be obtained. However, BC1 progeny were obtained by hand pollination of B. rapa with F1 hybrid pollen, with an outcrossing rate of 50%.

Globally, the cultivation area of genetically modified (GM) crops is increasing dramatically. Despite their well-known benefits, they may also pose many risks to agriculture and the environment. Among the various GM crops, GM rapeseed (Brassica napus L.) is widely cultivated, mainly for oil production. At the same time, B. napus possesses a number of characteristics, including the ability to form feral populations and act as small-seeded weeds, and has a high potential for hybridization with other species. In this review, we provide an overview of the commercialization, approval status, and cultivation of GM rapeseed, as well as the status of the feral rapeseed populations. In addition, we highlight the case studies on the unintentional environmental release of GM rapeseed during transportation in several countries. Previous studies suggest that the main reason for the unintentional release is seed spillage during transport/importing of rapeseed in both GM rapeseed-cultivating and -non-cultivating countries. Despite the fact that incidents of unintentional release have been recorded often, there have been no reports of serious detrimental consequences. However, since rapeseed has a high potential for hybridization, the possibilities of gene flow within the genus, especially with B. rapa, are relatively significant, and considering their weedy properties, effective management methods are needed. Hence, we recommend that specific programs be used for the effective monitoring of environmental releases of GM rapeseed as well as management to avoid environmental and agricultural perturbations.

The feasibility of rapid and non-destructive classification of six different Amaranthus species was investigated using visible-near-infrared (Vis-NIR) spectra coupled with chemometric approaches. The focus of this research would be to use a handheld spectrometer in the field to classify six Amaranthus sp. in different geographical regions of South Korea. Spectra were obtained from the adaxial side of the leaves at 1.5 nm intervals in the Vis-NIR spectral range between 400 and 1075 nm. The obtained spectra were assessed with four different preprocessing methods in order to detect the optimum preprocessing method with high classification accuracy. Preprocessed spectra of six Amaranthus sp. were used as input for the machine learning-based chemometric analysis. All the classification results were validated using cross-validation to produce robust estimates of classification accuracies. The different combinations of preprocessing and modeling were shown to have a classification accuracy of between 71% and 99.7% after the cross-validation. The combination of Savitzky-Golay preprocessing and Support vector machine showed a maximum mean classification accuracy of 99.7% for the discrimination of Amaranthus sp. Considering the high number of spectra involved in this study, the growth stage of the plants, varying measurement locations, and the scanning position of leaves on the plant are all important. We conclude that Vis-NIR spectroscopy, in combination with appropriate preprocessing and machine learning methods, may be used in the field to effectively classify Amaranthus sp. for the effective management of the weedy species and/or for monitoring their food applications.

Surveys of weed species on upland fields were conducted in Korea to investigate the occurrence of weed flora from April to May 2014 for winter crop fields and from July to August 2014 for summer crop fields. From the nation-wide survey, 375 weed species in 50 families were identified and classified to 162 annuals, 78 biennials and 135 perennials. Based on the occurrence ratio, the most weed species belonged to Compositae (73 species). 44 and 25 weed species belonged to Poaceae and Polygonaceae, respectively, and these 183 weed species in the most five families accounted for 49% of total weed occurrence. While 287 weed species in 45 families occurred in the winter crop fields, 339 weed species in 47 families occurred in summer crop fields. The most dominant weed species in Korean upland fields were Digitaria ciliaris, followed by Portulaca oleracea, Acalypha australis, Chenopodium album, Rorippa palustris etc. 129 weed species in 25 families were considered as exotic weeds. Based on the importance analysis, the highest value was C. album followed by Amaranthus lividus, Conyza canadensis etc. This information could be useful for estimation of future weed occurrence, weed population dynamics and establishment of weed control methods in upland fields of Korea.

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Bacterial communities in rhizosphere and root nodules have significant contributions to the growth and productivity of the soybean (Glycine max (L.) Merr.). In this report, we analyzed the physiological properties and dynamics of bacterial community structure in rhizosphere and root nodules at different growth stages using BioLog EcoPlate and high-throughput sequencing technology, respectively. The BioLog assay found that the metabolic capability of rhizosphere is in increasing trend in the growth of soybeans as compared to the bulk soil. As a result of the Illumina sequencing analysis, the microbial community structure of rhizosphere and root nodules was found to be influenced by the variety and growth stage of the soybean. At the phylum level, Actinobacteria were the most abundant in rhizosphere at all growth stages, followed by Alphaproteobacteria and Acidobacteria, and the phylum Bacteroidetes showed the greatest change. But, in the root nodules Alphaproteobacteria were dominant. The results of the OTU analysis exhibited the dominance of Bradyrhizobium during the entire stage of growth, but the ratio of non-rhizobial bacteria showed an increasing trend as the soybean growth progressed. These findings revealed that bacterial community in the rhizosphere and root nodules changed according to both the variety and growth stages of soybean in the field.