Improved organic and pesticide-free rice (Oryza sativa L.) authentication based on multiple stable isotope ratio analysis and rice milling state.

This study looked at the application of multiple bulk stable isotope ratio analysis to accurately authenticate organic rice and counteract organic fraud within the expanding global organic market. Variations of δ13C, δ15N, δ18O, and δ34S in organic, pesticide-free, and conventional rice were assessed across different milling states (brown, milled, and bran). Individual stable isotope ratio alone such as δ15N demonstrated limited capacity to correctly differentiate organic, pesticide-free, and conventional rice. A support vector machine model-incorporating δ13C, δ15N, δ18O, and δ34S in milled rice-yielded overall predictability (95%) in distinguishing organic, pesticide-free, and conventional rice, where δ18O emerged as the pivotal variable based on the feature weights in the SVM model. These findings suggest the potential of multi-isotope and advanced statistical approaches in combating organic fraud and ensuring authenticity in the food supply chain.

Impact of nanopollution on plant growth, photosynthesis, toxicity, and metabolism in the agricultural sector: An updated review.

Nanotechnology provides distinct benefits to numerous industrial and commercial fields, and has developed into a discipline of intense interest to researchers. Nanoparticles (NPs) have risen to prominence in modern agriculture due to their use in agrochemicals, nanofertilizers, and nanoremediation. However, their potential negative impacts on soil and water ecosystems, as well as plant growth and physiology, have caused concern for researchers and policymakers. Concerns have been expressed regarding the ecological consequences and toxicity effects associated with nanoparticles as a result of their increased production and usage. Moreover, the accumulation of nanoparticles in the environment poses a risk, not only because of the possibility of plant damage but also because nanoparticles may infiltrate the food chain. In this review, we have documented the beneficial and detrimental effects of NPs on seed germination, shoot and root growth, plant biomass, and nutrient assimilation. Nanoparticles exert toxic effects by inducing ROS generation and stimulating cytotoxic and genotoxic effects, thereby leading to cell death in several plant species. We have provided possible mechanisms by which nanoparticles induce toxicity in plants. In addition to the toxic effects of NPs, we highlighted the importance of nanomaterials in the agricultural sector. Thus, understanding the structure, size, and concentration of nanoparticles that will improve plant growth or induce plant cell death is essential. This updated review reveals the multifaceted connection between nanoparticles, soil and water pollution, and plant biology in the context of agriculture.

Long-term isotopic model study for ecofriendly rice (Oryza sativa L.) authentication: Updating a case study in South Korea.

To overcome the lack of consumer trust in ecofriendly products due to low reliability of ecofriendly certification and decreasing areas certified for growing ecofriendly agricultural products, alternative approaches for reliable certification are required. Isotopic-chemometric analysis has potential for determining organic authenticity, but previous studies have struggled to differentiate the authenticities of different rice types. The present study examined 5-year variations in δ13C and δ15N in ecofriendly and conventional rice sold at retail markets in South Korea, while assessing the feasibility of discriminant models for authentication of organic rice. Supporting vector machine analysis showed 4.4-14.6% better overall predictability of rice types than discriminant analysis and was effective in discriminating organic or conventional rice from pesticide-free rice, potentially enabling high-throughput screening to authenticate organic rice at marketplaces. Our findings provide reliable information for authenticating ecofriendly rice, with a potential to improve consumer safety and thus the confidence in organic products.

Regional Characterization Study of Fatty Acids and Tocopherol in Organic Milk as a Tool for Potential Geographical Identification.

Reliable geographical identification can protect producers of excellent agroproducts, and also provide reliable purchasing information to satisfy consumers. Therefore, this study aimed to evaluate the regional and monthly variation in fatty acid (FA) and tocopherol (TOC) in organic milk (OM) and develop a geographical discriminant model of OM in Korea. In this study, OM had α-TOC and showed a regional or monthly difference of 3-5%. Moreover, C16:0, C18:1 n9 cis + trans, C18:0, and C14:0 were the predominant FAs in OM, and OM mostly had higher ∑UFA, including nutritionally desirable FAs; but lower ∑SFA among four regions or in April and August (p < 0.001). The model prepared using stepwise discriminant analysis showed a classification accuracy of 100% for original and cross-validated sample sets. Our results have characterized regional and monthly nutritional variations of OM, thereby potentially suggesting the applicability of a reliable Korean geographical identification labeling system using nutrient compositional analysis of OM.

Potential geo-discriminative tools to trace the origins of the dried slices of shiitake (Lentinula edodes) using stable isotope ratios and OPLS-DA.

The Lentinus edodes species, known as shiitake, has a history of extensive use in many cuisines in several East Asian countries owing to its unique and pleasant flavor and texture. As international food trade increases, reliable discrimination of geographical origin is becoming increasingly crucial in Korea to identify cheaper imported Chinese shiitake. Herein, stable isotope ratios (i.e., δ13C, δ15N, δ18O, and δ34S) were measured with a stable isotope ratio mass spectrometer, and a geographical discrimination method using orthogonal projection to latent structure-discriminant analysis was developed. The externally validated discrimination method showed excellent predictability (Q2cum = 0.881) and illustrated that δ18O and δ15N were important isotope markers for the geographical discrimination of dried shiitake slices. This study extends the knowledge of geographical differences between China and Korea evidenced by the shiitake isotope signatures, thereby contributing to potential geographical authentication with broader applications for international shiitake markets.

Compound-specific δ13C and δ15N analyses of fatty acids and amino acids for discrimination of organic, pesticide-free, and conventional rice (Oryza sativa L.).

Herein, we improve the procedure for organic rice authentication using compound-specific δ13C and δ15N analyses of fatty acids and amino acids, addressing the increasing demand for accurate methods to confirm organic authenticity. Organic rice (OR) and pesticide-free rice (PFR) featured higher values of δ15Nbulk than conventional rice (CR), whereas the corresponding differences between OR and PFR were insignificant. Additionally, OR, PFR, and CR could be discriminated based on some δ13Camino-acid and δ15Namino-acid values. δ13Cbulk was correlated with most δ13Cfatty-acid (r ≥ 0.596) values, and δ15Nbulk was strongly correlated with most δ15Namino-acid (r ≥ 0.834) values. The first component in the orthogonal projection to latent structure-discriminant analysis model allowed for a clear separation between OR and PFR, and good predictability (Q2Y = 0.506). Thus, the present study improves the reliability of organic authentication when bulk stable isotope ratio analysis alone is insufficient for the accurate discrimination of OR, PFR, and CR.

Fatty Acid- and Amino Acid-Specific Isotope Analysis for Accurate Authentication and Traceability in Organic Milk.

The present study describes compound-specific δ13C and δ15N analyses of fatty acids and amino acids for improving the accurate authentication of organic milk (OM) against conventional milk (CM) collected in Korea. Most δ13Cfatty-acid and δ13Camino-acid values were lower in OM than in CM ( P < 0.05); however, most δ15Namino-acid values displayed weak discriminative power for OM authentication. Higher isotopic fractionation was observed in δ13Cfatty-acid than in δ13Camino-acid and δ15Namino-acid, with fractionation trends differing with individual amino acids. In particular, δ13Clinoleic-acid of -33.5‰ and δ13Cmyristic-acid of -28‰ were determined to be promising year-round threshold values for Korean OM authentication. The δ13Cbulk was highly correlated with δ13CAla ( r = 0.92) and δ13Coleic-acid, trans ( r = 0.77), and strong positive correlations were observed between δ13CVal and δ13CIle ( r = 0.98) and between δ15NThr and δ15NSer ( r = 0.90). Chemometric modeling for OM authentication produced a high quality model ( R2 X = 0.547, R2 Y = 0.865, and Q2 = 0.689) with reliable chemical markers, notably δ13Cmyristic-acid, δ13Clinoleic-acid, and δ13Cstearic-acid. Furthermore, the models developed for seasonal separation in OM ( Q2 = 0.954) and CM ( Q2 = 0.791) were of good quality. Our findings, based on compound-specific isotope data, improve the reliability of OM authentication in cases where bulk stable isotope ratio analysis alone is insufficient. They also provide valuable insight into the control of fraudulent OM labeling in Korea, with potential application in other countries.

Analysis of Selected Phenolic Compounds in Organic, Pesticide-Free, Conventional Rice (Oryza sativa L.) Using LC-ESI-MS/MS.

Rice (Oryza sativa L.) contains generous amounts of carbohydrates, proteins, vitamins, and dietary fibers, in addition to secondary metabolites such as phenols and flavonoids that act as antioxidants. The phenolic compounds detected in rice (organic rice (OR), conventional rice (CR), and pesticide-free rice (PFR)), namely, protocatechuic, gentisic, p-hydroxybenzoic, p-coumaric, ferulic, salicylic, and caffeic acids, are notable free radical scavengers. The sum of these phenolic compounds was found to be higher in PFR, followed by CR and OR (p < 0.0001), when the rice types were classified based on the farming system employed. In addition, significant differences were observed in the p-hydroxybenzoic acid levels for the OR and CR groups compared with the PFR groups (p < 0.01). Furthermore, greater quantities of p-coumaric acid were found in CR-08 and OR-02, although these groups contained overall higher and lower sums of phenolic compounds, respectively. Moreover, significance was observed in the sum of the phenolic compounds, although only small quantities were found in polished rice. Further research is thus required to provide a clearer picture regarding the phenolic profiles of different rice brands.

Feasibility Study for Detection of Turnip yellow mosaic virus (TYMV) Infection of Chinese Cabbage Plants Using Raman Spectroscopy.

Raman spectroscopy provides many advantages compared to other common analytical techniques due to its ability of rapid and accurate identification of unknown specimens as well as simple sample preparation. Here, we described potential of Raman spectroscopic technique as an efficient and high throughput method to detect plants infected by economically important viruses. To enhance the detection sensitivity of Raman measurement, surface enhanced Raman scattering (SERS) was employed. Spectra of extracts from healthy and Turnip yellow mosaic virus (TYMV) infected Chinese cabbage leaves were collected by mixing with gold (Au) nanoparticles. Our result showed that TYMV infected plants could be discriminated from non-infected healthy plants, suggesting the current method described here would be an alternative potential tool to screen virus-infection of plants in fields although it needs more studies to generalize the technique.

Quantitative real-time PCR assay for detection of Paenibacillus polymyxa using membrane-fusion protein-based primers.

Paenibacillus polymyxa is known to be a plant-growthpromoting rhizobacterium. The present study describes a quantitative polymerase chain reaction (qPCR) assay for the specific detection and quantitation of P. polymyxa using a primer pair based on the sequence of a membranefusion protein for the amplification of a 268 bp DNA fragment. This study reports that the qPCR-based method is applicable for the rapid and sensitive detection of P. polymyxa and can be used as an alternative method for agricultural soil monitoring.

Evaluation of soyasaponin, isoflavone, protein, lipid, and free sugar accumulation in developing soybean seeds.

A combination of analytical techniques was used to examine and quantify seed compositional components such as protein, lipid, free sugars, isoflavones, and soyasaponins during soybean development and maturation in two Korean soybean cultivars. Protein accumulation was rapid during reproductive stages, while lipid content was only relatively moderately increased. The major carbohydrate saccarides sucrose and stachyose constantly increased during the reproductive stage. Previously published results suggest that the free sugar and lipid content reached their maximal concentrations at a relatively early stage of seed development and remain constant in comparison to other chemical components. The malonylglucosides were the predominant isoflavone form followed by the glucosides, acetyl glucosides, and aglycone forms. As soybean seed matures, total soyasaponin concentration was constantly decreased until the R8 stage. Soyasaponin beta(g) was the major soyasaponin in DDMP-conjugated group B soyasaponins, followed by the non-DDMP counterpart soyasaponin I and soyasaponin A1. The ratio of total isoflavone to total soyasaponin in the developing soybean increased from 0.06 to 1.31. Protein, lipid, and free sugar contents in the developing soybean seeds showed significant positive correlations with conjugated isoflavones and total isoflavone concentration, while the lipid contents showed a negative correlation with the isoflavone aglycone. Protein, lipid, and free sugar contents showed a negative correlation with total group A and B soyasaponins and total soyasaponins; however, only the soyasaponin A content was significantly negatively correlated with free sugar content. Total soyasaponin content was negatively correlated with isoflavone content (r = -0.828 at p < 0.01).