Building a stable and accurate model for heavy metal detection in mulberry leaves based on a proposed analysis framework and laser-induced breakdown spectroscopy

Safe utilization and remediation potential of the mulberry-silkworm system in heavy metal-contaminated lands: A review

Mulberry cultivation and silkworm rearing hold a prominent position in the agricultural industries of many Asian countries, contributing to economic growth, sustainable development, and cultural heritage preservation. Applying the soil-mulberry-silkworm system (SMSS) to heavy metal (HM)-contaminated areas is significant economically, environmentally, and socially. The ultimate goal of this paper is to review the main research progress of SMSS under HM stress, examining factors affecting its safe utilization and remediation potential for HM-contaminated soils. HM tolerance of mulberry and silkworms relates to their growth stages. Based on the standards for HM contaminants in various mulberry and silkworm products and the bioconcentration factor of HMs at different parts of SMSS, we calculated maximum safe Cd and Pb levels for SMSS application on contaminated lands. Several remediation practices demonstrated mulberry's ability to grow on barren lands, absorb various HMs, while silkworm excreta can adsorb HMs and improve soil fertility. Considering multiple factors influencing HM tolerance and accumulation, we propose a decision model to guide SMSS application in polluted areas. Finally, we discussed the potential of using molecular breeding techniques to screen or develop varieties better suited for HM-contaminated regions. However, actual pollution scenarios are often complex, requiring consideration of multiple factors. More large-scale applications are crucial to enhance the theoretical foundation for applying SMSS in HM pollution risk areas.

Intelligent Rapid Detection Techniques for Low-Content Components in Fruits and Vegetables: A Comprehensive Review

Fruits and vegetables are an important part of our daily diet and contain low-content components that are crucial for our health. Detecting these components accurately is of paramount significance. However, traditional detection methods face challenges such as complex sample processing, slow detection speed, and the need for highly skilled operators. These limitations fail to meet the growing demand for intelligent and rapid detection of low-content components in fruits and vegetables. In recent years, significant progress has been made in intelligent rapid detection technology, particularly in detecting high-content components in fruits and vegetables. However, the accurate detection of low-content components remains a challenge and has gained considerable attention in current research. This review paper aims to explore and analyze several intelligent rapid detection techniques that have been extensively studied for this purpose. These techniques include near-infrared spectroscopy, Raman spectroscopy, laser-induced breakdown spectroscopy, and terahertz spectroscopy, among others. This paper provides detailed reports and analyses of the application of these methods in detecting low-content components. Furthermore, it offers a prospective exploration of their future development in this field. The goal is to contribute to the enhancement and widespread adoption of technology for detecting low-content components in fruits and vegetables. It is expected that this review will serve as a valuable reference for researchers and practitioners in this area.

Multi-phenotype response and cadmium detection of rice stem under toxic cadmium exposure

Rice stem is the sole conduit for cadmium translocation from underground to aboveground. The presence of cadmium can trigger responses of rice stem multi-phenotype, affecting metabolism, reducing yield, and altering composition, which is related to crop growth, food safety, and new energy utilization. Exploring the adversity response of plant phenotypes can provide a reliable assessment of growth status. However, the phytotoxicity and mechanism of cadmium stress on rice stem remain unclear. Here, we systematically revealed the response mechanisms of cadmium accumulation, adversity physiology, and morphological characteristic in rice stem under cadmium stress for the first time with concentration gradients of CK, 5, 25, 50, and 100 μM, and duration gradients of Day 5, Day 10, Day 15, and Day 20. The results indicated that cadmium stress led to a significant increase in cadmium accumulation, accompanied by the adversity response in stem phenotypes. Specifically, cadmium can cause fluctuations in soluble protein and disturbance of malondialdehyde (MDA), which reflects lipid peroxidation induced by cadmium accumulation. Lipid peroxidation inhibited rice growth by causing (1) a reduction in stem length, diameter, and weight, (2) suppression of air cavity, vascular bundle, parenchyma, and epidermal hair, and (3) disruption of cell structure. Furthermore, rapid detection of cadmium was realized based on the combination of laser-induced breakdown spectroscopy (LIBS) and machine learning, which took less than 3 min. The established qualitative model realized the precise discrimination of cadmium stress degrees with a prediction accuracy exceeding 92 %, and the quantitative model achieved the outstanding prediction effect of cadmium, with Rp of 0.9944. This work systematically revealed the phytotoxicity of cadmium on rice stem multi-phenotype from a novel perspective of lipid peroxidation and realized the rapid detection of cadmium in rice stem, which provided the technical tool and theoretical foundation for accurate prevention and efficient control of heavy metal risks in crops.

Effects of artificial diet rearing during all instars on silk secretion and gene transcription in Bombyx mori (Lepidoptera: Bombycidae)

Silkworms (Bombyx mori) reared on artificial diets during all instars have the advantages of simplicity and efficiency, year-round production, and reduced risk of poisoning. However, low silk yield remains a challenge, limiting its industrial application. To address this issue, the spinning behavior, nutrient absorption, and transcriptomics of silkworms were investigated. Compared with silkworms reared on mulberry leaves during all instars, those fed with artificial diets showed significantly lower cocoon weight, cocoon shell weight, cocoon shell rate, and silk gland tissue somatic index at the end of the fifth instar (P < 0.01). The spinning duration and crawling distance of silkworms reared on artificial diets were also significantly lower than those reared on mulberry leaves (P < 0.01). Regarding nutrient absorption, the dietary efficiency indexes of silkworms fed with artificial diets were significantly lower than those fed with mulberry leaves, except for the efficiency conversion of digesta to cocoon (P < 0.01). Further RNA-Seq analysis revealed 386 differentially transcribed genes between the 2 groups, with 242 upregulated and 144 downregulated genes. GO enrichment analysis showed that differential transcriptional genes were mainly enriched in organic acid metabolism, oxidation-reduction, and drug catabolism. KEGG enrichment analysis showed that differential transcriptional genes were mainly enriched in genetic information processing and metabolism pathways. Our findings provide new insights into the silk secretion and can serve as a reference for future research and application of silkworms fed with artificial diets.

Response mechanism and rapid detection of phenotypic information in rice root under heavy metal stress

The root is an important organ affecting cadmium accumulation in grains, but there is no comprehensive research involving rice root phenotype under cadmium stress yet. To assess the effect of cadmium on root phenotypes, this paper investigated the response mechanism of phenotypic information including cadmium accumulation, adversity physiology, morphological parameters, and microstructure characteristics, and explored rapid detection methods of cadmium accumulation and adversity physiology. We found that cadmium had the effect of "low-promotion and high-inhibition" on root phenotypes. In addition, the rapid detection of cadmium (Cd), soluble protein (SP), and malondialdehyde (MDA) were achieved based on spectroscopic technology and chemometrics, where the optimal prediction model was least squares support vector machine (LS-SVM) based on the full spectrum (R_p=0.9958) for Cd, competitive adaptive reweighted sampling-extreme learning machine (CARS-ELM) (R_p=0.9161) for SP and CARS-ELM (R_p=0.9021) for MDA, all with R_p higher than 0.9. Surprisingly, it took only about 3 min, which was more than 90% reduction in detection time compared with laboratory analysis, demonstrating the excellent ability of spectroscopy for root phenotype detection. These results reveal response mechanism to heavy metal and provide rapid detection method for phenotypic information, which can substantially contribute to crop heavy metal control and food safety supervision.

Laser-induced breakdown spectroscopy (LIBS) for the detection of exogenous contamination of metal elements in lily bulbs

Natural products with the underground edible part have the risk of excessive heavy metals due to the influence of the growing environment. In this study, the content of five metal elements in lily bulbs was detected by laser-induced breakdown spectroscopy (LIBS). In view of the mutual interference among elements, multivariable analysis models were established to effectively eliminate the interference. The partial least squares regression (PLSR) multivariate analysis model was evaluated by combining different data preprocessing with variable selection methods to achieve the best fit. The results show that the best regression model for Cu, Pb, Zn, Al, and Mg content achieved the coefficients determination of prediction (R_p²) values of 0.9920, 0.9737, 0.9835, 0.9723 and 0.9939, respectively, and root mean square error of prediction (RMSEP) values of 3.2386 mg/kg, 5.8559 mg/kg, 4.6334 mg/kg, 6.0073 mg/kg and 2.8103 mg/kg, respectively. Comprehensively comparing the accuracy, robustness, and number of variables of each model, it can be found that the PLSR model on the least absolute shrinkage and selection operator (LASSO) achieved good results in the quantitative prediction model of three kinds of metal elements. This indicates the superiority of the LASSO-PLSR algorithm framework and confirms the feasibility of LIBS technology for the detection of various metal elements in natural products.

The safety of Chinese medicine: A systematic review of endogenous substances and exogenous residues

BACKGROUND

Safety and toxicity have become major challenges in the internationalization of Chinese medicine. Inspite of its wide application, security problems of Chinese medicine still occur from time to time, raising widespread concerns about its safety. Most of the studies either only partially discussed the intrinsic toxicities or extrinsic harmful residues in Chinese medicine, or briefly described detoxification and attenuation methods. It is necessary to systematically discuss Chinese medicine's extrinsic and intrinsic toxic components and corresponding toxicity detoxification or detection methods as a whole.

PURPOSE

This review comprehensively summarizes various toxic components in Chinese medicine from intrinsic and extrinsic. Then the corresponding methods for detoxification or detection of toxicity are highlighted. It is expected to provide a reference for safeguards for developing and using Chinese medicine.

METHODS

A literature search was conducted in the databases, including PubMed, Web of Science,Wan-fang database, and the China National Knowledge Infrastructure (CNKI). Keywords used were safety, toxicity, intrinsic toxicities, extrinsic harmful residues, alkaloids, terpene and macrolides, saponins, toxic proteins, toxic crystals, minerals, heavy metals, pesticides, mycotoxins, sulfur dioxide, detoxification, detection, processing (Paozhi), compatibility (Peiwu), Chinese medicine, etc., and combinations of these keywords. All selected articles were from 2006 to 2022, and each was assessed critically for our exclusion criteria. Studies describe the classification of toxic components of Chinese medicine, the toxic effects and mechanisms of Chinese medicine, and the corresponding methods for detoxification or detection of toxicity.

RESULTS

The toxic components of Chinese medicines can be classified as intrinsic toxicities and extrinsic harmful residues. Firstly, we summarized the intrinsic toxicities of Chinese medicine, the adverse effects and toxicity mechanisms caused by these components. Next, we focused on the detoxification or attenuation methods for intrinsic toxicities of Chinese medicine. The other main part discussed the latest progress in analytical strategies for exogenous hazardous substances, including heavy metals, pesticides, and mycotoxins. Beyond reviewing mainstream instrumental methods, we also introduced the emerging biochip, biosensor and immuno-based techniques.

CONCLUSION

In this review, we provide an overall assessment of the recent progress in endogenous toxins and exogenous hazardous substances concerning Chinese medicine, which is expected to render deeper insights into the safety of Chinese medicine.

Study on Microdamage Quantitative Analysis of Cd and Pb in Leaves by Laser Induced Breakdown Spectroscopy

Recent years, research on the detection of heavy metals in Traditional Chinese Medicine (TCM) by laser induced breakdown spectroscopy (LIBS) have gradually increased. Current main methods of establishing calibration curve are based on grounding and pelleting of the tested samples. Although compared to digested samples, grounding and pelleting of the sample is already quite simple, it cannot fully reflect the advantages of LIBS: rapid analysis, and, also, the uneven distribution of heavy metals in the TCM is ignored. In order to avoid grinding and pelleting sample to be tested, and to achieve microdamage quantitative analysis by LIBS, this article presents a new method for establishing calibration curve. The experiment in this paper based on a study with Cd and Pb in leaves of laurel. The preparation of calibration samples and the establishment of calibration methods for microdamage quantitative analysis were presented, which proved the feasibility of microdamage quantitative analysis by LIBS. The square of the linear relationship coefficient R of Pb was higher than 0.82. This method provides a guiding method for the rapid quantitative analysis of heavy metals in TCM by LIBS.

Heavy metal detection in mulberry leaves: Laser-induced breakdown spectroscopy data

Five copper or chromium stress levels were carried out on mulberry leaf, and 20 samples were collected for each metal stress level. A total of 100 samples (copper or chromium) were processed into uniform pressed pellet. The mulberry leaf pellet was placed on a sample platform of laser-induced breakdown spectroscopy (LIBS) system. A laser was used to ablate the sample pellet and generate the emission lines, the intensity and delay time of laser ablation were 80 mJ and 4 μs respectively. To reduce the acquisition errors, 16 different positions of each sample were ablated for 5 accumulation. Then, 80 spectra were collected per sample and the average of them was considered as the sample spectrum for subsequent analysis. Finally, a total of 200 spectra of copper and chromium in mulberry leaves with a wavelength range of 219–877 nm were obtained for calibration analysis [1].