Raman spectroscopy-based diagnostics of water deficit and salinity stresses in two accessions of peanut

Can Metabolomic Approaches Become a Tool for Improving Early Plant Disease Detection and Diagnosis with Modern Remote Sensing Methods? A Review

The various areas of ultra-sensitive remote sensing research equipment development have provided new ways for assessing crop states. However, even the most promising areas of research, such as hyperspectral remote sensing or Raman spectrometry, have not yet led to stable results. In this review, the main methods for early plant disease detection are discussed. The best proven existing techniques for data acquisition are described. It is discussed how they can be applied to new areas of knowledge. The role of metabolomic approaches in the application of modern methods for early plant disease detection and diagnosis is reviewed. A further direction for experimental methodological development is indicated. The ways to increase the efficiency of modern early plant disease detection remote sensing methods through metabolomic data usage are shown. This article provides an overview of modern sensors and technologies for assessing the biochemical state of crops as well as the ways to apply them in synergy with existing data acquisition and analysis technologies for early plant disease detection.

Non-invasive identification of combined salinity stress and stalk rot disease caused by Colletotrichum graminicola in maize using Raman spectroscopy

Food security is an emerging problem that is faced by our civilization. There are millions of people around the world suffering from various kinds of malnutrition. The number of people that starve will only increase considering the continuous growth of the world's population. The problem of food security can be addressed by timely detection and identification biotic and abiotic stresses in plants that drastically reduce the crop yield. A growing body of evidence suggests that Raman spectroscopy (RS), an emerging analytical technique, can be used for the confirmatory and non-invasive diagnostics of plant stresses. However, it remains unclear whether RS can efficiently disentangle biotic and abiotic stresses, as well as detect both of them simultaneously in plants. In this work, we modeled a stalk rot disease in corn by inoculating the plant stalks with Colletotrichum graminicola. In parallel, we subjected plants to salt stress, as well as challenging plants with both stalk rot disease and salinity stress simultaneously. After the stresses were introduced, Raman spectra were collected from the stalks to reveal stress-specific changes in the plant biochemistry. We found that RS was able to differentiate between stalk rot disease and salinity stresses with 100% accuracy, as well as predict presence of both of those stresses in plants on early and late stages. These results demonstrate that RS is a robust and reliable approach that can be used for confirmatory, non-destructive and label-free diagnostics of biotic and abiotic stresses in plants.

Differentiation of advanced generation mutant wheat lines: Conventional techniques versus Raman spectroscopy

This research aimed to assess the feasibility of utilizing Raman spectroscopy in plant breeding programs. For this purpose, the evaluation of the mutant populations set up the application of 4 mM NaN₃ to the somatic embryos obtained from mature wheat (Triticum aestivum L. Adana-99 cv.) embryos. Advanced wheat mutant lines, which were brought up to the seventh generation with salt stress tolerance by following in vitro and in vivo environments constructed by mutated populations, were evaluated using conventional techniques [measurement of antioxidant enzyme activities (SOD, CAT, and POX), total chlorophyll, TBARS, and proline contents; measurement of the concentration of Na⁺ and K⁺ ions; and evaluation of gene expression by qPCR (TaHKT2;1, TaHKT1;5, TaSOS1, TaNa⁺/H⁺ vacuolar antiporter, TaV-PPase, TaV-ATPase, and TaP5CS)] and Raman spectroscopy. In this research, no significant difference was found in the increase of SOD, CAT, and POX antioxidant enzyme activities between the salt-treated and untreated experimental groups of the commercial cultivar, while there was a statistically significant increase in salt-treated advanced generation mutant lines as compared to control and the salt-treated commercial cultivar. Proline showed a statistically significant increase in all experimental groups compared to the untreated commercial cultivar. The degradation in the amount of chlorophyll was lower in the salt-treated advanced generation mutant lines than in the salt-treated commercial cultivar. According to gene expression studies, there were statistical differences at various levels in terms of Na⁺ and/or K⁺ uptake from soil to plant (TaHKT2;1, TaHKT1;5, and TaSOS1), and Na⁺ compartmentalizes into the cell vacuole (TaNa⁺/H⁺ vacuolar antiporter, Ta vacuolar pyrophosphatase, and Ta vacuolar H⁺-ATPase). The expression activity of TaP5CS, which is responsible for the transcription of proline, is similar to the content of proline in the current study. As a result of Raman spectroscopy, the differences in peaks represent the protein-related bands in mutant lines having a general decreasing trend in intensity when compared to the commercial cultivar. Amide-I (1,630 and 1,668 cm^-1), Histidine, Lysine, Arginine, and Leucine bands (823, 849, 1,241, 1,443, and 1,582 cm^-1) showed decreasing wavenumbers. Beta-carotene peaks at 1,153 and 1,519 cm^-1 showed increasing trends when the normalized Raman intensities of the mutant lines were compared.

Spectral-Based Classification of Genetically Differentiated Groups in Spring Wheat Grown under Contrasting Environments

The global concern about the gap between food production and consumption has intensified the research on the genetics, ecophysiology, and breeding of cereal crops. In this sense, several genetic studies have been conducted to assess the effectiveness and sustainability of collections of germplasm accessions of major crops. In this study, a spectral-based classification approach for the assignment of wheat cultivars to genetically differentiated subpopulations (genetic structure) was carried out using a panel of 316 spring bread cultivars grown in two environments with different water regimes (rainfed and fully irrigated). For that, different machine-learning models were trained with foliar spectral and genetic information to assign the wheat cultivars to subpopulations. The results revealed that, in general, the hyperparameters ReLU (as the activation function), adam (as the optimizer), and a size batch of 10 give neural network models better accuracy. Genetically differentiated groups showed smaller differences in mean wavelengths under rainfed than under full irrigation, which coincided with a reduction in clustering accuracy in neural network models. The comparison of models indicated that the Convolutional Neural Network (CNN) was significantly more accurate in classifying individuals into their respective subpopulations, with 92 and 93% of correct individual assignments in water-limited and fully irrigated environments, respectively, whereas 92% (full irrigation) and 78% (rainfed) of cultivars were correctly assigned to their respective classes by the multilayer perceptron method and partial least squares discriminant analysis, respectively. Notably, CNN did not show significant differences between both environments, which indicates stability in the prediction independent of the different water regimes. It is concluded that foliar spectral variation can be used to accurately infer the belonging of a cultivar to its respective genetically differentiated group, even considering radically different environments, which is highly desirable in the context of crop genetic resources management.

Good vibrations: Raman spectroscopy enables insights into plant biochemical composition

Non-invasive techniques are needed to enable an integrated understanding of plant metabolic responses to environmental stresses. Raman spectroscopy is one such technique, allowing non-destructive chemical characterisation of samples in situ and in vivo and resolving the chemical composition of plant material at scales from microns to metres. Here, we review Raman band assignments of pigments, structural and non-structural carbohydrates, lipids, proteins and secondary metabolites in plant material and consider opportunities this technology raises for studies in vascular plant physiology.

Combined remediation effects of biochar and organic fertilizer on immobilization and dissipation of neonicotinoids in soils

Neonicotinoid (NEO) pesticides have become a potential risk to ecological safety and human health after application. The combined use of biochar and organic fertilizer (OF) is a promising approach to reduce pesticide adverse effects and improve soil fertility in agricultural soils. However, the combined remediation effects of biochar and OF on immobilization and dissipation of NEOs in soils have not previously been systematically investigated. In this study, biochars derived from peanut shell prepared at low/high pyrolysis temperatures (PS400 and PS900) were combined with composted chicken manure (CCM) as an example for OF to remediate contaminated soils toward six typical NEOs, nitenpyram (NIT), thiamethoxam (THIA), clothianidin (CLO), imidacloprid (IMI), acetamiprid (ACE), thiacloprid (THI). Results shown that both biochars and CCM were effective in improving soil sorption capacity and immobilization efficiency. The Freundlich affinity parameters (K_f) of NEOs in soils increased 7.2-12.0 times after the combined remediation of biochar and CCM, and the K_f of six NEOs had negative correlation with their lipophilicity (p < 0.05), which followed by THI > ACE ≈ IMI > CLO > THIA > NIT. Meanwhile, NEOs-abiotic degradation was accelerated by biochar, CCM and their combined addition by adjusting soil pH and stimulating hydrolysis action. Biotic degradation was dominant in NEOs dissipation processes in amended soils, and the contribution ratios of biotic degradation (CR_bio) were in the range of 25.4-99.0%. The combined use of biochar and CCM selectively stimulated the relative abundance of NEOs-degraders, which simplified abiotic degradation of -NO₂-containing NEOs (viz., NIT, THIA, CLO, and IMI), but inhibited -C≡N-containing NEOs (viz., ACE and THI). The combined remediation provided a strategy for immobilizing NEOs and facilitating dissipation of -NO₂-containing NEOs in soils. The results in this study provide valuable information for policymakers and decision-makers to choose appropriate soil remediation approaches with respect to the NEO types.

Confirmatory detection and identification of biotic and abiotic stresses in wheat using Raman spectroscopy

Wheat is one of the oldest and most widely cultivated staple food crops worldwide. Wheat encounters an array of biotic and abiotic stresses during its growth that significantly impact the crop yield and consequently global food security. Molecular and imaging methods that can be used to detect such stresses are laborious and have numerous limitations. This catalyzes the search for alternative techniques that can be used to monitor plant health. Raman spectroscopy (RS) is a modern analytical technique that is capable of probing structure and composition of samples non-invasively and non-destructively. In this study, we investigate the accuracy of RS in confirmatory diagnostics of biotic and abiotic stresses in wheat. Specifically, we modelled nitrogen deficiency (ND) and drought, key abiotic stresses, and Russian wheat aphid (Diuraphis noxia) infestation and viral diseases: wheat streak mosaic virus (WSMV) and Triticum mosaic virus (TriMV), economically significant biotic stresses in common bread wheat. Raman spectra as well as high pressure liquid chromatography (HPLC)-based analyses revealed drastically distinct changes in the intensity of carotenoid vibration (1185 cm^-1) and in the concentration of lutein, chlorophyll, and pheophytin biomolecules of wheat, triggered in response to aforementioned biotic and abiotic stresses. The biochemical changes were reflected in unique vibrational signatures in the corresponding Raman spectra, which, in turn could be used for ~100% accurate identification of biotic and abiotic stresses in wheat. These results demonstrate that a hand-held Raman spectrometer could provide an efficient, scalable, and accurate diagnosis of both biotic as well as abiotic stresses in the field.

Raman spectroscopy enables highly accurate differentiation between young male and female hemp plants

Hand-held Raman spectroscopy can be used for highly accurate differentiation between young male and female hemp plants. This differentiation is based on significantly different concentration of lutein in these plants. Last year, a global market of only industrial hemp attained the value of USD 4.7 billion. It is by far the fastest growing market with projected growth of 22.5% between 2021 and 2026. Hemp (Cannabis sativa L.) is a dioecious species that has separate male and female plants. In hemp farming, female plants are strongly preferred because male plants do not produce sufficient amount of cannabinoids. Male plants are also eliminated to minimize a possibility of uncontrolled cross-fertilization of plants. Silver treatments can induce development of male flowers on genetically female plants in order to produce feminized seed. Resulting cannabinoid hemp production fields should contain 100% female plants. However, any unintended pollination from male plants can produce unwanted males in production fields. Therefore, there is a growing demand for a label-free, non-invasive, and confirmatory approach that can be used to differentiate between male and female plants before flowering. In this study, we examined the extent to which Raman spectroscopy, an emerging optical technique, can be used for the accurate differentiation between young male and female hemp plants. Our findings show that Raman spectroscopy enables differentiation between male and female plants with 90% and 94% accuracy on the level of young and mature plants, respectively. Such analysis is entirely non-invasive and non-destructive to plants and can be performed in seconds using a hand-held spectrometer. High-performance liquid chromatography (HPLC) analysis and collected Raman spectra demonstrate that this spectroscopic differentiation is based on significantly different concentrations of carotenoids in male vs female plants. These findings open up a new avenue for quality control of plants grown in both field and a greenhouse.