Fourier-transform infrared (FT-IR) spectroscopy analysis discriminates asymptomatic and symptomatic Norway spruce trees

Phytochemical Analysis of Anacamptis coriophora Plant Cultivated Using Ex Vitro Symbiotic Propagation

This study aims to investigate the functional groups and phytochemical profile of Anacamptis coriophora seeds, tubers, and flowers. Symbiotic seedlings produced using the ex vitro method were transferred to their natural habitat and grown to analyze the functional groups and phytochemical profiles of tubers and flowers. The life cycles of the transferred seedlings were monitored, and tubers and flowers were harvested for analysis. ATR-FTIR spectroscopy revealed the presence of functional groups such as polysaccharides, lignin, and proteins in both tubers and flowers. Differences in spectral frequencies between first-year and second-year tubers were observed. Fatty acid analysis identified 30 different compounds in seeds, flowers, and tubers, with linoleic acid being the most abundant (27 % in seeds, 33 % in tubers), and palmitic acid present in flowers (24 %). GC-MS analysis of ethanol extracts from these components highlighted the presence of 32 compounds, including hydroxyacetic acid, hydrazide, cytidine (Z)-7-hexadecenal, 2,2-dimethoxyethane, 2,5,6-trimethyldecane, and butanamide, 4-amino-N-hydroxy. A. coriophora's tubers, flowers, and seeds may contain active metabolites with therapeutic potential. These results are valuable for the commercial cultivation of the plant.

Physicochemical, rheological and structural properties of flours from six quinoa cultivars grown in Colombia

Background

Inclusion of quinoa in the diet of consumers has generated a challenge for quinoa producers and food processors, which involves the study of new cultivars and the functional properties of their flours.

Methods

Six quinoa cultivars (Titicaca, Blanca real, Soracá, Pasankalla, Puno and Nariño) were analyzed for their proximate composition using the methodologies proposed by the Association of Official Analytical Collaboration, AOAC. A rheological analysis was carried out with flours from each cultivar. A sequential test including a flow test, a pasting test and another flow test was programmed to evaluate the flow behavior before and after a heating process. In addition, the structural properties of the cultivar flours were evaluated by Fourier Transform Infrared spectroscopy (FTIR).

Results

It was found that the Pasankalla, Titicaca and Soracá cultivars had a higher (p < 0.05) protein content, while the Puno, Pansakalla and Blanca real cultivars stood out for their higher (p < 0.05) lipid content. On the other hand, it was found that before heating, all quinoa flour dispersions had a dilatant flow (n > 1), but after heating, all of them showed a decrease of index values, where the flours of the Titicaca and Pasankalla cultivars were more affected with a tendency toward a Newtonian flow (n ≈ 1). The pasting test showed that the viscosity varied according to the cultivar tested. It is noteworthy that both Titicaca and Soracá presented a high peak viscosity (0.16 ± 0.01 and 0.13 ± 0.02 Pa·s respectively) and different setback values on cooling (0.100 ± 0.028 and 0.01 ± 0.01 Pa·s respectively). Spectroscopic analysis showed a direct relationship between the intensity of the peaks and the nutritional content of the flours. In addition, secondary protein structures such as β-sheet, β-Turn, α-Helix and Random Coil were identified after deconvolution of the spectra. The differences in the protein structures of each cultivar could allow their identification by this methodology.

Conclusion

It can be concluded that quinoa flours from the six cultivars could be used for the formulation of different food products, such as beverages, baked goods, snacks, pasta and others, acting as nutritional improvers and modifiers of rheological, textural and functional properties.

Evaluation of Spectroscopy and Methodological Pre-Treatments to Estimate Soil Nutrients in the Vineyard

The characterization of vineyard soil is a key issue for crop management, which directly affects the quality and yield of grapes. However, traditional laboratory analysis of soil properties is tedious and both time and cost consuming, which is not suitable for precision viticulture. For this reason, a fast and convenient soil characterization technique is needed for soil quality assessment and precision soil management. Here, spectroscopy appears as a suitable alternative to assist laboratory analysis. This work focuses on estimating soil properties by spectroscopy. Our study was carried out using 96 soil samples collected from three vineyards in Rias Baixas Designation of Origen (Galicia, Spain). The soils that were characterized include nitrogen (N), organic matter (OM) and clay content (Clay). The presented work compared two regression techniques (partial least squares (PLSR) and random forest (RF)) and four spectral ranges: visible—VIS (350–700 nm), near infrared—NIR (701–1000 nm), short wave infrared—SWIR (1001–2500 nm) and VIS-NIR-SWIR (350–2500 nm) in order to identify the more suitable prediction models. Moreover, the effect of pre-treatments in reflectance data (smoothing Svitzky–Golay, SG, baseline normalization, BN, first derivative, FD, standard normal variate, SNV, logarithm of 1/reflectance or spectroscopy (SP) and detrending, SNV-D) was evaluated. Finally, continuous maps of the soil properties were created based on estimated values of regression models. Our results identified PLSR as the best regression technique, with less computation time than RF. The data improved after applying transformation in reflectance data, with the best results from spectroscopy pre-treatment (logarithm of 1/Reflectance). PLSR performances have obtained determination coefficients (R2) of 0.69, 0.73 and 0.52 for nitrogen, organic matter, and clay, respectively, with acceptable accuracy (RMSE: 0.03, 1.06 and 2.90 %) in a short time. Furthermore, the mapping of soil vineyards generates information of high interest for the precision viticulture management, as well as a comparison between the methodologies used.

Advanced applications of mass spectrometry imaging technology in quality control and safety assessments of traditional Chinese medicines

ETHNOPHARMACOLOGICAL RELEVANCE

Traditional Chinese medicines (TCMs) have made great contributions to the prevention and treatment of human diseases in China, and especially in cases of COVID-19. However, due to quality problems, the lack of standards, and the diversity of dosage forms, adverse reactions to TCMs often occur. Moreover, the composition of TCMs makes them extremely challenging to extract and isolate, complicating studies of toxicity mechanisms.

AIM OF THE REVIEW

The aim of this paper is therefore to summarize the advanced applications of mass spectrometry imaging (MSI) technology in the quality control, safety evaluations, and determination of toxicity mechanisms of TCMs.

MATERIALS AND METHODS

Relevant studies from the literature have been collected from scientific databases, such as "PubMed", "Scifinder", "Elsevier", "Google Scholar" using the keywords "MSI", "traditional Chinese medicines", "quality control", "metabolomics", and "mechanism".

RESULTS

MSI is a new analytical imaging technology that can detect and image the metabolic changes of multiple components of TCMs in plants and animals in a high throughput manner. Compared to other chemical analysis methods, such as liquid chromatography-mass spectrometry (LC-MS), this method does not require the complex extraction and separation of TCMs, and is fast, has high sensitivity, is label-free, and can be performed in high-throughput. Combined with chemometrics methods, MSI can be quickly and easily used for quality screening of TCMs. In addition, this technology can be used to further focus on potential biomarkers and explore the therapeutic/toxic mechanisms of TCMs.

CONCLUSIONS

As a new type of analysis method, MSI has unique advantages to metabolic analysis, quality control, and mechanisms of action explorations of TCMs, and contributes to the establishment of quality standards to explore the safety and toxicology of TCMs.

Rapid determination of lambda-cyhalothrin residues on Chinese cabbage based on MIR spectroscopy and a Gustafson–Kessel noise clustering algorithm

Pesticide residues exceeding the standard in Chinese cabbage is harmful to human health. In order to quickly, non-destructively and effectively qualitatively analyze lambda-cyhalothrin residues on Chinese cabbage, a method involving a Gustafson–Kessel noise clustering (GKNC) algorithm was proposed to cluster the mid-infrared (MIR) spectra. A total of 120 Chinese cabbage samples with three different lambda-cyhalothrin residue levels (no lambda-cyhalothrin, and cases where the ratios of lambda-cyhalothrin and water were 1 : 500 and 1 : 100) were scanned using an Agilent Cary 630 FTIR spectrometer for collecting the MIR spectra. Next, multiple scatter correction (MSC) was employed to eliminate the effects of light scattering. Furthermore, principal component analysis (PCA) and linear discriminant analysis (LDA) were utilized to reduce the dimensionality and extract the feature information from the MIR spectra. Finally, fuzzy c-means (FCM) clustering, Gustafson–Kessel (GK) clustering, noise clustering (NC) and the GKNC algorithm were applied to cluster the MIR spectral data, respectively. The experimental results showed that the GKNC algorithm gave the best classification performance compared against the other three fuzzy clustering algorithms, and its highest clustering accuracy reached 93.3%. Therefore, the GKNC algorithm coupled with MIR spectroscopy is an effective method for detecting lambda-cyhalothrin residues on Chinese cabbage.

Pesticide residues exceeding the standard in Chinese cabbage is harmful to human health.

Plant Disease Sensing: Studying Plant-Pathogen Interactions at Scale

Plant disease threatens the environmental and financial sustainability of crop production, causing $220 billion in annual losses. The dire threat disease poses to modern agriculture demands tools for better detection and monitoring to prevent crop loss and input waste. The nascent discipline of plant disease sensing, or the science of using proximal and/or remote sensing to detect and diagnose disease, offers great promise to extend monitoring to previously unachievable resolutions, a basis to construct multiscale surveillance networks for early warning, alert, and response at low latency, an opportunity to mitigate loss while optimizing protection, and a dynamic new dimension to agricultural systems biology. Despite its revolutionary potential, plant disease sensing remains an underdeveloped discipline, with challenges facing both fundamental study and field application. This article offers a perspective on the current state and future of plant disease sensing, highlights remaining gaps to be filled, and presents a bold vision for the future of global agriculture.

Soil-applied selenite increases selenium and reduces cadmium in roots of Moringa oleifera

Deficiency of selenium (Se) will lead to malnutrition and decreased immune function of the body. There is a common phenomenon of Se deficiency in foods. In this study, different concentrations of sodium selenite (Na₂SeO₃) were applied to Moringa oleifera grownin soil. The purpose was to explore the feasibility of Se biofortification of M. oleifera root. The effect of exogenous Se on the accumulation of Se and cadmium (Cd) in the roots of M. oleifera was studied by inductively coupled plasma mass spectrometry, and the mechanism of exogenous Se on the accumulation of Se and Cd in the roots was studied by Fourier transform infrared spectroscopy (FTIR) combined with principal component analysis and partial least squares regression analysis. The results showed that Na₂SeO₃ significantly affected the accumulation of Se and Cd in the roots (p < 0.05). The increase in Se was highest when Na₂SeO₃ was around 4.0 mg/kg, which increased by 315% compared with the control. The decrease in Cd was the lowest when Na₂SeO₃ was around 2.0 mg/kg, which decreased by 80% compared with the control. The results of FTIR analysis showed that Na₂SeO₃ treatment changed the carboxylate, phosphate radical, hemicellulose and protein in roots of M. oleifera, while the increase of Se was related to hemicellulose, protein, polysaccharide and lignin, and the decrease of Cd was related to hemicellulose and protein. The results showed that exogenous Se increased the accumulation of Se and inhibited the absorption of Cd. Therefore, the roots of M. oleifera can be used in Se biofortified products.