Phytochemical Screening of the Different Cultivars of Ixora Flowers by Non-Destructive, Label-Free, and Rapid Spectroscopic Techniques

Simultaneous Quantification and Visualization of Photosynthetic Pigments in Lycopersicon esculentum Mill. under Different Levels of Nitrogen Application with Visible-Near Infrared Hyperspectral Imaging Technology

Leaf photosynthetic pigments play a crucial role in evaluating nutritional elements and physiological states. In facility agriculture, it is vital to rapidly and accurately obtain the pigment content and distribution of leaves to ensure precise water and fertilizer management. In our research, we utilized chlorophyll a (Chla), chlorophyll b (Chlb), total chlorophylls (Chls) and total carotenoids (Cars) as indicators to study the variations in the leaf positions of Lycopersicon esculentum Mill. Under 10 nitrogen concentration applications, a total of 2610 leaves (435 samples) were collected using visible-near infrared hyperspectral imaging (VNIR-HSI). In this study, a "coarse-fine" screening strategy was proposed using competitive adaptive reweighted sampling (CARS) and the iteratively retained informative variable (IRIV) algorithm to extract the characteristic wavelengths. Finally, simultaneous and quantitative models were established using partial least squares regression (PLSR). The CARS-IRIV-PLSR was used to create models to achieve a better prediction effect. The coefficient determination (R2), root mean square error (RMSE) and ratio performance deviation (RPD) were predicted to be 0.8240, 1.43 and 2.38 for Chla; 0.8391, 0.53 and 2.49 for Chlb; 0.7899, 2.24 and 2.18 for Chls; and 0.7577, 0.27 and 2.03 for Cars, respectively. The combination of these models with the pseudo-color image allowed for a visual inversion of the content and distribution of the pigment. These findings have important implications for guiding pigment distribution, nutrient diagnosis and fertilization decisions in plant growth management.

Early detection of stripe rust infection in wheat using light-induced fluorescence spectroscopy

In the current study, the application of fluorescence spectroscopy along with the advanced statistical technique and confocal microscopy was investigated for the early detection of stripe rust infection in wheat grown under field conditions. The indigenously developed Fluorosensor fitted with LED, emitting monochromatic light was used that covered comparatively larger leaf area for recording fluorescence data thus presenting more reliable current status of the leaf. The examined leaf samples covered the entire range of stripe rust disease infection from no visible symptoms to the complete disease prevalence. The molecular changes were also assessed in the leaves as the disease progresses. The emission spectra mainly produce two fluorescence emission classes, namely the blue-green fluorescence (400-600 nm range) and chlorophyll fluorescence (650-800 nm range). The chlorophyll fluorescence region showed lower chlorophyll bands both at 685 and 735 nm in the asymptomatic (early diseased) and symptomatic (diseased) leaf samples than the healthy ones as a result of partial deactivation of PSII reaction centers. The 735 nm chlorophyll fluorescence band was either slight or completely absent in the leaf samples with lower to higher disease incidence and thus differentiate between the healthy and the infected leaf samples. The Hydroxycinnamic acids (caffeic and sinapic acids) showed decreasing trend, whereas the ferulic acid increased with the rise in disease infection. Peak broadening/shifting has been observed in case of ferulic acid and carotenes/carotenoids, with the increase in the disease intensity. While using the LEDs (365 nm), the peak broadening and the decline in the chlorophyll fluorescence bands could be used for the early prediction of stripe rust disease in wheat crop. The PLSR statistical techniques discriminated well between the healthy and the diseased samples, thus showed promise in early disease detection. Confocal microscopy confirmed the early prevalence of stripe rust disease infection in a susceptible variety at a stage when the disease is not detectable visually. It is inferred that fluorescence emission spectroscopy along with the chemometrics aided in the effective and timely diagnosis of plant diseases and the detected signatures provide the basis for remote sensing.

Probing the impact of sustainable emerging sonication and DBD plasma technologies on the quality of wheat sprouts juice

Sonication and dielectric barrier discharge (DBD) plasma are sustainable emerging food processing technologies. The study investigates the impact of sonication, DBD-plasma, and thermal treatment (TT) on wheat sprout juice. The obtained results indicated a significant (p < 0.05) increase in chlorophyll, total phenolics, flavonoids, DPPH assay, and ORAC assay after DBD-plasma (40 V) and sonication (30 mins) treatment as compared to TT and untreated samples. Both emerging technologies significantly (p < 0.05) reduce the polyphenol oxidase and peroxidase activities, but the TT sample had the highest reduction. Moreover, the synergistic application of both technologies significantly reduced the E. coli/Coliform, aerobics, yeast and mold up to the 2 log reduction, but the TT sample had a complete reduction. DBD-plasma and sonication processing significantly decreased (p < 0.05) the particle size, reducing apparent viscosity (η) and consistency index (K); while increasing the flow behavior (n), leading to higher stability of wheat sprout juice. To assess the impact of emerging techniques on nutrient concentration, we used surface-enhance Raman spectroscopy (SERS) as an emerging method. Silver-coated gold nano-substrates were used to compare the nutritional concentration of wheat sprout juice treated with sonication, DBD-plasma, and TT-treated samples. Results showed sharp peaks for samples treated with DBD-plasma followed by sonication, untreated, and TT. The obtained results, improved quality of wheat sprout juice, and lower microbial and enzymatic loads were confirmed, showing the suitability of these sustainable processing techniques for food processing and further research.