Correlation of carotenoid accumulation and expression pattern of carotenoid biosynthetic pathway genes in Indian wheat varieties

Enhancing grain drying methods with hyperspectral imaging technology: A visualanalysis

This study proposes a recognition model for different drying methods of grain using hyperspectral imaging technology (HSI) and multivariate analysis. Fresh harvested grain samples were dried using three different methods: rotating ventilation drying, mechanical drying, and natural drying. Hyperspectral images of the samples were collected within the 388-1065 nm band range. The spectral features of the samples were extracted using principal component analysis (PCA), while the texture features were extracted using second-order probability statistical filtering. Partial least squares regression (PLSR) drying models with different characteristics were established. At the same time, a BPNN (Back-propagation neural network, BPNN) based on spectral texture fusion features was established to compare the recognition effects of different models. Texture analysis indicated that the mean-image had the clearest contour, and the texture characteristics of mechanical drying were smaller than those of rotating ventilation drying and natural drying. The BPNN model established using spectral-texture feature variables showed the best performance in distinguishing grain in different drying modes, with a prediction model obtained based on the correlation coefficients of special variables. The spectral and texture feature values were fused for pseudo-color visualization expression, and the three drying methods of grain showed different colors. This study provides a reference for non-destructive and rapid detection of grain with different drying methods.

Wheat derived glucuronokinase as a potential target for regulating ascorbic acid and phytic acid content with increased root length under drought and ABA stresses in Arabidopsis thaliana

Glucuronokinase (GlcAK) converts glucuronic acid into glucuronic acid-1-phosphate, which is then converted into UDP-glucuronic acid (UDP-GlcA) via myo-inositol oxygenase (MIOX) pathway. UDP-GlcA acts as a precursor in the synthesis of nucleotide-sugar moieties forming cell wall biomass. GlcAK being present at the bifurcation point between UDP-GlcA and ascorbic acid (AsA) biosyntheses, makes it necessary to study its role in plants. In this study, the three homoeologs of GlcAK gene from hexaploid wheat were overexpressed in Arabidopsis thaliana. The GlcAK overexpressing transgenic lines showed decreased contents of AsA and phytic acid (PA) as compared to control plants. Root length and seed germination analyses under abiotic stress (drought and abscisic acid) conditions revealed enhanced root length in transgenic lines as compared to control plants. These results indicate that the MIOX pathway might be contributing towards AsA biosynthesis as evident by the decreased AsA content in the GlcAK overexpressing transgenic Arabidopsis thaliana plants. Findings of the present study will enhance the understanding of the involvement of GlcAK gene in MIOX pathway and subsequent physiological effects in plants.

Small molecule carbon source promoting dairy wastewater treatment of Rhodospirillum rubrum by co-metabolism and the establishment of multivariate nonlinear equation

Rhodospirillum rubrum water treatment technology could recycle bio-resource. However, the inability to degrade macromolecular organics limited its wide application. This paper discussed the feasibility of small molecular carbon source promoting R. rubrum directly treating dairy machining wastewater (DMW) and accumulations for single cell protein and pigment, and establishment of a mathematical model. Six small molecules promoted the degradation of macromolecules (proteins) in DMW. They promoted protease secretion and non-growth matrix (protein) decomposition in DMW through co-metabolism. Among the molecules, 550 mg/L potassium sodium tartrate was the best, protease activity and protein removal rate were increased by 100% compared with control. Then chemical oxygen demand (COD) and protein removal rates reached 80%, the single cell protein, carotenoid and bacterial chlorophyll yields were increased 2 times. Meanwhile, carbon nitrogen ratio (C/N) and food microbial ratio (F/M) were identified as the most important factors by principal component analysis. A multivariate nonlinear equation model between COD removal rate and C/N, F/M, time was established.