Identification of insect-damaged wheat kernels using short-wave near-infrared hyperspectral and digital colour imaging

Healthy wheat kernels and wheat kernels damaged by the feeding of the insects: rice weevil (Sitophilus oryzae), lesser grain borer (Rhyzopertha dominica), rusty grain beetle (Cryptolestes ferrugineus), and red flour beetle (Tribolium castaneum) were scanned using a near-infrared (NIR) hyperspecrtal imaging system (700-1100 nm wavelength range) and a colour imaging system. Dimensionality of hyperspectral data was reduced and statistical and histogram features were extracted from NIR images of significant wavelengths and given as input to three statistical discriminant classifiers (linear, quadratic, and Mahalanobis) and a back propagation neural network (BPNN) classifier. A total of 230 features (colour, textural, and morphological) were extracted from the colour images and the most contributing features were selected and used as input to the statistical and BPNN classifiers. The quadratic discriminant analysis (QDA) classifier gave the highest accuracy and correctly identified 96.4% healthy and 91.0-100.0% insect-damaged wheat kernels using the top 10 features from 230 colour image features combined with hyperspectral image features.     

Brucellosis in migratory sheep flock from Maharashtra,India

Brucellosis is a zoonotic disease worldwide distributed and having the economic as well as public health importance. The prevalence of brucellosis among sheep flock having history of abortions was studied. A total of 229 samples comprising of 157 blood and 72 clinical samples (vaginal swabs) were collected from 157 animals. Clinical samples were processed for the isolation of Brucella melitensis. Serum samples (n = 157) were tested by Rose Bengal plate test (RBPT) and i-ELISA. A total of 68 (43.31%) and 104 (66.24%) samples were positive by RBPT and ELISA, respectively. Brucella isolates (n = 2) were recovered from clinical samples. Both isolates demonstrated amplification for bcsp 31 and IS711 genes. On AMOS PCR, both the isolates amplified at 731 bp, i.e., belongs to B. melitensis species. The incidence of B. melitensis in a migratory flock warns the thorough testing and culling of Brucella-infected sheep from the flock on a continuous basis; otherwise, such incidence will be routine and poor farmers will be at a loss.     

Development of somaclonal variants of wheat (Triticum aestivum L.) for yield traits and disease resistance suitable for heat stressed and zero-till conditions

In a substantial rice–wheat cropping system area of South Asia, wheat sowing often gets too delayed and exposed to terminal heat stress. Therefore, farmers prefer varieties that are able to perform well under a short growing period. Tissue culturally regenerated plants of wheat variety cv. HUW 234, the most widely cultivated variety of North Eastern Plain Zone (NEPZ) of India were screened using immature embryo as explant. Days to heading and maturity, yield and other yield components and resistance to leaf rust and spot blotch were evaluated. A few somaclones in R₃ and R₄ generations displayed significant earliness for days to heading and maturity, improved yield traits and resistance to leaf rust and spot blotch diseases. The superior performance of two of the variants was confirmed in the R₅ generation in 3 years of testing under two dates of conventional and zero-till sowing. Stability analysis also suggested superiority of the two somaclones across 12 environments. This appeared to confirm the possibility of obtaining useful somaclonal variants of wheat for very late sown as well as zero-till managed agriculture. The superior performing somaclones can be used as parents in the ongoing breeding programmes targeting late sown wheat in South Asia exposed to terminal heat stress.     

Detection of Sprouted and Midge‐Damaged Wheat Kernels Using Near‐Infrared Hyperspectral Imaging

Sprout damage which results in poor breadmaking quality due to enzymatic activity of α‐amylase is one of the important grading factors of wheat in Canada. Potential of near‐infrared (NIR) hyperspectral imaging was investigated to detect sprouting of wheat kernels. Artificially sprouted, midge‐damaged, and healthy wheat kernels were scanned using NIR hyperspectral imaging system in the range of 1000–1600 nm at 60 evenly distributed wavelengths. Multivariate image analysis (MVI) technique based on principal components analysis (PCA) was applied to reduce the dimensionality of the hyperspectral data. Three wavelengths 1101.7, 1132.2, and 1305.1 nm were identified as significant and used in analysis. Statistical discriminant classifiers (linear, quadratic, and Mahalanobis) were used to classify sprouted, midge‐damaged, and healthy wheat kernels. The discriminant classifiers gave maximum accuracy of 98.3 and 100% for classifying healthy and damaged kernels, respectively.     

Comparison of a Neural Network and a Non-parametric Classifier for Grain Kernel Identification

The performances of a four-layer backpropagation neural network and a non-parametric statistical classifier were compared for classification of barley, Canada Western Amber Durum wheat, Canada Western Red Spring wheat, oats, and rye. A total of 230 features (51 morphological, 123 colour, and 56 textural) from the high-resolution images of kernels of the five grain types were extracted and used as input features for classification. Different feature models, viz. morphological, colour, texture, and a combination of the three, were tested for their ability to classify these cereal grains. To make the classification process fast, the number of input features were reduced to 60 and 30. A set of features consisting of an equal number of morphological, colour, and textural features gave the best classification accuracies. The neural network classifier outperformed the non-parametric classifier in almost all the instances of classification.     

Identification of QTLs for stay green trait in wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis> L.) in the ‘Chirya 3’ × ‘Sonalika’ population

Stay green or delayed senescence is considered to play a crucial role in grain development in wheat when assimilates are limited. We identified three QTLs for stay green on the chromosomes 1AS, 3BS and 7DS using a recombinant inbred (RI) population developed by making crosses between the stay green parent ‘Chirya 3’ and non-stay green ‘Sonalika’. The RI lines were evaluated in natural field conditions for 2 years in replicated trial. The QTL on chromosome 1A was identified in both the years, while the QTLs on 3BS and 7DS were identified only in 1st and 2nd year, respectively. The QTLs explained up to 38.7% of phenotypic variation in a final simultaneous fit. The alleles for higher stay green values derived from the stay green parent ‘Chirya 3’. The QTLs were named as QSg.bhu-1A, QSg.bhu-3B and QSg.bhu-7D. The QTL QSg.bhu-3B and QSg.bhu-7D were placed in the 3BS9-0.57-0.78 and 7DS5-0.36-0.61 deletion bins, respectively.     

Antioxidant,Anti-Nephrolithe Activities and in Vitro Digestibility Studies of Three Different Cyanobacterial Pigment Extracts

Phycobiliprotein-containing water and carotenoid-containing methanolic extracts of three different cyanobacteria, Pseudanabaena sp., Spirulina sp. and Lyngbya sp., were studied for their DPPH scavenging, iso-bolographic studies, and anti-nephrolithe activities. The best EC₅₀ values for DPPH scavenging were in Lyngbya water (LW, 18.78 ± 1.57 mg·mg⁻¹ DPPH) and Lyngbya methanol (LM, 59.56 ± 37.38 mg·mg⁻¹ DPPH) extracts. Iso-bolographic analysis revealed most of the combinations of extracts were antagonistic to each other, although LM—Spirulina methanol (SM) 1:1 had the highest synergistic rate of 86.65%. In vitro digestion studies showed that DPPH scavenging activity was considerably decreased in all extracts except for Pseudanabaena methanol (PM) and LM after the simulated digestion. All of the extracts were effective in reducing the calcium oxalate crystal size by nearly 60%–65% compared to negative control, while PM and Spirulina water (SW) extracts could inhibit both nucleation and aggregation of calcium oxalate by nearly 60%–80%.     

Dry matter production, chlorophyll, protein contents and foliar nutrient concentration inPeltophorum ferrugineum andAlbizia lebbeck under nursery conditions

This study assesses the dry matter production, chlorophyll, soluble protein and macronutrients inPeltophorum ferrugineum andAlbizia lebbeck. The parameters were measured at 30-day intervals for 180 days in fertile soil without moisture stress and in the natural nursery condition.Albizia lebbeck exhibited more dry matter production, chlorophyll, soluble protein and macronutrients thanP. ferrugineum. A significant positive correlation was observed between dry matter production, leaf area, leaf dry weight and soluble protein for both the tested seedlings. The possible reasons for the observed differences in the biomass production, biochemical contents and nutrient concentration between the two seedlings are discussed.