G. B. Pant University of Agriculture and Technology

About: G. B. Pant University of Agriculture and Technology is a education organization based out in Haldwani, India. It is known for research contribution in the topics: Population & Agriculture. The organization has 3154 authors who have published 3244 publications receiving 43741 citations. The organization is also known as: Govind Ballabh Pant Krishi Evam Praudyogik Vishwavidyalaya & Pantnagar University.

Effect of heat shock protein 70 polymorphism on thermotolerance in Tharparkar cattle.

Abstract: Aim: Out of various members of heat shock protein (HSP) superfamily which act a molecular chaperon by binding to the denaturing protein thus stabilizing them and preserving their activity, HSP70 are of major importance in thermotolerance development. Thus, present investigation aimed at a screening of HSP70 gene for polymorphisms and possible differences in thermotolerance in Tharparkar breed of cattle. Materials and Methods: A 295 bp fragment of HSP70 gene was subjected to polymerase chain reaction-single- strand conformation polymorphism (SSCP) followed by sequencing of different SSCP patterns in 64 Tharparkar cattle. A comparative thermotolerance of identified genotypes was analyzed using heat tolerance coefficients (HTCs) of animals for different seasons. Results: Three SSCP patterns and consequently two alleles namely A and B were documented in one fragment of HSP70 gene. On sequencing, one single-nucleotide polymorphism with G > T substitution was found at a position that led to a change of amino acid aspartate to tyrosine in allele A. It was found that in maintaining near normal average rectal temperature, genotype AA was superior (p≤0.01). Genotype AA, thus, was found to be most thermotolerant genotype with the highest HTC (p≤0.01). Conclusion: The polymorphism at HSP70 is expected to be a potent determinant for heat tolerance in cattle, which may aid in selection for thermotolerance in cattle.

Application of artificial neural network for predicting crack growth direction in multiple cracks geometry

Abstract: Summary of predicted and experimental results. The crack growth under multiple cracks is highly influenced by neighbouring cracks.No mathematical relation is available to predict the crack initiation direction.ANN has been used to predict crack growth direction in multiple crack geometry.The effect of degree of input variables and hybrid combination of activation functions is studied.Nonlinear and linear activation functions are used through the one and two-hidden layer ANN.The experimental dataset as first or second degree were used.Higher order input variables are found to be more suitable. The objective of this study is to design an efficient artificial neural network (ANN) architecture in order to predict the crack growth direction in multiple crack geometry. Nonlinear logistic (sigmoid and tangent hyperbolic) and linear activation functions have been used through the one- and two-hidden layer ANN. 85 tests were conducted on aluminium alloys under different crack positions, defined by crack tip distance, crack offset distance, crack size, and crack inclination with loading axis. The experimental data set as first degree or second degree were used to train 22 proposed ANN models to predict the output for new data sets (not included in the training sets). The model results were then compared with the experimental data. It was observed that ANN model with combinations of activation functions and two hidden layers predict the crack initiation direction with good accuracy when higher order input variables are presented to the network.

Genome wide association mapping of agro-morphological traits among a diverse collection of finger millet (Eleusine coracana L.) genotypes using SNP markers.

Abstract: Finger millet (Eleusine coracana L.) is an important dry-land cereal in Asia and Africa because of its ability to provide assured harvest under extreme dry conditions and excellent nutritional properties. However, the genetic improvement of the crop is lacking in the absence of suitable genomic resources for reliable genotype-phenotype associations. Keeping this in view, a diverse global finger millet germplasm collection of 113 accessions was evaluated for 14 agro-morphological characters in two environments viz. ICAR-Vivekananda Institute of Hill Agriculture, Almora (E1) and Crop Research Centre (CRC), GBPUA&T, Pantnagar (E2), India. Principal component analysis and cluster analysis of phenotypic data separated the Indian and exotic accessions into two separate groups. Previously generated SNPs through genotyping by sequencing (GBS) were used for association mapping to identify reliable marker(s) linked to grain yield and its component traits. The marker trait associations were determined using single locus single trait (SLST), multi-locus mixed model (MLMM) and multi-trait mixed model (MTMM) approaches. SLST led to the identification of 20 marker-trait associations (MTAs) (p value<0.01 and <0.001) for 5 traits. While advanced models, MLMM and MTMM resulted in additional 36 and 53 MTAs, respectively. Nine MTAs were common out of total 109 associations in all the three mapping approaches (SLST, MLMM and MTMM). Among these nine SNPs, five SNP sequences showed homology to candidate genes of Oryza sativa (Rice) and Setaria italica (Foxtail millet), which play an important role in flowering, maturity and grain yield. In addition, 67 and 14 epistatic interactions were identified for 10 and 7 traits at E1 and E2 locations, respectively. Hence, the 109 novel SNPs associated with important agro-morphological traits, reported for the first time in this study could be precisely utilized in finger millet genetic improvement after validation.

Immunotoxic responses of cypermethrin, a synthetic pyrethroid insecticide in rats.

Abstract: The study was undertaken to evaluate immunotoxic effects of cypermethrin administered orally (in ground nut oil) to male albino rats at dose levels (mg/kg) of 0 (control), 5, 10, 20 and 40 once daily for 90 days. Cypermethrin administration produced a significant leucopenia at 40 mg/kg on day 90. A dose dependent decrease (P greater than 0.05) in delayed type hypersensitivity reaction was noticed on day 61 post treatment. Humoral response as evidenced by serum haemagglutinin and haemolysin titres did not show any definite pattern on day 90. However, a significant decrease in spleen weights and significant increase in adrenal weights was recorded in rats receiving the highest test level. Total body weights and liver weights did not show any significant change with any of the dose level studied. Results of the study reveal that low doses (5 and 10 mg/kg) did not have any adverse effect on the immuno-competence of rats.

Phytic acid content may affect starch digestibility and glycemic index value of rice (Oryza sativa L.).

Abstract: Background Phytic acid (PA) is an anti-nutrient present in cereals and pulses. It is known to reduce mineral bioavailability and inhibit starch-digesting α-amylase (which requires calcium for activity) in the human gut. In principle, the greater the amount of PA, the lower is the rate of starch hydrolysis. It is reflected in the lower glycemic index (GI) value of food. People leading sedentary lifestyles and consuming rice as a staple food are likely to develop type 2 diabetes. Hence, this study was planned to understand how PA content of different rice varieties affects the GI. Results Rice Khira and Mugai which had very low PA (0.30 and 0.36 g kg-1 , respectively) had higher GI values and α-amylase activity, while Nua Dhusara and the pigmented rice Manipuri black rice (MBR) which had high PA (2.13 and 2.98 g kg-1 , respectively) showed low α-amylase activity and GI values. This relationship was statistically significant, though a weak relationship was found for the pigmented rice. Expression levels of MIPSI, IPKI and GBSSI markedly increased in the middle stage of grain development in all of the six genotypes having contrasting PA and GI. Maximum expression of MIPSI and IPKI was observed in Nua Dhusara and MBR (which had high PA) while that of GBSSI was observed in Khira and Mugai (with higher GI) at middle stage showing a negative correlation between PA and GI. Conclusions The data indicate that high PA content in rice might have an adverse effect on starch digestibility resulting in slower starch digestion in the human gut and consequently low glycemic response. © 2019 Society of Chemical Industry.