Interpretation of genotype x environment interaction and stability analysis for grain yield of pigeon pea (Cajanus cajan L.)

Fourteen pigeon pea (Cajanus cajan L.) genotypes were evaluated for their yield performance at two locations during kharif season of 2009-10 and 2010-11. A significant genotypic difference for yield character was observed. Highly significant genotype–environment interaction indicated differential response of the genotypes to the environmental changes. The stability analysis showed significance of linear component of variation for grain yield. The genotypes TJT-501 (1728.667Kg/Ha) and GRG-2009-3 (1570.000 Kg/Ha) exhibited low meanperformance along with regression value nearer to unity (bi=1) and non significant deviation from regression (S2 di=0) indicating, the high stability and wider adaptability across the different environments. The genotype ICPH-2671 (3134.833 Kg/Ha) exhibited highest mean value and regression value (bi>1) and non significant deviation (S2 di < 0). But genotypes JKM-197 (3072.667 Kg/ha), GRG-2009 (29993.167 Kg/ha), TS-3R (2823.333 Kg / Ha) and ICP-8863 (2740.417 Kg/Ha) exhibited high mean performance but higher regression value (bi>1) and significant deviation (S2 di < 0) value indicating adapted for high performance environments showing these genotypes are sensitive to environments and give maximum yield when inputs are not limited

Poisson Regression Model for Fertility Count Data and Its Applications

Introduction: Count data represents the number of occurrences of an event within a fixed period. For example the number of caesarean-section delivery in the lifetime of women. Count data is encountered in almost all research areas including economics, medicine, management, industrial organizations, and many more. Count data is very common in various fields such as biomedical science, public health, and marketing.Obj Introduction: Count data represents the number of occurrences of an event within a fixed period. For example the number of caesarean-section delivery in the lifetime of women. Count data is encountered in almost all research areas including economics, medicine, management, industrial organizations, and many more. Count data is very common in various fields such as biomedical science, public health, and marketing.Objectives: The main aim of this study is to estimate the parameters of interest and compare the number of caesarean-section deliveries (NCSD) among women aged 15-49, in the state of Andhra Pradesh, India, using the Poisson regression model (PRM) and negative binomial regression model (NBRM). The fertility counts data set, the real-world data of the National Family Health Survey (NFHS-5), 2019-2021, from the Demography and Health Survey (DHS), 2019-2021 phase VII data is used for the analysis.Methods: Investigating the delivery patterns among pregnant women. This study develops an algorithm based on Integrated Nested Laplace Approximation (INLA) for fitting the model NCSD in PRM and NBRM. The analysis is carried out using the INLA package in R.Results: By use of the Deviance Information Criterion (DIC) and Watanabe-Akaike information criterion (WAIC), the result shows that the NBRM; DIC (7079.61) and WAIC (7079.61) present a comparatively better fit in modelling the NCSD than the PRM; DIC (7096.79) and WAIC (7097.89).Conclusions: The INLA provides an efficient algorithm to model in PRM and NBRM. For further research, comparing the PRM with other models that estimate over-dispersion in count data is recommended.ectives: The main aim of this study is to estimate the parameters of interest and compare the number of caesarean-section deliveries (NCSD) among women aged 15-49, in the state of Andhra Pradesh, India, using the Poisson regression model (PRM) and negative binomial regression model (NBRM). The fertility counts data set, the real-world data of the National Family Health Survey (NFHS-5), 2019-2021, from the Demography and Health Survey (DHS), 2019-2021 phase VII data is used for the analysis.Methods: Investigating the delivery patterns among pregnant women. This study develops an algorithm based on Integrated Nested Laplace Approximation (INLA) for fitting the model NCSD in PRM and NBRM. The analysis is carried out using the INLA package in R.Results: By use of the Deviance Information Criterion (DIC) and Watanabe-Akaike information criterion (WAIC), the result shows that the NBRM; DIC (7079.61) and WAIC (7079.61) present a comparatively better fit in modelling the NCSD than the PRM; DIC (7096.79) and WAIC (7097.89).Conclusions: The INLA provides an efficient algorithm to model in PRM and NBRM. For further research, comparing the PRM with other models that estimate over-dispersion in count data is recommended. DOI: https://doi.org/10.52783/jchr.v13.i4.111

In vitro multiplication of Coffea arabica F1 hybrid (S.2800) and its performance in the field

See the pdf file here http://indsocplantationcrops.in/journal.php

MIRO-1 Determines Mitochondrial Shape Transition upon GPCR Activation and Ca^(2+) Stress

Mitochondria shape cytosolic calcium ([Ca^(2+)]_c) transients and utilize the mitochondrial Ca_2^+ ([Ca^(2+)]_m) in exchange for bioenergetics output. Conversely, dysregulated [Ca^(2+)]_c causes [Ca^(2+)]_m overload and induces permeability transition pore and cell death. Ablation of MCU-mediated Ca^(2+) uptake exhibited elevated [Ca^(2+)]_c and failed to prevent stress-induced cell death. The mechanisms for these effects remain elusive. Here, we report that mitochondria undergo a cytosolic Ca^(2+)-induced shape change that is distinct from mitochondrial fission and swelling. [Ca^(2+)]_c elevation, but not MCU-mediated Ca^(2+) uptake, appears to be essential for the process we term mitochondrial shape transition (MiST). MiST is mediated by the mitochondrial protein Miro1 through its EF-hand domain 1 in multiple cell types. Moreover, Ca^(2+)-dependent disruption of Miro1/KIF5B/tubulin complex is determined by Miro1 EF1 domain. Functionally, Miro1-dependent MiST is essential for autophagy/mitophagy that is attenuated in Miro1 EF1 mutants. Thus, Miro1 is a cytosolic Ca^(2+) sensor that decodes metazoan Ca^(2+) signals as MiST

Selective role for superoxide in InsP3 receptor–mediated mitochondrial dysfunction and endothelial apoptosis

Reactive oxygen species (ROS) play a divergent role in both cell survival and cell death during ischemia/reperfusion (I/R) injury and associated inflammation. In this study, ROS generation by activated macrophages evoked an intracellular Ca2+ ([Ca2+]i) transient in endothelial cells that was ablated by a combination of superoxide dismutase and an anion channel blocker. [Ca2+]i store depletion, but not extracellular Ca2+ chelation, prevented [Ca2+]i elevation in response to O2.− that was inositol 1,4,5-trisphosphate (InsP3) dependent, and cells lacking the three InsP3 receptor (InsP3R) isoforms failed to display the [Ca2+]i transient. Importantly, the O2.−-triggered Ca2+ mobilization preceded a loss in mitochondrial membrane potential that was independent of other oxidants and mitochondrially derived ROS. Activation of apoptosis occurred selectively in response to O2.− and could be prevented by [Ca2+]i buffering. This study provides evidence that O2.− facilitates an InsP3R-linked apoptotic cascade and may serve a critical function in I/R injury and inflammation

Molecular dissection of genetic diversity in pigeonpea [Cajanus cajan (L) Millsp.] minicore collection

The present investigation was carried out using 191genotypes as mini core collections of pigeonpea along with 5 check varieties to know the genetic diversity at molecular level. Significant variation was observed by the way of analysis of variance for nine characters viz., days to 50% flowering, days to maturity, plant height, number of branches per plant, pod bearing length, number of pods per plant, number of seeds per pod, seed yield per plant and hundred seed weight. Molecular diversity using 18 polymorphic simple sequence repeat (SSR) markers divided genotypes into 15 clusters, of which ICP11059 and AK-101 were solitary, indicating their distinctiveness among all genotypes. Similarly, BSMR-533, JKM-7, RVK-285, ICP-1126, ICP-348, ICP-6859 and ICP-7869 were found distinct among the genotypes. Geographical origin based diversity separated Indian and non Indian genotypes. The Un weighted Pair Group Method with Arithmetic mean (UPGMA) based dendrogram indicated distinctiveness of ICP-13633 and Bennur local, as they formed solitary cluster. The SSR marker CcM 602, as it could differentiate 4 genotypes at different base pair size can be used for identification and finger printing of genotypes