OBJECTIVE: The study sought to discern plant growth promoting (PGP) compounds that can amplify drought resilience and boost productivity in cauliflower.
METHODS: Investigations were centered on endophytes, microorganisms existing within plant tissues. The dual role of beneficial and detrimental Agrobacterium was scrutinized, particularly emphasizing the ethylene precursor compound, 1-amino-cyclopropane-1-carboxylic acid (ACCA).
RESULTS: ACCA possessed salient PGP traits, particularly demonstrating a pronounced enhancement of drought resistance in cauliflower plants. Specifically, during the pivotal marketable curd maturity phase, which necessitates defense against various threats, ACCA showcased a binding energy of -8.74 kcal/mol.
CONCLUSION: ACCA holds a significant promise in agricultural productivity, with its potential to boost drought resistance and cauliflower yield. This could be particularly impactful for regions grappling with high temperatures and possible nitrogen shortages. Future research should explore ACCA's performance under diverse environmental settings and its applicability in other crops.
METHODS: In the current study, multivariant traits were used to define 50 genotypes in the first year and 10 genotypes in the second year. The phenotypic correlations among all traits in the entire germplasm were assessed, and the data acquired for all quantitative characters were subjected to analysis of variance for augmented block design. Furthermore, WINDOWS STAT statistical software was used to carry out a principal component analysis (PCA). The presence of substantial variations in most symptoms was shown by analysis of variance.
RESULTS: Genotypic coefficient of variation (GCV) projections for grain yields were the highest, followed by panicle lengths and biological yields. Plant height and leaf length had the highest PCV estimates, followed by leaf width. Low GCV and phenotypic coefficient of variation (PCV) were measured as leaf length and 50% flowering in days. According to the PCV study, direct selection based on characters, panicle weight, test weight, and straw weight had a high and positive effect on grain yield per plant in both the rainy and summer seasons, indicating the true relationship between these characters and grain yield per plant, which aids indirect selection for these traits and thus improves grain yield per plant. Variability in foxtail millet germplasm enables plant breeders to effectively select appropriate donor lines for foxtail millet genetic improvement.
DISCUSSION: Based on the average performance of genotypes considered superior in terms of grain yield components under Prayagraj agroclimatic conditions, the best five genotypes were: Kangni-7 (GS62), Kangni-1 (G5-14), Kangni-6 (GS-55), Kangni-5 (GS-389), and Kangni-4 (GS-368).
METHODS: G. lucidum samples from various sources and in varying stages were identified by using δ 13C, δD, δ 18O, δ 15N, C, and N contents combined with chemometric tools. Chemometric approaches, including PCA, OPLS-DA, PLS, and FLDA models, were applied to the obtained data. The established models were used to trace the origin of G. lucidum from various sources or track various stages of G. lucidum.
RESULTS: In the stage model, the δ 13C, δD, δ 18O, δ 15N, C, and N contents were considered meaningful variables to identify various stages of G. lucidum (bud development, growth, and maturing) using PCA and OPLS-DA and the findings were validated by the PLS model rather than by only four variables (δ 13C, δD, δ 18O, and δ 15N). In the origin model, only four variables, namely δ 13C, δD, δ 18O, and δ 15N, were used. PCA divided G. lucidum samples into four clusters: A (Zhejiang), B (Anhui), C (Jilin), and D (Fujian). The OPLS-DA model could be used to classify the origin of G. lucidum. The model was validated by other test samples (Pseudostellaria heterophylla), and the external test (G. lucidum) by PLS and FLDA models demonstrated external verification accuracy of up to 100%.
CONCLUSION: C, H, O, and N stable isotopes and C and N contents combined with chemometric techniques demonstrated considerable potential in the geographic authentication of G. lucidum, providing a promising method to identify stages of G. lucidum.
METHODS: Genetic diversity was assessed using 20 SSR markers, and the parental lines were grouped into five clusters based on the Unweighted Pair Group Method of Arithmetic Means (UPGMA). Heterosis was examined through yield and yield-related traits among parents and hybrids.
RESULTS: Polymorphisms were detected in eight out of the twenty SSR markers across the parental lines. Notably, a high genetic distance was observed between some parents. The analysis of yield and yield-related traits demonstrated significant heterosis over mid, superior, and standard parents, particularly in fruit yield per plant. Two crosses (RKML-26 X PPC and RKML1 X PPC) displayed substantial heterosis over mid and better parents, respectively. However, the positive correlation between genetic distance and heterosis was only up to a certain threshold; moderate genetic distance often resulted in higher heterosis compared to very high genetic distance.
DISCUSSION: These findings emphasize the critical role of parental selection in hybrid breeding programs. The results contribute to the understanding of the relationship between genetic distance and heterosis, and it is suggested that future research should delve into the genetic mechanisms that drive heterosis and the effect of genetic distance variance on heterosis. The insights drawn from this study can be harnessed to enhance crop yield and economic value in breeding programs.