Genetic basis and principal component analysis in cotton (Gossypium hirsutum L.) grown under water deficit condition

Interactive effects of planting patterns combined with integrated nutrient management on maize production, water-nitrogen productivity and soil organic carbon fractions

BACKGROUND

Ridge and furrow rain-harvesting planting system and integrated nutrient management are crucial strategies for enhancing soil moisture and fertility in drylands. However, the synergistic impact of these approaches on soil hydrothermal environment, maize productivity, water-nitrogen productivity and soil carbon fractions has not been fully understood. A two-year field experiment were conducted in 2020 and 2021 was undertaken in Loess Plateau of China. Six treatments: (i-iii) Conventional flat planting with no nutrient management (CP), with nitrogen fertilizer (CPN), with nitrogen fertilizer and maize straw (CPSN); (iv-vi) ridge and furrow rain-harvesting planting with no nutrient management (RF), with nitrogen fertilizer (RFN), with nitrogen fertilizer and maize straw (RFSN).

RESULTS

The results showed that the RF, CPN, RFN, CPSN and RFSN significantly improved soil temperature, which showed gradually increased after the seedling stage and slowly decreased at silking to maturity stage in two maize growing period. The dynamics of soil water storage (SWS) varied significantly throughout the six growing periods. The increasing of grain yield and above-ground biomass were highly influenced by ridge and furrow rain-harvesting planting system and interaction with nitrogen fertilizer and crop straw management. The grain and straw N content, plant N uptake, water productivity also similar with the rank of grain yield and above-ground followed by RFSN>CPSN>FPN>CPN>FP>CP. Furthermore, the RFSN treatment significantly increased the N uptake efficiency (NUPE), agronomy efficiency of N (AEN), and partial factor productivity of N fertilizer (PFPN) compared to RFN, with a mean increase of 29.2%, 44.5% and 7.8% in both growing years. Meanwhile, the RFSN treatment increased DOC by 51.1% (53.2%), EOC by 25.4 % (26.1%), MBC by 96.3% (80.8%), MBN by 52.6% (86.7%) in 2020 (2021), respectively.

CONCLUSIONS

As a result, gray relation analysis and entropy TOPSIS model evaluated that application of maize straw 1.5 t ha-1 and chemical nitrogen fertilizer of 180 kg ha-1 in ridge and furrow rainwater harvesting system (RFSN) serve as a effective method of soil management to enhance water and nitrogen utilization, potentially boosting yields and promoting resource efficiency in the arid regions of the Loess Plateau.

Hybridization potential and genetic influence of parental varieties on fruit size and set rate in Gleditsia sinensis

Gleditsia sinensis is a dioecious perennial tree, with its fruit size directly impacting its economic value. Investigating the feasibility of hybridization between different Gleditsia varieties and the influence of parentage on fruit size is crucial. In this study, we compared the pollen viability of Gleditsia sinensis, Gleditsia japonica var. delavayi (G. delavayi), Gleditsia japonica and Gleditsia fera under long-term storage, and explored the feasibility of intraspecific and interspecific hybridization of Gleditsia sinensis. We also evaluated the genetic characteristics of parentage on the fruit size and fruit set rate of Gleditsia sinensis. The results indicated that dry storage at -80 °C is suitable for the long-term preservation of pollen for most Gleditsia varieties. Interspecific hybridization of G. sinensis is feasible, and hybridization with G. fera exhibits a high general combining ability for fruit size. Therefore, G. fera can serve as an excellent male parent for interspecific hybridization with G. sinensis. The phenotypic traits of the current generation's pods are primarily influenced by the additive effects of the maternal parent and the non-additive effects of both parents. Pod length and width exhibit high heritability, while pod thickness has lower heritability and is more significantly influenced by non-additive effects.

Exploratory analysis of agro-morphological characteristics in Nigella sativa L. plant genotypes to determine mutagen colchicine ameliorative/ non-ameliorative impacts

This experimental study aimed to elucidate the optimal colchicine concentration for inducing polyploidy and to examine the morphological effects on Nigella sativa L. (family Ranunculaceae) plants recognized as 'Kalonji' in India. Here, seeds were exposed with different concentration of colchicine ranging from 0.025 to 0.4% with varying time duration (24-48 h). The agro-morphological attributes and chromosome counts of the putative polyploids were compared with control diploid plants, revealing significant differences. The ploidy level determined by chromosome counts revealed that 0.05-0.1% concentration of colchicine induced tetraploids within both plant genotypes for 24 h and 48 h. However, results based on agro-morphological trait correlation analysis revealed more significant association among yield traits at 0.1% concentration and the principal component analysis revealed that the maximum possible ameliorative effect of the colchicine dose was the lowest concentration (0.025% for a 48-hour exposure time) for the AN1 genotype; likewise, a 0.05% concentration established a more positive association in terms of growth and yield attributes for the AN20 genotype. This study demonstrated that low dosages (0.025% and 0.1%) strongly impact plant growth and yield, whereas higher dosages obliterate these positive effects and add destructive characteristics within plants which ultimately reduces yield.

Heat stress tolerance in wheat seedling: Clustering genotypes and identifying key traits using multivariate analysis

Elevated atmospheric heat is considered as one of the bottlenecks for global wheat production. Screening potential wheat genotypes against heat stress and selecting some suitable indicators to assist in understanding thermotolerance could be crucial for sustaining wheat cultivation. Accordingly, 80 diverse bread wheat genotypes were evaluated in controlled lab condition by imposing a week-long heat stress (35/25 °C D/N) at the seedling stage. The response of heat stress was evaluated using multivariate analysis techniques on 20 morpho-physiological traits. Results showed significant variations in the studied traits due to the imposition of heat stress. Eleven seedling traits that contributed significantly to the genotypic variability were identified using principal component analysis (PCA). A substantial correlation between most of the selected seedling attributes was observed. Hierarchical cluster analysis identified three distinct clusters among the tested wheat genotypes. Cluster 1, consisting of 33 genotypes, exhibited the highest tolerance to heat stress, followed by Cluster 2 (18 genotypes) with moderate tolerance and Cluster 3 (29 genotypes) showing susceptibility. Linear discriminant analysis (LDA) approved that nearly 93 % of the wheat genotypes were appropriately ascribed to each cluster. The squared distance analysis confirmed the distinct nature of the clusters. Using multi-trait genotype-ideotype distance index (MGIDI), all 12 identified tolerant genotypes (BG-30, BD-468, BG-24, BD-9908, BG-32, BD-476, BD-594, BD-553, BD-488, BG-33, BD-495, and AS-10627) originated from Cluster 1. Selection gain in MGIDI analysis, broad-sense heritability, and multiple linear regression analysis together identified shoot and root dry and fresh weights, chlorophyll contents (a and total), shoot tissue water content, root-shoot dry weight ratio, and efficiency of photosystem II (PS II) as the most vital discriminatory factors explaining heat stress tolerance of 80 wheat genotypes. The identified genotypes with superior thermotolerance would offer resourceful genetic tools for breeders to improve wheat yield in warmer regions. The traits found to have greater contribution in explaining heat stress tolerance will be equally important in prioritizing future research endeavors.

Deciphering genotype-by-environment interaction in new soybean lines based on multiple traits using different adaptability and stability methods

The multi-environmental trials aid breeders in selecting the best genotypes for specific or general adaptability to different environments before commercial release. This study aimed to assess the stability of 13 new soybean pure lines, along with two controls, in terms of seed yield and important agronomic traits. The assessment was based on a completely randomized block design with three replications across four areas during 2020-2022. Various adaptability methods, including parametric, AMMI, GGE biplot, PCA, and SIIG were employed. The mixed analysis showed that the effects of environment, genotype, and genotype-environment (GE) interaction were significant for most studied traits. The AMMI showed the highest portion of environment (65.89%) in soybean seed yield. Based on all stability parameters, lines 2 and 5 were selected for their average seed yields of 3349 and 3142 kg ha-1, respectively. Additionally, lines 6 and 5 showed the most stability, yielding higher than the average, which were 2992 and 3142 kg ha-1, respectively, according to GGE biplot results. Furthermore, lines 2, 5, and 8 were identified as the ideal genotypes concerning seed yield and other agronomic traits, with high SIIG parameters and yields exceeding the average. Finally, the soybean line 5 was deemed the most suitable due to its higher yield, stability, and early maturity (128-day growth period). Therefore, line 5 is considered appropriate for its high stability and earliness in various regions of Iran.

Genetic improvement of Egyptian cotton (Gossypium barbadense L.) for high yield and fiber quality properties under semi arid conditions

Between 2016 and 2018, the Agriculture Research Center's Sakha Agriculture Research Station conducted two rounds of pedigree selection on a segregating population of cotton (Gossypium barbadense L.) using the F2, F3, and F4 generations resulting from crossing Giza 94 and Suvin. In 2016, the top 5% of plants from the F2 population were selected based on specific criteria. The superior families from the F3 generation were then selected to produce the F4 families in 2017, which were grown in the 2018 summer season in single plant progeny rows and bulk experiments with a randomized complete block design of three replications. Over time, most traits showed increased mean values in the population, with the F2 generation having higher Genotypic Coefficient of Variance (GCV) and Phenotypic Coefficient of Variance (PCV) values compared to the succeeding generations for the studied traits. The magnitude of GCV and PCV in the F3 and F4 generations was similar, indicating that genotype had played a greater role than the environment. Moreover, the mean values of heritability in the broad sense increased from generation to generation. Selection criteria I2, I4, and I5 were effective in improving most of the yield and its component traits, while selection criterion I1 was efficient in improving earliness traits. Most of the yield and its component traits showed a positive and significant correlation with each other, highlighting their importance in cotton yield. This suggests that selecting to improveone or more of these traits would improve the others. Families number 9, 13, 19, 20, and 21 were the best genotypes for relevant yield characters, surpassing the better parent, check variety, and giving the best values for most characters. Therefore, the breeder could continue to use these families in further generations as breeding genotypes to develop varieties with high yields and its components.

Prioritization of Physio-Biochemical Selection Indices and Yield-Attributing Traits toward the Acquisition of Drought Tolerance in Chickpea (Cicer arietinum L.)

Chickpea is widely grown in rainfed areas of developing countries because of its nutritional abundance and adaptability. To overcome the environmental effect of drought on yield, a characteristic-linked selection strategy is proved as well-thought-out and advantageous for the development of drought-tolerant cultivars. To precisely understand the contribution of various physio-biochemical and yield-attributing traits toward drought tolerance in chickpea (Cicer arietinum L.), forty chickpea genotypes were evaluated in the years 2020-2021 and 2021-2022 under normal irrigated as well as drought-stressed conditions. Among the studied genotypes, genotype ICC4958 retained the highest chl content (0.55 mg g-1 FW), minimal electrolyte leakage, and superoxide dismutase (1.48 U/mg FW) and peroxidase (2.21 µmol/min/g FW) activities while cultivar JG11 maintained the maximum relative water content and proline accumulation. The principal-component-based biplots prioritized the physio-biochemical and yield-accrediting characteristics based on their association significance and contribution to terminal drought tolerance. Under drought stress, grain yield per plant was depicted to have a strongly positive association with canopy temperature depression, catalase, superoxide dismutase, and peroxidase activities as well as total soluble sugar, proline, and chlorophyll content, along with the numbers of pods and biological yield per plant. These identified physio-biochemical and yield-attributing traits can be further deployed to select drought-tolerant chickpea genotypes for the breeding of climate-smart chickpea genotypes.

Estimating the combining ability and genetic parameters for growth habit, yield, and fiber quality traits in some Egyptian cotton crosses

It is crucial to understand how targeted traits in a hybrid breeding program are influenced by gene activity and combining ability. During the three growing seasons of 2015, 2016, and 2017, a field study was conducted with twelve cotton genotypes, comprised of four testers and eight lines. Thirty-two F1 crosses were produced in the 2015 breeding season using the line x tester mating design. The twelve genotypes and their thirty-two F1 crosses were then evaluated in 2016 and 2017. The results demonstrated highly significant differences among cotton genotypes for all the studied traits, showing a wide range of genetic diversity in the parent genotypes. Additionally, the line-x-tester interaction was highly significant for all traits, suggesting the impact of both additive and non-additive variations in gene expression. Furthermore, the thirty-two cotton crosses showed high seed cotton output, lint cotton yield, and fiber quality, such as fiber length values exceeding 31 mm and a fiber strength above 10 g/tex. Accordingly, selecting lines and testers with high GCA effects and crosses with high SCA effects would be an effective approach to improve the desired traits in cotton and develop new varieties with excellent yield and fiber quality.