Response of Maize Hybrids in Drought-Stress Using Drought Tolerance Indices

Identifying critical growth stage and resilient genotypes in cowpea under drought stress contributes to enhancing crop tolerance for improvement and adaptation in Cameroon

Drought stress following climate change is likely a scenario that will have to face crop growers in tropical regions. In mitigating this constraint, the best option should be the selection and use of resilient varieties that can withstand drought threats. Therefore, a pot experiment was conducted under greenhouse conditions at the Research and Teaching Farm of the Faculty of Agronomy and Agricultural Sciences of the University of Dschang. The objectives are to identify sensitive growth stage, to identify drought-tolerant genotypes with the help of yield-based selection indices and to identify suitable selection indices that are associated with yield under non-stress and stress circumstances. Eighty-eight cowpea genotypes from the sahelian and western regions of Cameroon were subjected to drought stress at vegetative (VDS) and flowering (FDS) stages by withholding water for 28 days, using a split plot design with two factors and three replications. Seed yields under stress (Ys) and non-stress (Yp) conditions were recorded. Fifteen drought indices were calculated for the two drought stress levels against the yield from non-stress plants. Drought Intensity Index (DII) under VDS and FDS were 0.71 and 0.84 respectively, indicating severe drought stress for both stages. However, flowering stage was significantly more sensitive to drought stress compared to vegetative stage. Based on PCA and correlation analysis, Stress Tolerance Index (STI), Relative Efficiency Index (REI), Geometric Mean Productivity (GMP), Mean Productivity (MP), Yield Index (YI) and Harmonic Mean (HM) correlated strongly with yield under stress and non-stress conditions and are therefore suitable to discriminate high-yielding and tolerant genotypes under both stress and non-stress conditions. Either under VDS and FDS, CP-016 exhibited an outstanding performance under drought stress and was revealed as the most drought tolerant genotype as shown by ranking, PCA and cluster analysis. Taking into account all indices, the top five genotypes namely CP-016, CP-021, MTA-22, CP-056 and CP-060 were identified as the most drought-tolerant genotypes under VDS. For stress activated at flowering stage (FDS), CP-016, CP-056, CP-021, CP-028 and MTA-22 were the top five most drought-tolerant genotypes. Several genotypes with insignificant Ys and irrelevant rank among which CP-037, NDT-001, CP-036, CP-034, NDT-002, CP-031, NDT-011 were identified as highly drought sensitive with low yield stability. This study identified the most sensitive stage and drought tolerant genotypes that are proposed for genetic improvement of cowpea.

Impact of research on maize production challenges in Hungary

Maize (Zea mays L), as a major cereal crop produced in Hungary in addition to wheat, attracts enormous research from both educational and non-educational institutions. Research is aimed at addressing the key abiotic, biotic and social economic constraints. The stakeholders and institutions involved in research are spread all over Hungary. Currently, no review has been done to comprehensively reveal the trend of maize research in Hungary, as well as key players such as institutions, universities, industry and researchers. Hence, this bibliographic review was conducted to: i) identify the major research institutions and their contribution towards maize research in Hungary; ii) evaluate the major maize research areas in Hungary between 1975 and 2022. Literature search was conducted in Web of Science (WoS) database using keywords; 'maize' OR 'maize' + 'Research' + 'Hungary'. Bibliometric analyses were performed using the VOSviewer software. Changes in the publication trend of documents was tested using Mann Kendall Test. A total of 947 publications related to the topic were published by 441 institutions between 1975 and 2022. There was a significant (p = 0.001) positive increase in the number of published documents. Hungarian Academy of Science (210 documents) and University of Debrecen (132 documents) recorded the highest number of publications contributing 58.7% of the maize research literature in Hungary. The major research areas included: increasing maize yield, hybrid development, pests and diseases, irrigation, fertilization (nitrogen), drought, temperature, gene expression and climate change. The increasing number of published documents signifies an improved response to addressing maize production challenges through research in order to boost its productivity.

Molecular mechanisms of drought resistance using genome-wide association mapping in maize (Zea mays L.)

BACKGROUND

Drought is a critical abiotic stress that influences maize yield and reduces grain yield when it occurs at the flowering or filling stage. To dissect the genetic architecture of grain yield under drought stress (DS), a genome-wide association analysis was conducted in a maize population composed of diverse inbred lines from five locations under well-watered and DS conditions at flowering in 2019 and 2020.

RESULTS

Using a fixed and random model circulating probability unification model, a total of 147 loci associated with grain yield or the drought resistance index (DRI) were identified, of which 54 loci were associated with a DRI with an average phenotypic variation explanation of 4.03%. Further, 10 of these loci explained more than 10% of the phenotypic variation. By integrating two public transcriptome datasets, 22 differentially expressed genes were considered as candidate genes, including the cloned gene ZmNAC49, which responds to drought by regulating stomatal density. Enrichment and protein interaction network showed that signaling pathways responded to drought resistance, including jasmonic acid and salicylic acid, mitogen-activated protein kinase, and abscisic acid-activated. Additionally, several transcription factors involved in DS were identified, including basic leucine zipper (GRMZM2G370026), NAC (GRMZM2G347043), and ethylene-responsive element binding protein (GRMZM2G169654).

CONCLUSIONS

In this study, we nominated several genes as candidate genes for drought resistance by intergrating association maping and transcription analysis. These results provide valuable information for understanding the genetic basis of drought tolerance at the mature stage and for designing drought-tolerant maize breeding.

Dataset on effects of nitrogen fertilizer and soil moisture levels on the performance of Water Efficient Maize (WEMA) on Ferric Luvisol and Rhodic Ferralsol soils

The most important factors affecting maize production are water stress and nitrogen deficiency. A greenhouse experiment was conducted to assess the influence of different N fertilizers and soil moisture levels on the growth and yields of the WEMA variety on two different soils. The experiment was designed in a factorial of 5 × 2 × 2 fitted into a three replicate completely randomized design. Treatments included five N fertilizer rates (0, 60, 120, 180, and 240 kg N/ha), two soil moisture levels [45 and 100% field capacity], and two soil types. The morphological traits, physiological traits, drought indices and agronomic efficiency were determined. The data were analyzed using GenStat, version 11, analysis of variance (ANOVA), and differences in treatment means were assessed with a probability of 5% using the Duncan Multiple Range Test (DMRT). The associations between the measured parameters were examined using regression and correlation analysis. Data were analyzed using analysis of variance (ANOVA) of GenStat, edition 11, and differences in treatment means were tested using the Duncan Multiple Range Test (DMRT) with a probability of 5%. The regression and correlation analyses were used to examine the relationships between the measured parameters.

Selection of maize hybrids based on genotype × yield × trait (GYT) in different environments

This study aimed to identify the best genotypes using the genotype × yield × trait (GYT) method. To investigate the relationships was performed between yield × traits in four regions of Karaj, Birjand, Shiraz and Arak in two cropping years in a randomized complete block design (RCBD) with three replications. The average grain yield in four regions and two years of the experiment was calculated as 5966 kg/ha, and GYT was obtained based on the multiplication of grain yield with different traits. Comparing the average effect of genotype × year in different environments showed that KSC703 and KSC707 hybrids are among the most productive hybrids among the studied genotypes in grain yield. By examining the correlation coefficients between yield × traits in the tested areas, Y × TWG with Y × GW, Y × NRE, Y × NGR and Y × EL, Y × ED with Y × NGR, Y × NRE with Y × GW and the combination of Y × GW with Y × GL had a positive and significant correlation in all regions. The correlation diagrams were drawn on the evaluated areas' data and showed the correlation of most compounds except Y × GT with each other. Based on the analysis of the main components, the first three components explained the greatest diversity in the population. They were named the component ear grain profile, grain thickness component and plant height profile component.

Stability yield indices on different sweet corn hybrids based on AMMI analysis

Currently, sweet corn is considered an important crop due to its high sugar content and low starch content. Important sugars in sweet corn include sucrose, fructose, glucose, and maltose. The purpose of the present study was to use the yield indices of the eight examined sweet corn hybrids and the correlation of the yield indices together. Concentration is important for consumers in terms of yield indices. The research site was located at the Látókép Experimental Station of the University of Debrecen. The small plot experiment had a strip plot design with four replications. The previous crop was sweet corn; the plant density was 64 thousand/ha. The obtained result indicates that Biplot AMMI based on IPCA1 showed that the DB, NO, GS, and GB hybrids had stability and high performance in terms of yield indices. At the same time, fructose and glucose had stable parameters for the hybrids involved in the study. IPCA1 AMMI biplot showed that the ME hybrid had stability and high performance in terms of iron and zinc as well. IPCA2 AMMI biplot showed that DE, GB, and GS hybrids had stability and the highest performance on yield parameters in the scope of the research. Fructose, glucose, and sucrose had stable parameters on hybrids based on IPCA2. The DB and SE hybrids had desirable performance in Lutein and Zeaxanthin based on the biplot. The DE hybrid had a maximum performance on iron and zinc parameters.