Maize Production under Drought Stress: Nutrient Supply, Yield Prediction

Széles, Adrienn; Horváth, Éva; Simon, Károly; Zagyi, Péter; Huzsvai, László

doi:10.3390/plants12183301

Cited by 9 publications

(9 citation statements)

References 92 publications

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“…These yield losses fall within the range reported by other authors [16,[40][41][42][43]. The magnitude of grain yield reduction as a result of drought is known to depend on the duration and intensity of the drought stress [44][45][46][47].…”

Section: Discussionsupporting

confidence: 87%

Performance and Stability Analysis of Extra-Early Maturing Orange Maize Hybrids under Drought Stress and Well-Watered Conditions

Bonkoungou,

Badu-Apraku,

Adetimirin

et al. 2024

Agronomy

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The consistently low yield turnout of maize on farmers’ fields owing to drought and the nutritional challenges attributable to the consumption of white endosperm maize pose a major threat to food and nutritional security in Sub-Saharan Africa (SSA). The objectives of this study were to assess the performance of newly developed extra-early maturing orange hybrids under managed drought and well-watered conditions, compare the outcomes of multiple-trait base index and multi-trait genotype–ideotype distance index selection procedures, and identify drought-tolerant hybrids with stable performance across contrasting environments for commercialization in SSA. One hundred and ninety orange hybrids and six checks were evaluated under managed drought and well-watered conditions at Ikenne for two seasons between 2021 and 2023. A 14 × 14-lattice design was used for the field evaluations under both research conditions. Drought stress was achieved by the complete withdrawal of irrigation water 25 days after planting. Results revealed significant differences among the hybrids under drought and well-watered conditions. Grain yield, ears per plant, and plant aspect under managed drought were correlated to the same traits under well-watered conditions, suggesting that the expression of these traits is governed by common genetic factors. Twenty-nine hybrids were identified as top-performing drought-tolerant hybrids by the multiple-trait base index and the multi-trait genotype–ideotype distance index. Of the selected outstanding 29 hybrids, 34% were derived from crosses involving the tester TZEEIOR 197, demonstrating the outstanding genetic potential of this inbred line. Further analysis of the 29 selected hybrids revealed TZEEIOR 509 × TZEEIOR 197 as the hybrid that combined the most drought-tolerant adaptive traits. However, the hybrids TZEEIOR 526 × TZEEIOR 97, TZEEIOR 384 × TZEEIOR 30, TZEEIOR 515 × TZEEIOR 249, TZEEIOR 510 × TZEEIOR 197, TZEEIOR 479 × TZEEIOR 197, and TZEEIOR 458 × TZEEIOR 197 were identified as the most stable hybrids across drought and well-watered conditions. These hybrids should be extensively tested in multi-location trials for deployment and commercialization in SSA.

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Section: Discussionsupporting

confidence: 87%

Performance and Stability Analysis of Extra-Early Maturing Orange Maize Hybrids under Drought Stress and Well-Watered Conditions

Bonkoungou,

Badu-Apraku,

Adetimirin

et al. 2024

Agronomy

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“…Physiological traits, such as chlorophyll content (SPAD), showed significantly higher levels under normal conditions compared to drought conditions. This finding affirms that drought reduces chlorophyll concentration in maize leaves, leading to a reduction in nitrogen concentration (Kira et al, 2016;Széles et al, 2023). A significant reduction was also found in LA trait under drought condition, suggesting the plant's response to water scarcity by adjusting its foliage area.…”

Section: Analysis Of Hybrid Performance Under Normal and Drought Cond...supporting

confidence: 79%

Optimizing ensembles machine learning, genetic algorithms, and multivariate modeling for enhanced prediction of maize yield and stress tolerance index

Azrai,

Aqil,

Andayani

et al. 2024

Front. Sustain. Food Syst.

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The frequent occurrence of drought, halting from unpredictable climate-induced weather patterns, presents significant challenges in breeding drought-tolerant maize to identify adaptable genotypes. The study explores the optimization of machine learning (ML) to predict both the grain yield and stress tolerance index (STI) of maize under normal and drought-induced stress. In total, 35 genotypes, comprising 31 hybrid candidates and four commercial varieties, were meticulously evaluated across three normal and drought-treated sites. Three popular ML were optimized using a genetic algorithm (GA) and ensemble ML to enhance data capture. Additionally, a Multi-trait Genotype-Ideotype Distance (MGIDI) was also involved to identify superior maize hybrids well-suited for drought conditions. The results highlight that the ensemble meta-models optimized by grid search exhibit robust performance with high accuracy across the testing datasets (R2 = 0.92 for grain yield and 0.82 for STI). The RF optimized by GA algorithm demonstrates slightly lower performance (R2 = 0.91 for grain yield and 0.79 for STI), surpassing the predictive performance of individual SVM-GA and KNN-GA models. Selection of the best-performing hybrids indicated that out of the six hybrids with the highest STI values, both the ensemble and MGIDI can accurately predict four hybrids, namely H06, H10, H13, and H35. Thus, combining ML with MGIDI enables researchers to discern traits for each genotype and holds promise for advancing the field of drought-tolerant maize breeding and expediting the development of resilient varieties.

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“…The SPAD meter, a reading recognized as a reliable indicator of chlorophyll content, has proven instrumental in quantifying stress-related alterations. The findings of Szeles et al [3] underscore the significant reduction in SPAD values under water stress conditions, offering a tangible measure of the impact on chlorophyll dynamics. Humic acid is known for its beneficial effects on root growth and expansion; therefore, it has demonstrated its ability to enhance water uptake and improve plant water status, offering a promising remedy to subside the harmful effects of water stress.…”

Section: Introductionmentioning

confidence: 86%

Exploring the Effect of Humic Acid on Chlorophyll Levels in Japanese Mint under Drip and Flood Irrigation Amidst Water and Nutrient Constraints

Baurai,

Singh,

Raverkar

et al. 2024

IJPSS

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A field experiment on Mentha (Mentha arvensis L.) was conducted during the spring seasons of 2022 and 2023 at G.B. Pant University of Agriculture and Technology, Pantnagar. The objective was to investigate the impact of foliar spray of humic acid on SPAD values under conditions of limited water and nutrients. The experiment comprised two drip irrigation levels (80% and 100% of crop evapotranspiration) and four nutrient management practices. These practices included: 25% NPK basal + 75% NPK fertigation, 50% NPK basal + 50% NPK fertigation, No basal + 75% NPK fertigation + three foliar sprays of humic acid at 0.3%, and 25% NPK basal + 50% NPK fertigation + three foliar sprays of humic acid at 0.3%. The experiment was laid out in a randomized block design with three replicates (factorial), and an extra control was included. The control followed conventional practices, where the crop received recommended doses of fertilizers (N: P2O5: K2O @ 120:60:40 kg/ha) and was irrigated at an IW: CPE ratio of 1.2 with a 5 cm irrigation depth. Significantly higher SPAD values were observed when the crop was irrigated at 100% ETc level of drip irrigation and with nutrient management practices involving foliar application of humic acid, compared to 80% ETc level of drip irrigation and total NPK supply through chemical fertilizers, respectively. At harvest, crops irrigated at 100% ETc level recorded SPAD readings that were 11.1% and 18% higher than those irrigated at 80% ETc level during 2022 and 2023, respectively. The humic acid application helped to maintain the SPAD values even after a 25% reduction in nutrient dosage. SPAD values for control were significantly lower than the combination of best nutrient management practices with either 80 or 100% ETc level of drip irrigation.

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Maize Production under Drought Stress: Nutrient Supply, Yield Prediction

Cited by 9 publications

References 92 publications

Performance and Stability Analysis of Extra-Early Maturing Orange Maize Hybrids under Drought Stress and Well-Watered Conditions

Performance and Stability Analysis of Extra-Early Maturing Orange Maize Hybrids under Drought Stress and Well-Watered Conditions

Optimizing ensembles machine learning, genetic algorithms, and multivariate modeling for enhanced prediction of maize yield and stress tolerance index

Exploring the Effect of Humic Acid on Chlorophyll Levels in Japanese Mint under Drip and Flood Irrigation Amidst Water and Nutrient Constraints

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