Agrosystems, Geosciences & Environment最新文献

Maize (Zea mays L.) tolerance to early defoliation is shaped by genotype-specific physiological and morphological responses. Defoliation disrupts the source–sink balance, altering carbon allocation and plant development. Understanding these responses is crucial for optimizing breeding programs and agronomic management. In this study, the effects of complete canopy defoliation at vegetative stage 4 on growth parameters, root morphology, chlorophyll fluorescence, and yield stability in four maize genotypes were evaluated. Defoliation significantly reduced total leaf area, plant height, and root biomass while increasing root tissue density and the harvest index across all genotypes. Despite these structural changes, no significant differences were observed in key yield components, especially grain yield. Chlorophyll fluorescence analysis revealed distinct genotype-specific responses. Under defoliation, KWS9606 VIP3 exhibited enhanced photochemical efficiency at 9 days after defoliation (DAD) and increased quenching photochemical (qP) at 17 and 24 DAD. While BRS1010, qP increased under defoliation at all dates, suggesting greater openness of PSII reaction centers. NPQ responses were variable and lacked a consistent pattern, indicating diverse energy dissipation strategies. NS90 PRO2 exhibited no significant differences between genotype × defoliation level combinations, reflecting limited physiological response. Principal component analysis highlighted the trade-offs between morphological and physiological adaptations, with root traits dominating first principal component and chlorophyll fluorescence parameters influencing second principal component. These findings indicate that maize genotypes exhibit diverse acclimation mechanisms to mitigate defoliation stress while maintaining yield stability. Understanding genotype-specific responses supports breeding programs aimed at improving tolerance to foliar loss and informs more resilient crop management strategies.

This study evaluated the yield stability of 14 advanced lentil genotypes alongside two control cultivars (Kimia and Gachsaran) across three growing seasons (2013–2016) and three locations in Iran (Gachsaran, Ilam, and Khoramabad). A randomized complete block design with three replications was employed at each site. The likelihood ratio test confirmed significant effects for environment and genotype-by-environment interaction (GEI). A scree test determined that the first three interaction principal components were significant, collectively explaining 79.27% of the total GEI variation. According to the additive main effects and multiplicative interaction 1 (AMMI1) biplot, genotypes G10, G6, G7, G4, and G14 were identified as the most stable, demonstrating minimal contribution to the GEI. Furthermore, the AMMI2-based biplot (grain yield vs. weighted average absolute scores of BLUP [WAASB]) highlighted genotypes G1, G14, G18, G3, G6, G7, G4, G10, and G9 as possessing high yield and stability. By integrating AMMI and best linear unbiased prediction estimates and applying different weights for seed yield and stability (WAASB), genotypes G2, G9, G12, G16, and G8 were selected as high-performing and widely stable. Among all, G12 and G2 emerged as the most promising genotypes, combining superior yield with remarkable stability, and are thus recommended as ideal candidates for cultivar release and future breeding programs.

Understanding the genetic basis of grain yield and related traits in bread wheat under different water regimes is essential for improving moisture stress tolerance and water-use efficiency. This study aimed to identify stable loci associated with these traits under rainfed conditions. A single-nucleotide polymorphism (SNP)-based multi-locus genome-wide association study (ML-GWAS) was conducted using 22,962 polymorphic SNPs and six ML-GWAS models in 220 bread wheat genotypes sourced from International Maize and Wheat Improvement Center, International Center for Agricultural Research in the Dry Areas, and Ethiopian breeding programs. Field trials were carried out across three environments using an alpha lattice design with two replications. Combined analysis revealed highly significant (p < 0.001) differences among genotypes for most traits. The ML-GWAS identified seven stable quantitative trait nucleotides (QTNs) associated with four yield and yield-related traits, spanning 21 chromosomes. Candidate genes near these QTNs encode key functional proteins, including serine-rich protein, TF-B3 domain protein, zinc finger GRF-type protein, protein kinase domain protein, glycoside hydrolase family five proteins, cytochrome P450, polycomb VEFS-box protein, and auxin response factor implicated in drought tolerance, nutrient remobilization, and developmental regulation. These results provide valuable genomic resources for future breeding programs, offering robust markers for marker-assisted and genomic selection to accelerate the development of wheat varieties with improved resilience and yield stability under rainfed conditions.

Anthropogenic activities have increased CO₂ emissions, elevating global temperatures and disrupting rainfall patterns, thus affecting crop productivity. This study examines the photosynthetic performance of Zea mays under elevated temperatures (25°C and 30°C) and CO₂ levels (400 and 700 ppm) in two cropping systems: monoculture and an agroforestry system combining Z. mays with Neolamarckia cadamba. The experiment consisted of three water treatments: P1 (low rainfall), P2 (normal rainfall), and P3 (high rainfall), each with four replicates, giving a total of 12 pots per cropping system and 36 pots overall across the three experimental conditions. Key photosynthetic parameters measured were CO₂ assimilation rate (A), stomatal conductance (Gs), transpiration rate (E), and water use efficiency. Results revealed that Z. mays in the agroforestry system under normal rainfall, 25°C, and 700 ppm CO₂ recorded the highest net assimilation rate. This is likely due to favorable microclimatic conditions provided by the tree canopy, including better moisture retention and reduced heat stress. In contrast, the lowest photosynthetic performance occurred under low rainfall (P1), higher temperature (30°C), and ambient CO₂ concentration (400 ppm). Under these stress conditions, stomatal conductance declined significantly, restricting CO₂ uptake and reducing photosynthetic efficiency. These findings suggest that agroforestry systems could help mitigate the negative impacts of climate change on crop productivity. Integrating trees with crops could enhance photosynthetic performance under future climate scenarios, supporting sustainable agriculture and food security.

Little is known about the sustainability of an intercropping system comprising finger millet (Eleusine coracana) and pigeon pea (Cajanus cajan). We therefore sowed both cover crops and the above crops over 3 years in a seed mix of 8:2 by weight to assess their effects on soil properties, yield potential, and energy-use efficiency. Treatments consist of tillage intensity-conventional, reduced, or no tillage in combination with the cover crop horse gram or lablab bean versus no cover crop. Averaged over 3 years, conventional tillage required energy inputs 12% higher than reduced tillage and 4% higher than those without tillage. The sustainable yield index (89.6%) was highest in conventional tillage with horse gram as the cover crop with a mean of 51.6% and a variation of 42.3%. This combination also improved soil quality, although the energy index was greater under reduced tillage than under no-tillage or conventional tillage. In the wet year (2019), we had higher soil quality index values (8.45–9.97) than in the dry years (2018) (2.50–3.02). The right combination of a cover crop and the intensity of tillage may confer substantial environmental benefits with only minimal detrimental effects on yield.

In recent years, the cultivation area and consumption of quinoa (Chenopodium quinoa Willd) have increased in the country due to its nutritional properties and ability to grow in adverse conditions. Based on climate change scenarios, long periods of drought are expected, which emphasizes the need for planting and developing new plants that are adapted to these conditions. Quinoa's morphological, biochemical, and physiological responses to nanoparticle Fe and Zn foliar treatment during drought stress were examined. Quinoa development was also compared to zinc and iron. With nutrient supplementation, a 2019 drought experiment assessed quinoa growth and quality. The Giza1 cultivar of quinoa was evaluated for its morphological, biochemical, and physiological parameters. The experiment studied three factors: (1) Foliar application of different micronutrient combinations (control, Fe(as FeSO₄), Zn (as ZnSO₄), Fe+Zn, nano-Fe, nano-Zn, nano-Fe+nano-Zn); (2) Application timing at two reproductive stages (50% flowering and 100% flowering); and (3) Drought stress at two levels: control (irrigation at soil moisture potential of field capacity) and stress (irrigation at soil moisture potential of −9 bar). Drought stress greatly reduced plant height, main and lateral branch numbers, leaf number, inflorescence length, leaf, stem, and seed dry weight, wet and dry plant weights, and seed output. Foliar fertilizer increased plant height, main and lateral branch numbers, leaves, inflorescence length, stem, seed dry weights, and plant wet and dry weights. Iron and zinc nanoparticles were better nutrition. Drought stress affects quinoa production less with fertilizer. Also most metrics were negatively affected by drought stress; however, foliar nano-Fe and nano-Zn at 50% flowering minimized its negative effects. High protein, proline, soluble carbohydrates, water, photosynthetic pigments, antioxidant enzyme activity, and low malondialdehyde. Drought stress-application time-nutrient correlations were significant in most parameters. At50% blooming, nano-Fe and nano-Zn treatments had the highest protein, proline, soluble carbohydrate, and antioxidant enzyme levels under drought stress.

Taro (Colocasia esculenta (L.) Schott) is one of the neglected root crops with great potential for ensuring food security. Nigerian taro genetic diversity has been rarely reported, particularly using single-nucleotide polymorphism (SNP) markers. The objective of the present study was to determine the genetic diversity of taro accessions based on agro-morphological traits and Diversity Arrays Technology sequence (DArTseq) SNP markers. Twenty-five accessions collected from five states in Nigeria were used in the study. A field experiment was conducted at Ebonyi State University during the 2020 and 2021 cropping seasons using a 5 × 5 lattice design. Sequencing was performed at Biosciences Eastern and Central Africa (International Livestock Research Institute), Nairobi, Kenya. The results for qualitative traits showed significant (p < 0.05) differences among the accessions, with a mean Shannon–Weaver diversity index (H′) of 0.68. Most quantitative traits also showed significant differences among accessions. Genetic cluster analysis indicated the formation of two major clusters and confirmed the existence of variability among accessions. The polymorphic information content of markers ranged from 0.48 to 0.49. The taro population gene diversity/expected heterozygosity (He) ranged from 0.24 to 0.26, while the observed heterozygosity (Ho) ranged from 0.42 to 0.45. Analysis of molecular variance revealed high genetic variation among individuals within populations (86.90%) but low genetic variation among populations (13.10%). Therefore, breeding strategies should focus on exploiting variation within populations rather than between them. The findings of this study provide a foundational resource for the conservation, management, and utilization of these genetic resources to develop improved taro cultivars in Nigeria and similar agroecologies.

Participatory variety selection (PVS) offers a practical alternative to researcher-led breeding by directly involving farmers in evaluating and selecting crop varieties that meet their production needs and local conditions. This study assessed the agronomic performance and farmer preferences for eight released teff varieties and one standard check during the 2021 and 2022 cropping seasons in Shebel Berenta and Dejen districts of the East Gojjam Zone, Ethiopia. Mother-and-baby trials were established using a randomized complete block design at Farmer Training Centers. Significant variation was observed among varieties across years and locations. Boset produced the highest grain yield in Shebel Berenta (3285 kg/ha), yielding 21.00% more than the standard check, Quncho, while in Dejen, it produced 2256 kg/ha, a 26.80% advantage over the standard check. Farmers identified grain yield, panicle length, and tillering ability as the most important selection criteria. Boset was the top-preferred variety in both locations, followed by Dagem and Quncho in Shebel Berenta, and Felagot and Quncho in Dejen. The findings demonstrate the practical value of PVS in generating varieties that align with farmers’ priorities, thereby enhancing the likelihood of adoption and ensuring better matching between breeding objectives and local agronomic and market needs.

Pecans [Carya illinoinensis (Wangenh.) K. Koch] are widely cultivated in the semi-arid and arid regions of New Mexico and Texas, where irrigation relies heavily on the Rio Grande River and brackish groundwater. This study evaluated the impact of these water sources on soil physicochemical properties, nutrient availability, and pecan tree performance across six orchards along the Rio Grande in southern New Mexico and western Texas over two growing seasons. Soil samples were analyzed for texture, ion concentrations, sodium adsorption ratio (SAR), electrical conductivity (EC), and pH. Pecan performance was assessed using stem water potential (SWP) and leaf and kernel nutrient concentrations. Soil texture significantly influenced magnesium (Mg), calcium (Ca), and sodium (Na). The highest SAR (11.75) and EC (6.21 dS/m) were observed in loamy soil at Fabens 2, with pH ranging from 7.3 to 7.5. SWP values ranged from −12 to −14 bar in clayey soils and −10 to −12.5 bar in sandy soils. Leaf and kernel nutrient concentrations varied by location, with the highest zinc (Zn) levels in Fabens 2 (leaf: 160 mg/kg) and Derry (kernel: 120 mg/kg), and peak phosphorus (P) in Derry (leaf: 1195 mg/kg) and Las Cruces (kernel: 2858 mg/kg). Loamy soils with higher EC supported elevated Zn, Na, and potassium (K) in leaves, while sandy loams promoted higher Mg and kernel nutrient accumulation. In leaf, Zn decreased with Mg and K, while Na was strongly antagonistic to Ca and Mg. In the kernel, P, Mg, Ca, and K increased together. Zn tended to decline as P and K were raised. Seasonal variations showed greater Mg, Ca, and Na in leaves in October, while P and Ca in kernels peaked in 2015. A massive increase in nutrients from soil to leaf, then a decrease in the kernel. These findings underscore the need for site-specific nutrient management and regular soil and tissue testing to optimize fertilization and mitigate imbalances.

Peppermint (Mentha piperita) is a perennial herb valued for its menthol-rich oil and requires high nitrogen (N) inputs for its irrigated production. Optimizing N management can reduce nitrous oxide (N₂O) emissions, a potent greenhouse gas associated with fertilizer N input. A 2-year experiment (2022–2023) was conducted in western Nebraska to evaluate the effects of N fertilizer sources (urea and polymer-coated urea; PCU) applied at different rates on peppermint yield and N₂O emissions. Application rates were lower in 2022 than in 2023 due to transplanting and herbicide injury issues. Therefore, dry matter yield was lower in 2022 (3.38–3.84 Mg ha⁻¹) than in 2023 (7.56–14.11 Mg ha⁻¹). In 2023, PCU at the highest rate (332 kg N ha⁻¹) had a greater peppermint dry matter yield than all other treatment combinations except for urea at the same rate. In 2023, yield did not vary with N source, except at the low rate, where PCU had a greater yield (12.14 Mg ha⁻¹) than urea (9.31 Mg ha⁻¹). In both years, urea had greater N₂O emissions than PCU, except for the lowest N rate (34 kg N ha⁻¹) in 2022. Nitrous oxide emissions varied by N rates for urea but not for PCU. Fertilizer-induced emission factors (FIEF) were within the range of the Intergovernmental Panel on Climate Change (IPCC) disaggregated emission factor of 0.5% (0.0%–1.1%) for dry climates. Nitrogen source-specific FIEF disaggregation might narrow the current IPCC uncertainty range.