Showing papers by "Qingwu Xue published in 2021"

Annual forage impacts on dryland wheat farming in the Great Plains

Abstract: Wheat (Triticum spp.) dominates dryland grain crop production in the North American Great Plains and other regions with semi‐arid steppe climates. A common practice is to alternate winter or spring wheat with a 14‐ to 21‐mo fallow period to allow for soil‐water recharge, despite economic inefficiencies and environmental degradation. Replacing fallow with non‐ cereal grain and seed crops often reduces future wheat yields due to increased water stress during grain fill. The use of annual forages may not have the disadvantages associated with grain and seed crops. The objective of this review was to determine benefits and challenges of incorporating annual forages into dryland wheat systems in semi‐arid steppe climates, using the Great Plains within the United States as a model system. Results indicate that: (a) cool‐ and warm‐season, annual grass and broadleaf species can be grown for forage across the region; (b) forage production will be less risky than grain and seed crop production under predicted climate‐change scenarios; (c) grazing annual forages may offer advantages (e.g., nutrient cycling, improved soil structure, added revenue from livestock) over mechanically harvesting annual forages; (d) the lack of infrastructure and local markets impede the use of annual forages to diversify wheat‐based cropping systems in the region; and (e) limited networking among researchers hinders the advancement in knowledge on how annual forages can be used to improve dryland wheat system resilience. Carr, Patrick M, Bell, Jourdan M, Boss, Darrin L, DeLaune, Paul, Eberly, Jed O., Edwards, Laura, Fryer, Heather, Graham, Christopher, Holman, John, Islam, M. Anowarul, Leibig, Mark, Miller, Perry R., Obour, Augustine, and Xue, Qingwu. “Annual forage impacts on dryland wheat farming in the Great Plains.” Agronomy Journal. (2021): 113: 1– 25.

RNA-seq analysis reveals different drought tolerance mechanisms in two broadly adapted wheat cultivars ‘TAM 111’ and ‘TAM 112’

Abstract: Wheat cultivars 'TAM 111' and 'TAM 112' have been dominantly grown in the Southern U.S. Great Plains for many years due to their high yield and drought tolerance. To identify the molecular basis and genetic control of drought tolerance in these two landmark cultivars, RNA-seq analysis was conducted to compare gene expression difference in flag leaves under fully irrigated (wet) and water deficient (dry) conditions. A total of 2254 genes showed significantly altered expression patterns under dry and wet conditions in the two cultivars. TAM 111 had 593 and 1532 dry-wet differentially expressed genes (DEGs), and TAM 112 had 777 and 1670 at heading and grain-filling stages, respectively. The two cultivars have 1214 (53.9%) dry-wet DEGs in common, which agreed with their excellent adaption to drought, but 438 and 602 dry-wet DEGs were respectively shown only in TAM 111 and TAM 112 suggested that each has a specific mechanism to cope with drought. Annotations of all 2254 genes showed 1855 have functions related to biosynthesis, stress responses, defense responses, transcription factors and cellular components related to ion or protein transportation and signal transduction. Comparing hierarchical structure of biological processes, molecule functions and cellular components revealed the significant regulation differences between TAM 111 and TAM 112, particularly for genes of phosphorylation and adenyl ribonucleotide binding, and proteins located in nucleus and plasma membrane. TAM 112 showed more active than TAM 111 in response to drought and carried more specific genes with most of them were up-regulated in responses to stresses of water deprivation, heat and oxidative, ABA-induced signal pathway and transcription regulation. In addition, 258 genes encoding predicted uncharacterized proteins and 141 unannotated genes with no similar sequences identified in the databases may represent novel genes related to drought response in TAM 111 or TAM 112. This research thus revealed different drought-tolerance mechanisms in TAM 111 and TAM 112 and identified useful drought tolerance genes for wheat adaption. Data of gene sequence and expression regulation from this study also provided useful information of annotating novel genes associated with drought tolerance in the wheat genome.

Assessing the Effect of Drought on Winter Wheat Growth Using Unmanned Aerial System (UAS)-Based Phenotyping

Abstract: Drought significantly limits wheat productivity across the temporal and spatial domains. Unmanned Aerial Systems (UAS) has become an indispensable tool to collect refined spatial and high temporal resolution imagery data. A 2-year field study was conducted in 2018 and 2019 to determine the temporal effects of drought on canopy growth of winter wheat. Weekly UAS data were collected using red, green, and blue (RGB) and multispectral (MS) sensors over a yield trial consisting of 22 winter wheat cultivars in both irrigated and dryland environments. Raw-images were processed to compute canopy features such as canopy cover (CC) and canopy height (CH), and vegetation indices (VIs) such as Normalized Difference Vegetation Index (NDVI), Excess Green Index (ExG), and Normalized Difference Red-edge Index (NDRE). The drought was more severe in 2018 than in 2019 and the effects of growth differences across years and irrigation levels were visible in the UAS measurements. CC, CH, and VIs, measured during grain filling, were positively correlated with grain yield (r = 0.4–0.7, p < 0.05) in the dryland in both years. Yield was positively correlated with VIs in 2018 (r = 0.45–0.55, p < 0.05) in the irrigated environment, but the correlations were non-significant in 2019 (r = 0.1 to −0.4), except for CH. The study shows that high-throughput UAS data can be used to monitor the drought effects on wheat growth and productivity across the temporal and spatial domains.

Managing Micronutrients for Improving Soil Fertility, Health, and Soybean Yield

Abstract: Plants need only a small quantity of micronutrients, but they are essential for vital cell functions. Critical micronutrients for plant growth and development include iron (Fe), boron (B), manganese (Mn), zinc (Zn), copper (Cu), molybdenum (Mo), chlorine (Cl), and nickel (Ni). The deficiency of one or more micronutrients can greatly affect plant production and quality. To explore the potential for using micronutrients, we reviewed the literature evaluating the effect of micronutrients on soybean production in the U.S. Midwest and beyond. Soil and foliar applications were the major micronutrient application methods. Overall, studies indicated the positive yield response of soybean to micronutrients. However, soybean yield response to micronutrients was not consistent among studies, mainly because of different environmental conditions such as soil type, soil organic matter (SOM), moisture, and temperature. Despite this inconsistency, there has been increased pressure for growers to apply micronutrients to soybeans due to a fact that deficiencies have increased with the increased use of high-yielding cultivars. Further studies on quantification and variable rate application of micronutrients under different soil and environmental conditions are warranted to acquire more knowledge and improve the micronutrient management strategies in soybean. Since the SOM could meet the micronutrient need of many crops, management strategies that increase SOM should be encouraged to ensure nutrient availability and improve soil fertility and health for sustainable soybean production.

Cotton photosynthetic productivity enhancement through uniform row-spacing with optimal plant density in Xinjiang, China.

Abstract: Xinjiang is currently the most dominant cotton (Gossypium hirsutum L.)-growing region in China and possesses abundant radiation resource. The cultivation techniques such as wide and narrow row-spacing and high density are widely adopted to obtain high cotton yield in the region. However, the region is facing some problems including poor light transmittance in the field and low exploitation for light resources under the current planting pattern which impedes further growth in cotton yields. Therefore, it is essential to develop some cultivation practices to increase radiation use efficiency (RUE) and cotton yields in Xinjiang. Here we conducted a field experiment to quantify the effects of row spacing pattern and plant density on RUE, intercepted photosynthetically active radiation from May to August (IRAR5-8), and lint yield during 2017 and 2018. In this study, we designed two row-spacing configurations (R1, wide and narrow configuration, 66 cm + 10 cm; R2, uniform row-spacing configuration, 76 cm) and six plant densities (4.5, 9.0, 13.5, 18.0, 22.5, and 27.0 plants m-2). The RUE, lint yield, and number of bolls were higher in R2 than R1 by 4.1-5.9, 2.5-4.8, and 9.1-14.2%, respectively. The RUE significantly increased with plant density, but lint yield stabilized at 18.0 plants m-2. Moreover, RUE had more significant positive effects on boll number and lint yield. Overall, we found that R2 combined with optimal plant densities (13.5-18.0 plants m-2) would be an effective strategy to achieve higher RUE and yields in the Xinjiang cotton system.

Effect of nitrogen supply on stay-green sorghum in differing post-flowering water regimes

Abstract: The expression of stay-green (SG) characteristic in sorghum under water stress was related to N supply. SG genotype performed better than a non-stay-green (NSG) genotype at medium and high N levels. The differences in physiological parameters between SG and NSG genotypes were not significant at low N level and severe water stress. Grain sorghum [Sorghum bicolor (L.) Moench] with stay-green (SG) trait has the potential to produce more biomass and use soil water and nitrogen (N) more efficiently under post-flowering water stress. Previous studies were mostly conducted without N deficiency and more information is needed for interactions among soil N availability, SG genotype, and post-flowering water stress. In this study, the differences in leaf growth and senescence, shoot and root biomass, evapotranspiration (ET), water use efficiency (WUE), leaf photosynthetic responses, and nitrogen use efficiency (NUE) between a SG genotype (BTx642) and a non-stay-green (NSG) genotype (Tx7000) were examined. The two genotypes were grown at three N levels (Low, LN; Medium, MN; High, HN) and under three post-flowering water regimes (No water deficit, ND; Moderate water deficit, MD; Severe water deficit, SD). The genotypic difference was generally significant while it frequently interacted with N levels and water regimes. At medium and high N levels, SG genotype consistently had greater green leaf area, slower senescence rate, more shoot biomass and root biomass, and greater WUE and NUE than the NSG genotype under post-flowering drought. However, differences in several variables (e.g., leaf senescence, ET, WUE and NUE) between genotypes were not significant under SD at LN. At HN and MN, photosynthetic function of SG genotype was better maintained under drought. At LN, SG genotype maintained greater green leaf area but had lower photosynthetic activity than the NSG genotype. Nonetheless, adequate N supply is important for SG genotype under drought and greater root biomass may contribute to greater NUE in SG genotype.

A New Strategy for Using Historical Imbalanced Yield Data to Conduct Genome-Wide Association Studies and Develop Genomic Prediction Models for Wheat Breeding

Abstract: Using imbalanced historical yield data to predict performance and select new lines is an arduous breeding task. An association mapping panel of 227 Texas elite (TXE) wheat breeding lines was used for GWAS and a training population to develop prediction models for grain yield selection. An imbalanced set of yield data collected from 102 environments (year-by-location) over ten years was used. Based on correlations among data from different environments within two adjacent years and broad-sense heritability estimated in each environment, yield data from 87 environments were selected and assigned to two correlation-based groups. The yield best linear unbiased estimation (BLUE) from each group, along with reaction to greenbug and Hessian fly in each line, were used for GWAS to reveal genomic regions associated with yield and insect resistance. A total of 74 genomic regions were associated with grain yield and two of them were commonly detected in both correlation-based groups. Greenbug resistance in TXE lines was mainly controlled by Gb3 on chromosome 7DL in addition to two novel regions on 3DL and 6DS, and Hessian fly resistance was conferred by the region on 1AS. Genomic prediction models developed in two correlation-based groups were validated using a set of 105 new advanced breeding lines and the model from correlation-based group G2 was more reliable for prediction. This research not only identified genomic regions associated with yield and insect resistance but also established the method of using historical imbalanced breeding data to develop a genomic prediction model for crop improvement.

Transpiration efficiency of corn hybrids at different growth stages

Abstract: Understanding transpiration efficiency (TE), especially in water-limited environments, is likely to result in increased crop yield. Two successive greenhouse experiments were conducted in 2017 to d...