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1.
Sci Total Environ ; 806(Pt 4): 150967, 2022 Feb 01.
Article in English | MEDLINE | ID: mdl-34656603

ABSTRACT

Improvement of nutrient use efficiency and limiting trace elements such as arsenic and uranium bioavailability is critical for sustainable agriculture and food safety. Arsenic and uranium possess different properties and mobility in soils, which complicates the effort to reduce their uptake by plants. Here, we postulate that unsaturated soil amended with ferrihydrite nanominerals leads to improved nutrient retention and helps reduce uptake of these geogenic contaminants. Unsaturated soil is primarily oxic and can provide a stable environment for ferrihydrite nanominerals. To demonstrate the utility of ferrihydrite soil amendment, maize was grown in an unsaturated agricultural soil that is known to contain geogenic arsenic and uranium. The soil was maintained at a gravimetric moisture content of 15.1 ± 2.5%, typical of periodically irrigated soils of the US Corn Belt. Synthetic 2-line ferrihydrite was used in low doses as a soil amendment at three levels (0.00% w/w (control), 0.05% w/w and 0.10% w/w). Further, the irrigation water was fortified (~50 µg L-1 each) with elevated arsenic and uranium levels. Plant dry biomass at maturity was ~13.5% higher than that grown in soil not receiving ferrihydrite, indicating positive impact of ferrihydrite on plant growth. Arsenic and uranium concentrations in maize crops (root, shoot and grain combined) were ~ 20% lower in amended soils than that in control soils. Our findings suggest that the addition of low doses of iron nanomineral soil amendment can positively influence rhizosphere geochemical processes, enhancing nutrient plant availability and reduce trace contaminants plant uptake in sprinkler irrigated agroecosystem, which is 55% of total irrigated area in the United States.


Subject(s)
Arsenic , Soil Pollutants , Uranium , Arsenic/analysis , Ferric Compounds , Nutrients , Rhizosphere , Soil , Soil Pollutants/analysis
2.
Nat Commun ; 12(1): 5549, 2021 09 20.
Article in English | MEDLINE | ID: mdl-34545076

ABSTRACT

Irrigation is an important adaptation to reduce crop yield loss due to water stress from both soil water deficit (low soil moisture) and atmospheric aridity (high vapor pressure deficit, VPD). Traditionally, irrigation has primarily focused on soil water deficit. Observational evidence demonstrates that stomatal conductance is co-regulated by soil moisture and VPD from water supply and demand aspects. Here we use a validated hydraulically-driven ecosystem model to reproduce the co-regulation pattern. Specifically, we propose a plant-centric irrigation scheme considering water supply-demand dynamics (SDD), and compare it with soil-moisture-based irrigation scheme (management allowable depletion, MAD) for continuous maize cropping systems in Nebraska, United States. We find that, under current climate conditions, the plant-centric SDD irrigation scheme combining soil moisture and VPD, could significantly reduce irrigation water use (-24.0%) while maintaining crop yields, and increase economic profits (+11.2%) and irrigation water productivity (+25.2%) compared with MAD, thus SDD could significantly improve water sustainability.

3.
Front Big Data ; 2: 34, 2019.
Article in English | MEDLINE | ID: mdl-33693357

ABSTRACT

Variable rate irrigation (VRI) may improve center pivot irrigation management, including deficit irrigation. A remote-sensing-based evapotranspiration model was implemented with Landsat imagery to manage irrigations for a VRI equipped center pivot irrigated field located in West-Central Nebraska planted to maize in 2017 and soybean in 2018. In 2017, the study included VRI using the model, and uniform irrigation using neutron attenuation for full irrigation with no intended water stress (VRI-Full and Uniform-Full treatments, respectively). In 2018, two deficit irrigation treatments were added (VRI-Deficit and Uniform-Deficit, respectively) and the model was modified in an attempt to reduce water balance drift; model performance was promising, as it was executed unaided by measurements of soil water content throughout the season. VRI prescriptions did not correlate well with available water capacity (R 2 < 0.4); however, they correlated better with modeled ET in 2018 (R 2 = 0. 69, VRI-Full; R 2 = 0.55, VRI-Deficit). No significant differences were observed in total intended gross irrigation depth in 2017 (VRI-Full = 351 mm, Uniform Full = 344). However, in 2018, VRI resulted in lower mean prescribed gross irrigation than the corresponding uniform treatments (VRI-Full = 265 mm, Uniform Full = 282 mm, VRI-Deficit = 234 mm, and Uniform Deficit = 267 mm). Notwithstanding the differences in prescribed irrigation (in 2018), VRI did not affect dry grain yield, with no statistically significant differences being found between any treatments in either year (F = 0.03, p = 0.87 in 2017; F = 0.00, p = 0.96 for VRI/Uniform and F = 0.01, p = 0.93 for Full/Deficit in 2018). Likewise, any reduction in irrigation application apparently did not result in detectable reductions in deep percolation potential or actual evapotranspiration. Additional research is needed to further vet the model as a deficit irrigation management tool. Suggested model improvements include a continuous function for water stress and an optimization routine in computing the basal crop coefficient.

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