Enhancement of agricultural systems models for limited irrigated cropping systems research

2013 Spring.Includes bibliographical references.To view the abstract, please see the full text of the document

Do maize crop models catch the impact of future [CO2] on maize yield and water use?

Do maize crop models catch the impact of future [CO2] on maize yield and water use?. iCROPM2016 International Crop Modelling Symposiu

Comparing CSM-CROPGRO and APSIM-OzCot Simulations for Cotton Production and Eddy Covariance-Based Evapotranspiration in Mississippi

Optimizing irrigation water use efficiency (WUE) is critical to reduce the dependency of irrigated cotton (Gossypium spp.) production on depleting aquifers. Cropping system models can integrate and synthesize data collected through experiments in the past and simulate management changes for enhancing WUE in agriculture. This study evaluated the simulation of cotton growth and evapotranspiration (ET) in a grower’s field using the CSM-CROPGRO-cotton module within the Decision Support System for Agrotechnology Transfer (DSSAT) and APSIM (Agricultural Production Systems simulator)-OzCot during 2017–2018 growing seasons. Crop ET was quantified using the eddy covariance (EC) method. Data collected in 2017 was used in calibrating the models and in 2018 validating. Over two cropping seasons, the simulated seedling emergence, flowering, and maturity dates were varied less than a week from measured for both models. Simulated leaf area index (LAI) varied from measured with the relative root mean squared errors (RRMSE) ranging between 20.6% to 38.7%. Daily ET deviated from EC estimates with root mean square errors (RMSEs) of 1.90 mm and 2.03 mm (RRMSEs of 63.1% and 54.8%) for the DSSAT and 1.95 mm and 2.17 mm (RRMSEs of 64.7% and 58.8%) for APSIM, during 2017 and 2018, respectively. Model performance varied with growing seasons, indicating improving ET simulation processes and long-term calibrations and validations are necessary for adapting the models for decision support in optimizing WUE in cotton cropping systems

Assessing the Effects of Agronomic Management Practices on Soybean (<i>Glycine max</i> L.) Post-Grain Harvest Residue Quality in the Lower Mississippi Delta

Livestock producers often resort to either baling or grazing of crop residues due to high hay prices and reduced supply of other forages and silage in the markets. Soil-water-crop management practices can affect residue nutrient qualities for its use as cattle feedstock. A two-year study (2018–2019) was conducted to investigate the effects of irrigation (AI, all row-irrigation; ARI, alternate row irrigation; and RF, rainfed) and planting pattern, PP (SR, single row; and TR, twin-row) on soybean (maturity group IV cv. 31RY45 Dyna-Gro) post-grain harvest residue quality such as crude protein (CP), acid detergent fiber (ADF), neutral detergent fiber (NDF), acid detergent lignin (ADL), net energy for maintenance (NEM), net energy for gain (NEG), net energy for lactation (NEL), total digestible nutrients (TDN), and relative feed value (RFV). Irrigation has a significant effect on CP, ADF, NDF, and TDN while PP affected only NDF. All the above parameters were significantly affected except NEM by the contrasting climate conditions, particularly during July through August coinciding with early crop reproductive stages and maturity. The RFV values ranged from 70.4 to 81.6 and this lower range was attributable to nutrient translocation to seeds and higher lignification during plant senescence towards the grain filling stage of the crop as good quality hay records over 120 RFV. These results indicate that both irrigation and weather during soybean seed development can alter post-grain harvest residue quality parameters, thereby playing critical roles in its RFV

Growing season variability in carbon dioxide exchange of irrigated and rainfed soybean in the southern United States

Measurement of carbon dynamics of soybean (Glycine max L.) ecosystems outside Corn Belt of the United States (U.S.) is lacking. This study examines the seasonal variability of net ecosystem CO2 exchange (NEE) and its components (gross primary production, GPP and ecosystem respiration, ER), and relevant controlling environmental factors between rainfed (El Reno, Oklahoma) and irrigated (Stoneville, Mississippi) soybean fields in the southern U.S. during the 2016 growing season. Grain yield was about 1.6 t ha−1 for rainfed soybean and 4.9 t ha−1 for irrigated soybean. The magnitudes of diurnal NEE (~2-weeks average) reached seasonal peak values of −23.18 and−34.78 μmol m−2 s−1 in rainfed and irrigated soybean, respectively, approximately two-months after planting (i.e., during peak growth). Similar thresholds of air temperature (Ta, slightly over 30 °C) and vapor pressure deficit (VPD, ~2.5 kPa) for NEE were observed at both sites. Daily (7-day average) NEE, GPP, and ER reached seasonal peak values of −4.55, 13.54, and 9.95 g C m−2 d−1 in rainfed soybean and −7.48, 18.13, and 14.93 g Cm−2 d−1 in irrigated soybean, respectively. The growing season (DOY 132–243) NEE, GPP, and ER totals were−54, 783, and 729 g C m−2, respectively, in rainfed soybean. Similarly, cumulative NEE, GPP, and ER totals for DOY 163–256 (flux measurementwas initiated on DOY 163, missing first 45 days after planting) were−291, 1239, and 948 g C m−2, respectively, in irrigated soybean. Rainfed soybean was a net carbon sink for only two months, while irrigated soybean appeared to be a net carbon sink for about three months. However, grain yield and the magnitudes and seasonal sums of CO2 fluxes for irrigated soybean in this study were comparable to those for soybean in the U.S. Corn Belt, but they were lower for rainfed soybean

Effects of Irrigation and Planting Geometry on Soybean (Glycine max L.) Seed Nutrition in Humid Climates

This study investigates the effect of irrigation (FI, all rows-irrigation; HI, alternate row irrigation; RF, rainfed) and planting geometry (PG) (SR, single-row; TR, twin-row) on soybean seed constituents. Results showed that most of these seed components were significantly affected by crop season due to contrasting precipitation and solar radiation patterns, particularly during July-August, coinciding with early reproductive and seed development stages. Both seed protein and oil levels responded positively to irrigation, while most of the amino acids were nonresponsive. The protein content ranged between 36.3 and 37.6% in 2018, while it was between 36.4 and 38.3% in 2019. Total seed oil content varied between 24.2 and 26.1% in 2018 and between 25.3 and 26.5% in 2019. Among amino acids, glycine, alanine, valine, and methionine levels were significantly higher in both FI and HI treatments. Among sugars, only sucrose was higher in response to the RF treatment, and irrigation did not affect both stachyose and raffinose. Oleic acid was higher in RF, while no significant differences were observed for linolenic and linoleic acids. Similarly, seasonal variation was significant for stearic acid content, but the 2019 season had relatively higher accumulation (stearic acid: between 4.1 and 4.5% in 2018 and from 4.6 to 4.9% in 2019). These results indicate that both irrigation and climate during seed development can alter some seed composition constituents and play critical roles in determining seed nutritional qualities

Open-Source Wireless Cloud-Connected Agricultural Sensor Network

Agricultural research involves study of the complex soil&#8315;plant&#8315;atmosphere&#8315;water system, and data relating to this system must be collected under often-harsh outdoor conditions in agricultural environments. Rapid advancements in electronic technologies in the last few decades, as well as more recent widespread proliferation and adoption of electronic sensing and communications, have created many options to address the needs of professional, as well as amateur, researchers. In this study, an agricultural research project was undertaken to collect data and examine the effects of different agronomic practices on yield, with the objectives being to develop a monitoring system to measure soil moisture and temperature conditions in field plots and to upload the data to an internet website. The developed system included sensor nodes consisting of sensors and electronic circuitry to read and transmit sensor data via radio and a cellular gateway to receive node data and forward the data to an internet website via cellular infrastructure. Microcontroller programs were written to control the nodes and gateway, and an internet website was configured to receive and display sensor data. The battery-powered sensor nodes cost $170 each, including electronic circuitry and sensors, and they were operated throughout the cropping season with little maintenance on a single set of batteries. The solar-powered gateway cost$163 to fabricate, plus an additional cost of $2 per month for cellular network access. Wireless and cellular data transmissions were reliable, successfully transferring 95% of sensor data to the internet website. Application of open-source hardware, wireless data transfer, and internet-based data access therefore offers many options and advantages for agricultural sensing and monitoring efforts

Eddy covariance assessment of alternate wetting and drying floodwater management on rice methane emissions

Reducing methane emissions and water use is critical for combating climate change and declining aquifers on food production. Reductions in irrigation water use and methane emissions are known benefits of practicing alternate wetting and drying (AWD) over continuous flooding (CF) water management in lowland rice (Oryza sativa L.) production systems. In a two-year (2020 and 2021) study, methane emissions from large farm-scale (∼50 ha) rice fields managed under CF and AWD in soils dominated by Sharkey clay (Sharkey clay, clay over loamy, montmorillonitic non-acid, thermic Vertic halauepet) were monitored using the eddy covariance method (EC). In the EC system, an open-path laser gas analyzer was used to monitor air methane gas density in the constant flux layer of the atmosphere over the rice-crop canopies. Total water pumped into the field for floodwater management was higher in CF compared to AWD by 24 and 14% in 2020 and 2021, respectively. Considerable variations between seasons in the amount of methane emitted from the CF and AWD treatments were observed: CF emitted 29 and 75 kg ha−1 and AWD emitted 14 and 34 kg ha−1 methane in 2020 and 2021, respectively. Notwithstanding, the extent of reduction in methane emissions due to AWD over CF was similar for each crop season (52% in 2020 and 55% in 2021). Rice grain yield harvested differed by only ±2% between AWD and CF. This investigation of large-scale system-level evaluation, using the EC method, confirmed that by practicing AWD floodwater management in rice, water pumped from aquifers could be reduced by about a quarter and methane emissions from rice fields could be cut down by about half without affecting grain yields, thereby promoting sustainable water management and greenhouse gas emission reduction during rice production in the Lower Mississippi Delta

Effect of continuous sugarcane bagasse-derived biochar application on rainfed cotton (Gossypium hirsutum L.) growth, yield and lint quality in the humid Mississippi delta

Abstract Optimizing soil health through soil amendments is a promising strategy for enhancing rainwater efficiency for stabilizing crop production. Biochar, obtained by torrefaction of sugarcane bagasse, a byproduct from sugar mills, has a high potential for its use as a soil amendment, which can boost crop yields, but needs further field trials for its adoption in farming systems. A field study was conducted during 2019–2021 at Stoneville, Mississippi, to assess rainfed cotton (Gossypium hirsutum L.) production under four biochar levels (0, 10, 20, and 40 t ha−1) on Dundee silt loam soil. The effects of biochar on cotton growth and lint yield and quality were examined. Biochar levels had no significant impact on cotton lint and seed yield for the first two years. Still, in the third year, a significant increase in lint yield by 13 and 21.7% was recorded at 20 and 40 t ha−1 biochar levels, respectively. In the third year, lint yields were 1523, 1586, 1721, and 1854 kg ha−1 at 0, 10, 20 and 40 t ha−1 biochar levels, respectively. Similarly, cotton seed yield increased by 10.8% and 13.4% in 20 and 40 t ha−1 biochar plots. This study demonstrated that successive biochar applications at 20 or 40 t ha−1 can enhance cotton lint and seed yields under rainfed conditions. These improved yields with biochar did not produce increased net returns due to the increased production costs. Many lint quality parameters were unaffected except for micronaire, fiber strength and fiber length. However, potential long-term benefits of enhanced cotton production from biochar application beyond the length of the study merit further investigation. Additionally, biochar application is more relevant when accrued carbon credits through carbon sequestration outweigh the increased production costs due to biochar application