Irrigated Soybean Research Articles

Irrigation of soybean under environments of Prialeyskaya steppe

Soybean is one of the most important agricultural crops, which although in general very unpretentious, but under the environments of the Altai Territory (Prialeyskaya steppe) it is almost impossible to obtain consistently high yields due to unfavorable climatic conditions. The main factor in obtaining consistently high yields and involving additional areas for soybean crop in this climatic zone is the use of complex agrotechnical techniques, namely regular irrigation. The purpose of the work was to develop an optimal mode of soybean irrigation under the environments of the Prialeyskaya steppe in the Altai Territory. The possibility of effective soybean cultivation on the irrigated lands of the arid Prialeyskaya steppe in the Altai Territory has been theoretically substantiated and experimentally confirmed in the paper. The regularities of the influence of different irrigation regimes on soybean productivity have been established. The specific water consumption per unit of marketable output has been determined depending on the irrigation regime. The relations of grain yield with the change of irrigation regime have been established. The maximum yield of soybean grain has been obtained in the 80% LMC variant (the lowest moisture capacity), which was 3,3 t/ha in 2016. The average yield for 3 years of research was 3,1 t/ha and exceeded the yield on the control variant by 2,1 t/ha. In the 80% LMC variant but with the treatment of soybean seeds before sowing with an inoculant the average yield was 3,5 t/ha, which exceeded the yield in the control variant by 2,5 t/ha. Also in the 80% LMC variant and with inoculant seed treatment the yield of soybean grain exceeded the yield in the non-treated variant by 0,4 t/ha. Thus, it has been established that to obtain the maximum yield of soybean under the environments of the Prialeyskaya steppe should support the level of pre-irrigation soil moisture at 80% LMC.

Optimum dosage of rice husk-based silicon foliar spray to improve yield of soybean grown on irrigated lowland

Silicon (Si) is highly abundant in soil and plays important role in growth and development of plant. However, number of available Si is limited depend on soil type and condition, thus supplementary Si from fertilizer is needed. Rice husk is one of potential source of Si fertilizer. This study aimed to determine the optimum dosage of rice husk-based bio-silicon foliar spray (SiF) improve yield of soybean. The experiment was laid out in a randomized block design at Narmada Research Station of AIAT (Assessment Institute for Agricultural Technology) of West Nusa Tengara Province from May to June 2018. There were four treatments of SiF concentration with four replications viz. SiF1 = 3 ml/lt, SiF2 = 6 ml/lt, SiF3 = 9 ml/lt, and SiF0 = 0 ml/lt (control). The results showed that plant growth and yield attribute i.e., weight of biomass, number of pods, fresh pod weight, yield were improved on all SiF treatments when compared to the control. Total ground above biomas m−2 was also significantly improved, while the highest yield produced at SiF3. Current study suggests that optimum dosage of rice husk-based bio-silica foliar spray for lowland irrigated soybean was 6 ml/lt, and further on-farm experiment is needed to test the dosage at wider scale.

Estimation of soybean yield from machine learning techniques and multispectral RPAS imagery

Throughout the plant development, the physiological processes of growth, as well as the handling of water and fertilizers represent sources of variation in the spectral response of the crops. Thus, in the context of precision agriculture, information on the phenological stage of cultivation can be decisive in accurately estimating agronomic variables through the use of aerial images obtained by RPAS (Remotely Piloted Aircraft System) platforms. Therefore, the aim of this study was: i) to investigate the potential of using RPAS embedded with multispectral sensors in order to obtain data on a soybean irrigated field with a central pivot system ii) to identify the best stage of development of irrigated soybean in order to obtain multispectral images aiming to the yield prediction; iii) to test different vegetation indices (VIs) for estimating the yield of soybean crop using artificial neural networks. The treatments were established using different metric water potentials in the soil and the analysis was comprised by 30 sample units. Multispectral images were acquired through a Sequoia® camera aboard the Phantom 4® Pro platform, during seven phenological crop stages. In addition to the spectral bands, nine VIs were taken as predictors based on the response variables derived from the site survey. The selection of the best growth stage was based on the highest level of association, represented by the Spearman correlation coefficient between predictors and each response variable. The Multi-Layer Perceptron (MLP) algorithm was used to adjust the predictive model, whose performance was assessed in terms of training and testing. To have independent measurements of the performance of the proposed algorithm was used by k-fold cross-validation. The results obtained from the correlation between the image-derived data and the soybean yield indicate that the ideal monitoring window for irrigated soybean can be found at the end of the vegetative stage (V6). The selection of the phenological crop stage had a positive impact on the predictions. The MLP models showed a good adjustment and good generalization capability. In turn, grain yield was the most complex agronomic parameter for modeling, with correlations of 0.70 and 0.92 for training/testing, and excellent results in other statistical tests, reinforce the great combining capacity between remote sensing via RPAS and machine learning (ML) in applications aimed at precision agriculture. This approach offers a useful tool for evaluating grain yield in center-pivot-irrigated soybean crops and emphasizes the need of observation regarding the phenological crop stage as a factor of analysis in the prediction of grain yield via remote sensing.

The economic value of water in crop productions and policy implications in southern Brazil

Promoting economically efficient solutions to meet competing demands for water under uncertain and variable supplies requires knowledge about the economic value of water and costs for its scarcity. In this work, an agricultural production optimisation model was used to evaluate the marginal value of water (MVW) in an agricultural region of rice and soybean growing in southern Brazil. The results indicate a MVW of 0.02–0.09 R$/m3 (1 R$ = £0.14), which is higher than common values considered for water charges for agricultural uses in Brazilian watersheds. The total scarcity costs of two recent drought periods were also investigated – these were approximately R$138 million (£19 million) and accounted for up to 15.5% of irrigated rice and soybean agriculture net return in some of the studied regions. Finally, the potential for cropping mix changes for some regions was explored through short-term water reallocation programmes to mitigate drought impacts. The results of this work should be useful in the design of water policies in terms of improved economic water management instruments, key infrastructure investments to be prioritised by watershed plans, strategies to integrate with other sectoral policies to secure funding for new water infrastructure and strategies to reinforce local adaptation through crop mix changes and short-term water reallocation.

Integrated energy-water-land nexus planning to guide national policy: an example from Uruguay

Despite broad consensus on the benefits of a nexus approach to multi-sector planning, actual implementation in government and other decision-making institutions is still rare. This study presents an approach to conducting integrated energy-water-land (EWL) planning, using Uruguay as an example. This stakeholder-driven study focuses on assessing the EWL nexus implications of actual planned policies aimed at strengthening three of Uruguay’s key exports (beef, soy, and rice), which account for more than 40% of total national export revenue. Five scenarios are analyzed in the study: a reference scenario, a climate impacts scenario, and three policy scenarios. The three policy scenarios include measures such as increasing the intensity of beef production while simultaneously decreasing emissions, increasing irrigated soybean production, and improving rice yields. This study supplements previous sector-specific planning efforts in Uruguay by conducting the first stakeholder-driven integrated multi-sector assessment of planned policies in Uruguay using a suite of integrated modeling tools. Key insights from the study are: as compared to a reference scenario, improving beef productivity could lead to cropland expansion (+30%) and significant indirect increases in water requirements (+20%); improving rice yields could lead to increases in total emissions (+3%), which may partially offset emissions reductions from other policies; expanding irrigated soy could have the least EWL impacts amongst the policies studied; and climate-driven changes could have significantly less impact on EWL systems as compared to human actions. The generalizable insights derived from this analysis are readily applicable to other countries facing similar multi-sector planning challenges. In particular, the study’s results reinforce the fact that policies often have multi-sector consequences, and thus policies can impact one another’s efficacy. Thus, policy design and implementation can benefit from coordination across sectors and decision-making institutions.

Irrigated soybean response to granular fertilizer potassium application timing

AbstractAmelioration of K deficiency during the growing season requires knowledge of critical tissue concentrations and crop yield response to fertilization time. Our objectives were to characterize the yield and uptake responses of K‐deficient irrigated soybean [Glycine max (L.) Merr.] to in‐season fertilizer‐K application time and rate, evaluate fertilizer‐potassium‐recovery efficiency (FKRE), and evaluate how leaflet‐K concentration responds to K‐fertilization time. Six trials were established on silt loam soils. Muriate of potash was applied pre‐plant and compared to an equivalent K rate applied post‐emergence on six or seven dates. Grain yield, trifoliolate‐K concentration, and K uptake were measured. Relative soybean yields were regressed across days after planting (DAP) for two situations of K‐responsive soybean: season‐long K‐deficiency symptoms or few symptoms (hidden hunger). The maximum yield increases from K fertilization ranged from 524 to 1948 kg ha−1 among trials producing relative yields that were 59−90% of the maximum yield produced with the greatest pre‐plant‐applied K rate. A linear‐plateau model showed maximal yields of soybean with hidden hunger could be produced with in‐season fertilizer K applied as late as 83 DAP or 44 d after R1 stage (DAR1). For soybean experiencing season‐long K deficiency, K fertilization from pre‐plant until 60 DAP or about 20 DAR1 produced similar relative yields. The FKRE of pre‐plant‐applied fertilizer K ranged from 36 to 75% among trials. Regardless of the severity of K deficiency, fertilizer K applied post‐emergence into the R2 development stage was taken up efficiently and produced similar yields as equal pre‐plant‐applied K rates.

Impact and Control of Powdery Mildew on Irrigated Soybean Varieties Grown in Southeast Australia

Powdery mildew—caused by the fungus Erisyphe diffusa (syn. Microsphaera diffusa)—was first observed in commercial soybean crops in southern New South Wales (NSW), Australia, in 2011. Its detection raised concerns that soybean production might be constrained if the severity of the disease reached the levels observed in northern Australia. Field experiments were conducted over four consecutive seasons to examine the response of three soybean cultivars—Djakal, SnowyA and the breeding line N005A-80—to two fungicides and two fungicide application regimes. The cultivar Djakal was identified as having a high level of resistance to powdery mildew. The severity of infection symptoms varied between seasons. The most severe symptoms were observed during the 2014–2015 season which resulted in the largest grain yield reduction of 20% for the cultivar SnowyA. All fungicide treatments provided a significant reduction in the severity of symptoms, with the split application of tebuconazole and both the single and split applications of tebuconazole + prothioconazole providing the most effective control of the disease. Few other grain yield effects were found, even when strong disease control was achieved. This was a suspected result of the consistent late-in-the-season onset of the disease. Few differences were observed among the treatments in terms of lodging severity, date of physiological maturity, or grain oil and protein concentrations. It was concluded that both fungicides provided effective control of powdery mildew. However, when disease pressure is low, application might not be warranted in southern NSW.

Levantamento de plantas daninhas em lavoura de soja irrigado com pivô em Cachoeira do Sul - RS

The presence of weed species in soybean crops is a concern for farmers. Knowing these species is of great importance, as they cause serious damage to crops due to competition for nutrients, water, light and physical space with soy. This work aimed to survey weeds in pivot irrigated soybean crops in Cachoeira do Sul municipality, Capané district, in the experimental area of the Rio Grandense do Arroz Institute (IRGA). The evaluations were performed by applying the 0.25 m2 square method, launched at random sixty times. Weeds in the sampled areas were removed from the soil, species identified and quantified. Evaluations were performed after three applications of glyphosate herbicide. Even after glyphosate applications, seven species were identified, representing the families Asteraceae, Poaceae, Malvaceae, Euphorbiaceae and Rubiaceae. This survey enables the planning of preventive strategies for the sustainable control of weeds in the field, reducing production costs and the impact on the environment.

Developing sensor‐based irrigation scheduling that maximizes soybean grain yield, irrigation water use efficiency, and returns above irrigation costs

AbstractAgricultural withdrawal from the Mississippi River Valley Alluvial aquifer (MRVAA) exceeds its recharge rate, causing groundwater declines and cones of depression across the midsouthern United States. This research was conducted to determine whether sensor‐based irrigation scheduling of soybean [Glycine max (L.) Merr.] could improve yield and profitability while minimizing consumptive water use. The effects of season‐long soil water potential (SWP) threshold (−50 and −85 centibar [cbar]) on consumptive water use and on agronomic and economic parameters were compared with scheduling irrigations as a function of growth stage (VN–R2, R3–R4, and R5–R6.5) and SWP threshold (−50, −85, and −125 cbar) on a Dundee silty clay loam (fine‐silty, mixed, active, thermic Typic Endoaqualfs) near Stoneville, MS, from 2015 through 2017. Decreasing the season‐long SWP threshold for soybean from −50 to −85 cbar reduced consumptive water use 49% while having no adverse effect on yield, returns above irrigation costs, or irrigation water use efficiency (IWUE). Adjusting the irrigation threshold as a function of growth stage did not improve yield or returns above irrigation costs. Our data indicate that maintaining a season‐long irrigation threshold of −85 cbars optimizes yield, returns above irrigation costs, and IWUE efficiency while reducing withdrawal for soybean irrigation from the MRVAA up to 49% relative to the −50 cbar producer standard.

Decision-Making of Irrigation Scheme for Soybeans in the Huaibei Plain Based on Grey Entropy Weight and Grey Relation–Projection Pursuit

To provide a scientific reference for formulating an effective soybean irrigation schedule in the Huaibei Plain, potted water deficit experiments with nine alternative irrigation schemes during the 2015 and 2016 seasons were conducted. An irrigation scheme decision-making index system was established from the aspects of crop water consumption, crop growth process and crop water use efficiency. Moreover, a grey entropy weight method and a grey relation–projection pursuit model were proposed to calculate the weight of each decision-making index. Then, nine alternative schemes were sorted according to the comprehensive grey relation degree of each scheme in the two seasons. The results showed that, when using the entropy weight method or projection pursuit model to determine index weight, it was more direct and effective to obtain the corresponding entropy value or projection eigenvalue according to the sequence of the actual study object. The decision-making results from the perspective of actual soybean growth responses at each stage for various irrigation schemes were mostly consistent in 2015 and 2016. Specifically, for an integrated target of lower water consumption and stable biomass yields, the scheme with moderate-deficit irrigation at the soybean branching stage or seedling stage and adequate irrigation at the flowering-podding and seed filling stages is relatively optimal.

Comparative study of different soybean genotypes in irrigation technology

In many places in Hungary, early maturity soybean can be successfully grown. The earlier maturity group of soy which ripened in 110–125 days in most crop areas in Hungary. However, to achieve excellent results, the selection of proper varieties is important too. Successful cultivation is largely dependent on the macro and microclimate of the production area, the nutrient supply of the soil and the cultivation technology. Soybean can be produced in places where the amount of precipitation is right, as the lack of water results in lower yields and deteriorated oil and protein concentrations. In the following study, 2 years (2016 and 2017) are compared to the yield, protein and oil content of the soybeans of the early maturation group in irrigated and non-irrigated treatments. Based on our experiment, it can be stated that, during the irrigation of soybean, oil and protein content and yields did not always change.

A Comparative Life Cycle Assessment of Crop Systems Irrigated with the Groundwater and Reclaimed Water in Northern China

Using reclaimed water from treated wastewater as an irrigation source is gaining popularity in arid and semi-arid areas. However, life cycle assessment studies, utilizing experimental data to analyze the environmental and health impacts of crops irrigated with reclaimed water, are lacking. This study presents the first comparative life cycle assessment of corn, soybean and wheat systems irrigated with groundwater and reclaimed water in Northern China. While the life cycle foreground inventory was based on a combination of experimental and modeling datasets, the life cycle background inventory was compiled with commercially available data packages augmented with Chinese electricity mix data. The life cycle impact analyses were based on the characterization factors from state-of-art life cycle impact assessment models. The analyses indicated that the life cycle global warming impacts of the crop systems ranged from 0.37 to 0.64 kg CO2-eq/kg grain, with reclaimed water irrigated soybean and ground water irrigated wheat exhibiting, respectively, the lowest and highest global warming impacts. Irrigation, farming equipment operation, on-field emissions and fertilizer production ranked as top contributors to the life cycle impacts for corn, soybean, and wheat. The comparative analyses of irrigation sources suggested that significant environmental tradeoffs existed. Replacing groundwater with reclaimed water as the irrigation source significantly decreased life cycle global warming, acidification, ozone depletion, smog formation, and respiratory impacts of corn, soybean and wheat systems. However, replacing groundwater with reclaimed water increased the life cycle noncancer impacts of those systems. Coordinating policies within the water–food–health nexus is required, in order to minimize the environmental tradeoffs, while maximizing the benefits of irrigation with reclaimed water.

Validation of Soil‐Test‐Based Phosphorus and Potassium Fertilizer Recommendations for Irrigated Soybean

Core Ideas The most common soil‐test‐based fertilization recommendation error is a false positive. Surface soil sample P and K concentrations are qualitative indicators of subsoil P and K concentrations. The R2‐stage, leaflet‐K concentration of irrigated soybean is an accurate indicator of yield responsiveness to K fertilization. Soil testing is the best available technology for making crop fertilizer recommendations, and precision agriculture has increased the demand for soil‐testing. Our primary research objectives were to validate the accuracy of soil‐test P (STP) and K (STK) availability (Mehlich‐3) and trifoliolate leaflet‐P and leaflet‐K concentration interpretations for predicting irrigated‐soybean [Glycine max (L.) Merr.] yield response to P and K fertilization at 22 site‐years. Each trial contained six treatments involving two P rates and four K rates including a no fertilizer‐P or ‐K control and the soil‐test recommendation. Yield and tissue nutrient concentration responses were assessed at three significance levels (p ≤ 0.05, p ≤ 0.10, or p ≤ 0.25) and identified as correct or incorrect according to the response predicted by soil‐test recommendations. The accuracy of soil and tissue analyses to predict the correct plant response to fertilization increased as the significance level moved from conservative (p ≤ 0.05) to liberal (p ≤ 0.25). Mehlich‐3 STP accurately identified soils that did not respond to fertilizer P and had an overall accuracy of 40 (p ≤ 0.05) to 48% (p ≤ 0.25) in predicting yield response to fertilization. Existing STK interpretations were 72 (p ≤ 0.05) to 82% (p ≤ 0.25) accurate. Critical leaflet‐K concentrations accurately identified soybean response to K fertilization at 46 (p ≤ 0.05) to 60% (p ≤ 0.25) of the sites. Interpretation errors were most common in the very low and low STP levels, low and medium STK levels, and the low tissue‐K level. The accuracy of the soil and tissue testing and their interpretation process were reasonably accurate for K but substantial improvements are needed for P.

Soybean irrigation requirements and canopy-atmosphere coupling in Southern Brazil

The lack of base information on crop water requirements under tropical conditions is one of the causes for inefficient water use and inadequate irrigation management. The crop coefficient (Kc) approach is universally adopted for scheduling and quantifying the water management and, recently, its relation with the evaporative atmosphere demand has been included in this approach to improve the decision-making on irrigation management. In this paper, we measured crop evapotranspiration (ETc) in two experiments as evaporative heat flux from a centre pivot-irrigated soybean plantations in tropical Brazil to quantify the crop water needs. Irrigation requirements were determined by comparing ETc with reference evapotranspiration (ETo), derived from FAO-56 (Allen et al., 1998). In this study, the average Kc value obtained was 0.92, which is nearly 20% lower than those recommended by the FAO-56 (Allen et al., 1998) and varied inversely as a function of ETo. Based on aerodynamic and leaf diffusive resistance (rs) data, Ω was computed and presented values relatively high compared to other crops, which means a relatively poor coupling of soybean canopies to the atmosphere. Throughout both experiments, the Kc value decreased by up to 44.8% when the ETo increased from 2 to 4 mm d−1, depending on the phenological phase, indicating the need for taking into account the ETo values when selection the Kc values for improving the irrigation management in tropical soybean.

Soybean Irrigation Initiation in Mississippi: Yield, Soil Moisture, and Economic Response

Abstract. Irrigated acreage is expanding and groundwater supplies are decreasing in the Mississippi Delta. Efficient irrigation scheduling of soybean [ (L.) Merr] will aid in conservation efforts to sustain groundwater resources. The objective of this study was to develop irrigation initiation recommendations for soybean grown on Mississippi Delta soils. Field studies were conducted on a deep silty clay (SiC) in 2012, 2013, 2014, and 2015 and on a deep silty clay loam (SiCL) and deep silt loam (SiL) or loam (L) soil in 2013, 2014, and 2015. Irrigation was initiated multiple times during the growing season and soybean yield and net return were determined to evaluate the effectiveness of each initiation timing. Growth stage, soil water potential (SWP), and soil water deficit (SWD) were compared at these initiation timings to determine which parameter or combination of parameters consistently predicted the resulting greatest yields and net returns. Stress conditions that reduce yield can occur at any time from late vegetative stages to full seed on these deep soils. The wide range of trigger values found for SWP and SWD to increase yields in different years emphasizes the complexity of irrigation scheduling. Monitoring soil moisture by itself or use of a single trigger value is not sufficient to optimize irrigation scheduling to maximize soybean yield with the least amount of water every year on these soils. Monitoring one or more parameters (e.g., leaf water potential, canopy temperature, air temperature, humidity, solar radiation, and wind) is needed in conjunction with soil moisture to directly or indirectly quantify the abiotic stresses on the plant to better define when a yield reducing stress is occurring. Keywords: Irrigation initiation, Irrigation scheduling, Soil water deficit, Soil water potential, Soybean, Water conservation.

Биологическая активность орошаемой лугово-черноземной почвы и продуктивность сои в зависимости от условий минерального питания в южной лесостепи Западной Сибири

Биологическая активность орошаемой лугово-черноземной почвы и продуктивность сои в зависимости от условий минерального питания в южной лесостепи Западной Сибири

Genotypic differences in yield loss of irrigated soybean attributable to charcoal rot

ABSTRACT Charcoal rot, caused by the fungus Macrophomina phaseolina (Tassi) Goid., is a disease of soybean (Glycine max (L.) Merr.) that causes yield loss worldwide. The purpose of this research was to determine the effects of charcoal rot on the yield loss of six individual soybean genotypes grown in infested, irrigated plots. Overall, colony-forming unit (CFU) levels were low (≤5,500). Even so, regression analysis indicated a significant (P ≤ 0.05) negative linear relationship of CFUs with seed yield for one genotype in two out of 3 years (2011, r 2 = 0.43, P = 0.0403; 2013, r 2 = 0.71, P = 0.0023) at levels of CFUs that ranged from zero to 1,300. At low CFU levels, none of the other five genotypes showed a significant (P ≤ 0.05) linear relationship. Hence, not all genotypes that were colonized by M. phaseolina lost seed yield. These results indicated that yield loss was dependent on both genotype and environment.

A lack of response of irrigated soybean (Glycine max L. Merr.) in rotation with cotton (Gossypium hirsutum L.) in the Mississippi Delta, USA

The effects of cotton (Gossypium hirsutum L.): soybean [Glycine max (L.) Merr.] rotations on the respective crops are limited. This manuscript discusses the response of irrigated soybean in crop rotation with cotton. An irrigated soybean: cotton rotation experiment was conducted from the year 2012 through 2015 near Elizabeth, MS. The crop rotation sequences were included continuous soybean (SSSS), continuous cotton (CCCC), cotton followed by soybean (SCSC), soybean followed by cotton (CSCS), soybean followed by two year of cotton (SCCS), and cotton followed by two year of soybean (CSSC). The rotations were grown under two production systems conventional and transgenetic with respect to weed control. During this study, a weed control treatment of (pendimethalin pre-emergence vs. glyphosate post-emergence) as included on the soybean plots was used. The soybean yields across rotations within a year were not significantly different. The means yields differed among years (3655.1, 3023.6, 3500.6 and 2600.3 Kg ha-1 for the year 2012, 2013, 2014 and 2015, respectively) and appear related to difference in rainfall/irrigation amounts. The results revealed that the weights of 100 seed samples averaged 13.9g in the year 2015 which differed from the previous years (16.2, 15.6, and 16.2g; 2012, 2013 and 2014, respectively). Therefore, the rotations of cotton with soybean appear to have neither a beneficial or negative effect on soybean yield.

Quantifying soybean evapotranspiration using an eddy covariance approach

Quantification of evapotranspiration (ETc) from crops is critical in irrigation scheduling in agriculture. In a pioneering study, in the Mississippi (MS) Delta region, we quantified ETc from soybean (Glycine max L.) using the eddy covariance (EC) approach (ETe). We also monitored ETc using a residual energy balance (EB) approach (ETb) and compared the fluxes. The unclosed energy fluxes in the EC were post-analysis closed using the Bowen ratio (BR) and latent heat (LH) methods. The measurements were conducted in a 35-ha clay soil planted to irrigated soybean in the lower MS Delta in 2016. The crop reached physiological maturity in 126 days after emergence (DAE). Maximum LAI was 5.7 and average grain yield was 4900 kg ha−1. The EC showed an energy balance closure of about 88% on a 30 min and 90% on a daily flux accumulation. The ETe was 18.2, 6.8, and 15.9% lower than ETb, and ETe corrected using BR (ETebr) and LH (ETele) approaches, respectively. Average soybean seasonal ETe, ETb, ETebr, and ETele were 422, 499, 451, and 490 mm, respectively. Seasonal reference-crop evapotranspiration for alfalfa (ETo) and grass (ETr) were 470 and 547 mm, respectively. Daily ETe, ETb, ETebr, ETele, ETo, and ETr averaged across the whole season were 4.4, 5.2, 4.7, 5.1, 4.9, and 5.7 mm, respectively. For scheduling irrigations, based on grass and alfalfa reference crop ET calculated from weather data, averages of the ETe, ETb, ETebr, and ETele daily estimates were used in deriving crop coefficients (Kc). The Kc for grass reference varied between 0.56 and 1.29 and for alfalfa reference varied between 0.56 and 1.02. The information developed will be useful for scheduling irrigations in the MS Delta region, and the methodology developed can be adapted for generating similar information elsewhere.

Effects of Rotation of Cotton (Gossypium Hirsutum L.) and Soybean [Glycine Max (l.) Merr.] Crops on Soil Fertility in Elizabeth, Mississippi, USA

The effects of cotton (Gossypium hirsutum L.): soybean [Glycine max (L.) Merr.] rotation on the soil fertility levels are limited. An irrigated soybean: cotton rotation experiment was conducted from 2012 through 2015 near Elizabeth, Mississippi, USA. The crop rotation sequences were included continuous cotton (CCCC), continuous soybean (SSSS), cotton-soybean-cotton-soybean (CSCS), cotton-soybean-soybean-cotton (CSSC), soybean-cotton-cotton-soybean (SCCS), soybean-cotton-soybean-cotton (SCSC). The crop rotation sequences were followed continuous soybean, continuous cotton, cotton followed by soybean, soybean followed by cotton, soybean followed by two years of cotton, and cotton followed by two years of soybean. A weed control treatment of a non-glyphosate post-emergence vs. glyphosate post emergence was used in both crops. Soil samples taken prior to planting each year and in 2016 showed no differences in cation exchange capacity, organic matter, pH, or macro nutrient levels among the rotations, over the five sampling periods nor weed control methods used for either crop.