ECOPHYSIOLOGY OF SOYBEAN YIELD AND WATER USE EFFICIENCY-EXPERIMENTAL AND MODELING APPROACHES

• Sponsoring Institution: National Institute of Food and Agriculture
• Project Status: COMPLETE
• Funding Source: HATCH
• Reporting Frequency: Annual
• Accession No.: 1011780
• Project Start Date: Jan 3, 2017
• Project End Date: Jan 2, 2022
• Program Code: [(N/A)]- (N/A)

Recipient Organization
UNIVERSITY OF KENTUCKY
500 S LIMESTONE 109 KINKEAD HALL
LEXINGTON,KY 40526-0001

Performing Department
Plant and Soil Sciences

Non Technical Summary
Crop management transformations that can increase average yields are essential in order to meet an increasing food demand. The yield gap between potential and attainable yields in some of the agricultural areas in the US could be greatly narrowed with the aid of irrigation during periods of insufficient water supply. However, depletion of aquifers is a critical issue for the sustainable access to irrigation water for agriculture. For regions in Kentucky and nearby states with large acreage potentially transformed to irrigation, a preemptive approach in the evaluation of the yield potential of main grain crops as well their irrigation requirements is essential for the development of these agricultural areas.The goal of this research is to investigate the yield response and the water use efficiency (WUE) of soybean grown under a wide range of management options for both irrigated and rainfed conditions in Kentucky.The use of mechanisticcrop simulation models that describe complexgenotype x management x environment interactionscan allow to study crop responses acrossdifferent environments, soil types, and future weather scenarios. This approachcan save time and money invested in field trials, reduce the number of treatments tested, and aid in the design of future experiments to test management options with high scope of increasing yield and/or water productivity. Preliminary crop models simulations were conducted that indicate a high potential to modify yield pontential and water use efficiency with management of planting date and maturity choices in soybean. In this project, field trials will be carried out attwo contrasting locaitons in KYcomprising the range of management options in the area. Data from field expeiriments will be used to understand the ecophysiological basis underlying the observed yield responses, and will allow to calibrate and test acrop model. Thereafter, the model will be used to study management options that maximize yield potential and water use efficiency for different locations in the research area, and for long term weather data and future weather scenarios.

Animal Health Component

60%

Research Effort Categories

Basic

40%

Applied

60%

Developmental

(N/A)

Classification

Knowledge Area (KA)	Subject of Investigation (SOI)	Field of Science (FOS)	Percent
102	1820	1020	50%
111	1820	3100	50%

Knowledge Area
102 - Soil, Plant, Water, Nutrient Relationships; 111 - Conservation and Efficient Use of Water;

Subject Of Investigation
1820 - Soybean;

Field Of Science
1020 - Physiology; 3100 - Management;

Keywords

soybean

water use effiency

planting date

crop model

Goals / Objectives
Crop management transformations that can increase average yields are essential in order to meet an increasing food demand. The yield gap between potential and attainable yields in some of the agricultural areas in the US could be greatly narrowed with the aid of irrigation during periods of insufficient water supply. For regions in Kentucky and nearby states with large acreage potentially transformed to irrigation, a preemptive approach in the evaluation of the yield potential of main grain crops as well their irrigation requirements is essential for the development of these agricultural areas with a sustainable use of water.The general goal of this research is to investigate the interaction of soybean maturity group (MG) and environment on development, grain yield, and water use efficiency (WUE) of soybean cropping systems in Kentucky. The specific objectives of this research are:Estimate soybean yield potential without water limitations for different MG cultivars and planting dates with the aid of experimental studies and crop simulation models.Study the effect of environmental conditions on mechanistic processes underlying biomass production and yield.Investigate grain yield productivity and water use efficiency (WUE) of complex genotype x management x environment interactions with long term crop simulations.

Project Methods
OBJECTIVE A: Estimate soybean yield potential under no water limitations for different MG cultivars and planting dates with the aid of experimental studies and crop simulation models.Field experiments under irrigated conditions including a range of MG cultivars and planting dates will be conducted at Lexington, KY and at Princeton, KY during 2017 to 2019. Further locations in Kentucky and in southern latitudes will be included pending further funding. Nutrient and pest and disease management will be optimized to bring yields close to the potential yield for each environment. The experimental design will be a split-split-plot with four replications. The main splitting factor will be planting date, the second will be irrigation management (rainfed vs. irrigated), and the third will be the soybean MG (MG 2, 3, 4 or 5). At both locations there will be four planting dates ranging from mid-April to mid-July. Three soybean cultivars will be randomized within each MG, making a total of 12 soybean cultivars. Plots will consist of 6 rows with a 15 inch spacing and 20 feet long. A preliminary field layout of the experimental design is shown in Figure 4. Irrigation will be applied according to the crop evapotranspiration demand and allowing a 30 mm water deficit. Irrigation will be supplied with a drip tape irrigation system that will be disconnected for each MG and planting date soon before physiological maturity (R7). A flow meter will be installed in the main pipe to estimate the total irrigation water applied.Data collected across 3-yr of field trials in this study will be used to evaluate the accuracy of DSSAT-CROPGRO (Booteet al., 1998; Hoogenboomet al., 2012; Joneset al., 2003) for predicting soybean main developmental stages and yield potential under no water limitations in Kentucky with previously calibrated genetic coefficients across environments in the Midsouth (Salmerón and Purcell, 2016; Salmerón et al, 2016b).OBJECTIVE B: Study the effect of environmental conditions on mechanistic processes underlying biomass production and yield.The range of planting dates and soybean MG cultivars in this project will provide different conditions of temperature and solar radiation under field conditions during critical developmental stages in soybean. At harvest, final seed mass, seed number, and harvest index will be estimated from each plot. A closer monitoring of yield physiological traits will be conducted in the experimental trial conducted at Lexington, KY for the irrigated treatments, and to a lesser extent in the experiment that will conducted at Princeton and for rainfed treatments. Destructive samplings during the growing season will include: crop growth rate estimated from R1 to R5 growth stages, seed growth rate with 3-4 samplings during the linear phase of seed growth, and length of the effective seedfill period. Additionally, in vitro cotyledon growth rate will be measured after growing cotyledons for eight days in a solution with high sucrose concentration (Egli et al., 2001; Pipolo et al., 2004). Finally, cotyledon cell count will be estimated in mature seeds following a modification of the procedure by Egli et al (2001). Physiological traits that can be measured at the end of the growing season in harvested seed, such as cell number in mature seeds, will be tested aspotential variables that can improve optimization of cultivar coefficientsacross a wide range of environments.OBJECTIVE C: Investigate grain yield productivity and water use efficiency (WUE) of complex genotype x management x environment interactions with long term crop simulations.Crop model simulations will be used to study soybean yield and water use responses across different environments, soil types, and future weather scenarios.Parametrization of soil properties for different soil types in Kentucky will be done based on soil texture and pedotransfer functions that estimate soil properties (Saxton et al., 1986; Wösten, 1997).A sensitivity analysis with modification of soil water parameters and different approaches in the estimation of crop evapotranspiration will be conducted to test the applicability of DSSAT-CROPGRO to reproduce soil water content and soybean yields for irrigated and water-limited (rainfed) conditions with general soil textural class information. The use of long term simulations with historical weather data or with future weather scenarios will be used to identify management strategies with a higher probability of maximizing productivity and water use efficiency across locations and soils in Kentucky.

Progress 10/01/19 to 09/30/20

Outputs
Target Audience:Target audiences of this project include grain crop producers in Kentucky and neighboring producing states (Midwest and Upper Midsouth producers), the scientific community, and graduate and undergraduate students. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?Training activities: This project has provided support to provide mentorship form the PI to a postdoctoral scholar, and a graduate student. The project also provided funds for 2 undergraduate students working part time that gained hands-on research experience. Professional development - attendance to conferences and meetings: The PI participated in research conferences presenting 1 oral presentation and 4 posters that contribute to the goals in this project. How have the results been disseminated to communities of interest?Results were diseminated with the research community through 4 presentations at reserach conferences, and through a peer-reviewed publication. What do you plan to do during the next reporting period to accomplish the goals?During the last year of this project, activities and outcomes from Goal 2 and 3 will be finalyzed. This will involve finalizing analysis of model calibration and application data (Goal 3), and data collected from trials in Goal 2. Results from this research will be shared with producers and the research community.

Impacts
What was accomplished under these goals? Impact statement: Crop management transformations that can increase yields in grain crops are essential to meet an increasing food demand with a sustainable use of agricultural land and resources. Management factors (e.g. planting date, irrigation, cover cropping, crop rotations, and choice of cultivar maturity) can affect the use of resources (water, nutrient, solar radiation), and influence the impact of grain crops at a system's level. Evaluating these interactions with the aid of field trials alone is challenging due to a limitation on the number of trials and field measurements we can conduct. In addition, there is variability in environmental conditions from one year to another, and crop models can be used to investigate management options that are more beneficial for a given climate. This project combined field trials with simulations from a process-based eco-physiological model to study management recommendations that can help US grain crop producers achieve high productivity. This research is necessary to provide best management recommendations for producers, but also to quantify environmental impact, and for informed policy making. However, correct simulations from models are essential before models can be used. Thus, this project is also focused in collection of data for model calibration, model evaluation, and model improvement. Model evaluation and improvement is addressed through multi-model evaluation of soybean models, and also through hypotheses-based research investigating physiological processes involved in yield determination and their interaction with environmental conditions to improve the description of these processes in eco-physiological models. Goal 1: Estimate soybean yield potential without water limitations for different MG cultivars and planting dates with the aid of experimental studies and crop simulation models. Field trials were conducted in 2020 in Lexington under irrigated and rainfed conditions and a range of soybean cultivar maturities from MG 2 to 5. Data from 2017-2020 was analyzed and compiled in a draft research manuscript for publication. Results show that yield under non-water stressed conditions in the trials was highly dependent on the environment and MG choice, ranging from 43 to 87 bu/ac. The yield response to irrigation ranged from no response in 2018 (year with high precipitation), to a 38% yield increase in 2019. The effect of cultivar selection within a MG was relatively small relative to the effect of MG selection. However, optimum MG recommendations were variable depending not only on the planting date, but also changed from year to year. The results highlight the need to use crop model simulations to evaluate if some planting date and MG recommendations could be more efficient in increasing yield under rainfed conditions in the KY climate. The model was calibrated with data from 2017-2020 to quantify soybean yields under different planting date and MG scenarios without water limitation, and under rainfed conditions (manuscript under preparation). Goal 2: Study the effect of environmental conditions on mechanistic processes underlying biomass production and yield. Environmental conditions can affect yield determination through an indirect effect on assimilate supply, or a direct effect defining the size and number of sinks. This is a complex interaction that is difficult to measure under field conditions and that can limit crop model applications. During 2019 and 2020 we conducted greenhouse trials under different sour-sink manipulations imposed at different seed developmental stages. Results from source-sink manipulation trials were submitted for publication in 2020 (Chiluwal et al., under review). In this study we provide striking new evidence that soybean seeds can respond to increases in assimilate supply until the end of the seed filling phase, unlike in cereal crops. These results provide scope to increase seed growth accumulation and soybean yield through management practices and breeding efforts that increase the duration of a photosynthetically active canopy. The results also suggest that the end of the seed filling period in soybean in crop-eco-physiological models should be driven by assimilate supply and less by photothermal time. Goal 3: Investigate grain yield productivity and water use efficiency (WUE) of complex genotype x management x environment interactions with long term crop simulations. We used the DSSAT software to simulate cover crop-corn rotations in soils characteristics of the rolling landscapes in KY. The model was calibrated with data collected during 2019 by a collaborator at University of Kentucky. My research program aided with model calibration and application. Results from this crop model application were accepted for publication (Leuthold et al., accepted in Field Crops Research). Through this crop model application, we were able to identify unexpected benefits of cover crops for rainfed corn in our climate. Cover crops reduced risk of low corn yields in dry years and increased yield stability, due to a reduction in water runoff and evaporation losses, and increased water availability during late reproductive stages.

Publications

• Type: Journal Articles Status: Published Year Published: 2020 Citation: Sciarresi, C, C. Proctor, J. McMechan, G.I. Carmona, J. Wehrbein, R. Elmore, R. Werle, L.E. Lindsey, W. Looker, E.R. Haramoto, and M. Salmer?n. 2020. Evaluating short-season soybean management adaptations for cover crop rotations with crop model simulations. Field Crops Research, 250: 107734. http://doi.org/10.1016/j.fcr.2020.107734
• Type: Conference Papers and Presentations Status: Published Year Published: 2020 Citation: Sciarresi,, C., M. Salmer�n, C. Proctor, E.R. Haramoto, L.E. Lindsey, G. Inveninato Carmona, R. Elmore, S. Everhart, W. Looker, M. Marroquin-Guzman, J. McMechan, J. Wehrbein, and R. Werle. 2020. Evaluating short-season soybean management adaptations for cover crop rotations. Second International Crop Modelling Symposium (iCROPM2020). February 35, Montpellier, France. (poster)
• Type: Conference Papers and Presentations Status: Published Year Published: 2020 Citation: Salmer�n,M, Kothari, K., R. Battisti, K.J. Boote, S. Archontoulis, A. Confalone, J. Constantin, S. Cuadra, P. Debaeke, B. Faye, D. Fleisher, B. Grant, G.Hoogenboom, Q. Jing, I. Kisekka, B. Kimball, F. Leung, F. Marin, H. Meng, C. Nendel, B. Qian, C. Schoving, V. Sheila, E. da Silva, W. Smith, A. Srivastava, W. Sun, A. Suyker, K. Thorp, D. Timlin, N. Vieira Jr., K. Williams, and X. Xu. 2020. Evapotranspiration and water stress response in soybean: multi-model sensitivity analysis. 2021. ASA-CSSA-SSSA International Annual Meeting. November 7-10, Salt Lake City, Utah (virtual presentation)
• Type: Conference Papers and Presentations Status: Published Year Published: 2020 Citation: Chiluwal, A. , M. Salmer�n, D. Hildebrand, and T. Kawashima. Soybean seed size responds to increases in assimilate supply at the end of seed filling. 2020. ASA-CSSA-SSSA International Annual Meeting. November 7-10, Salt Lake City, Utah (poster presentation)
• Type: Conference Papers and Presentations Status: Published Year Published: 2020 Citation: Leuthold, S., H.J. Poffenbarger, M. Salmer�n, O. Wendroth, and E.R. Haramoto. 2020. Do cover crops increase or decrease spatiotemporal variability in maize yield? Second International Crop Modeling Conference (iCROPM). February 35, Montpellier, France. (poster)

Progress 10/01/18 to 09/30/19

Outputs
Target Audience:Target audiences of this project include grain crop producers in Kentucky and neighboring producing states (Midwest and Upper Midsouth producers), the scientific community, and graduate and undergraduate students. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?Training activities: This project has provided funds that help suport totallly or partially thementoring of three Master graduate students (Maria Morrogh Bernard graduated in the Fall of 2018;Cintia Sciarresi, graduated in the Fall of 2019;and Juan di Salvo, graduated in the fall of 2019). In addition, the project has provided partial support for students to attend research conferences and present their research. The project also provided funds to 4 undergaduate students working part time that gained hands-on research experience. One undergraduate presented independent research in a reserach conference. Professional development - attendance to conferences and meetings: The PI has participated in research conferences presenting3 oral presentations or posters during 2019 that were funded from this project. Other professional development:ThePIattended the DSSAT development Sprint workshop in University of Florida (7-11 Jan, 2019, Gainesville, FL). How have the results been disseminated to communities of interest?Results were disseminated to KY producers in 2019 throughtheextension report cited below. Salmerón, M., M. Morrogh Bernard†, C.D. Lee, C. Knot, E. Ritchey, and J. Shockley. Quantifying the soybean yield potential and yield gap associated to water stress in Kentucky. 2019 Kentucky Soybean Science Research Reports. https://graincrops.ca.uky.edu/files/soybeanscienceresearchreport2019.pdfSalmerón, M., M. Morrogh Bernard†, C.D. Lee, C. Knot, E. Ritchey, and J. Shockley. Quantifying the soybean yield potential and yield gap associated to water stress in Kentucky. 2019 Kentucky Soybean Science Research Reports. https://graincrops.ca.uky.edu/files/soybeanscienceresearchreport2019.pdf What do you plan to do during the next reporting period to accomplish the goals? Nothing Reported

Impacts
What was accomplished under these goals? Impact statetement: Crop management transformations that can increase yields in grain crops are essentialto meet an increasing food demand wth a sustainable use of agricultural land and resources.Management factors such as planting date, irrigation, and choice of cultivar maturityare main defining factors of final yield. These management decissions alsoaffectthe efficiency in the use of resources (water, nutrient, solar radiation), and influence the impact of different grain crops rotations at a system'slevel. Evaluating these interactions with the aid of field trials alone is challenging due to a limitation on the number of trials we can conduct, and due the variabiliy in environmental conditons from one year to another. This project combined field trials with simulations froma process-based eco-physiological model to study management recomendationsthat can help US grain crop producers achieve high productivity. Correct simulations from models are essential formodel applications that provide best management recomendations for producers, but also to quantify environmental impact, and for infomed policy making. Thus, this project isalso focused in the evaluation and improvement of soybean models through multi-model evaluatoin andinvestigating phyisological processes invovled in yield determantion and their interaction with environmental conditions to improve the description of these processes in eco-physiological models. Goal 1: Estimate soybean yield potential without water limitations for different MG cultivars and planting dates with the aid of experimental studies and crop simulation models. Field trials were conducted in 2017 to 2019 in Lexington, KY (and Princeton, KY in 2017)under irrigated and rainfed conditions and a range of soybean cultivar maturities from MG 2 to 5. Results from 2017-2019 were shared with producers in an extension report, and the Kentucky Soybean Promotion Board provided funds to support another year of trials in 2020 and a graduate student that will conduct crop model simulations with the data collected. Results from field experiments so far show thatyield under non-water stressed conditionsin the trials was highly dependent on the environment and MG choice, ranging from 43 to 87 bu/ac. The yield response to irrigation ranged from no response in 2018 (year with high precipitation), to a 38% yield increase in 2019. The effect of cultivar selection within a MG was relatively small relative to the effect of MG selection. However, optimum MG recomendations were variable depending not only on the planting date, but also changed from year to year. The results highlightthe need to use crop model simulations to provide more robust recomendations that take into account changes in evironmental conditions form year to year. Goal 2:Study the effect of environmental conditions on mechanistic processes underlying biomass production and yield. Environmental conditions can affect yield determination through an indirect effect on assmilate supply, or a direct effect defining the size an number of sinks. This is a complex interaction that is difficult to measure under field condtitions and that can limit crop model applicatoins under changing climate.We conducted growth chamber experiments under different temperatures during early soybean reproductive stages, in vitro seed growth experiments under different temperatures, and also greenhouse trials udner different sour-sink manipualtions imposed at different seed developmental stages.These findings can identify oportunities for yield improvement and be relevant for soybean breeders, and will help improve the description of yield physiological processes in soybean models. Goal 3: Investigate grain yield productivity and water use efficiency (WUE) of complex genotype x management x environment interactions with long term crop simulations. Data from another soybean multi-state study from 13 site-years (in 2017 and 2018) across Kentucky, Nebraska, and Ohio was already available and used to calibrate theDSSAT - CROPGRO model to simualte yields of MG 0 to 4 cultivars. Each site-year was either rainfed or irrigated, but with help of model simulations across 20-years we investigated the interaction of water avalabiliy on optimum maturity group selections. We were interested in evaluating short-season maturities as these may provide a larger window that facilitates planting of winter cover crops after soyeban in the fall.This manuscript is currently under final preparation. The results showed that themodel was efficientfor the simulation of date ofharvest maturity (R8; Model efficiency [ME]=0.61; Root Mean Square Error [RMSE]=7.4 days) and yield (ME=0.38; RMSE=0.452 Mg ha−1).Thereafter, a multi-factor sensitivity analysisacross 30-yr of historical weather data was conducted. Simulated results showed that MG 3 cultivars would not reduce yield and would advance cover crop establishment compared to MG 4 cultivars. For planting dates in May and conditions of no water stress, adaptating cultivar choices to MG lower than 3 would reduce yields by 55 to 567 kg ha−1 per unit decrease in MG. Under water stress or when planting date was delayed, adapting cultivarchoices to MG lower than 3 had a less detrimental effect on yield. Overall, switching to earlier cutlivar maturities would advance soybean harvest by 7-11 days MG−1 (May 15 planting date) or 1-7 days MG-1 (Jul 1 planting date), and lengthen the cover crop growing season in the fall by 95-198 °C day MG−1 (May 15 planting date) or 19−104 °C day MG−1 (Jul 1 planting date). The greater potential to increase the cover crop growing season with short-season MG cultivars was also associated with a greater soybean yield penalty in the warmest locations in our study.

Publications

• Type: Conference Papers and Presentations Status: Published Year Published: 2019 Citation: Brown, P., M. Salmer�n, F.M. Ali, and T. Kawashima. 2019. Effect of shading and pod competition on seed growth and development. ASA-CSSA-SSSA International Annual Meetings. November 10-11, San Antonio, Texas.
• Type: Conference Papers and Presentations Status: Published Year Published: 2019 Citation: Chiluwal, A., M. Salmer�n, and T. Kawashima. 2019. Source-Sink Manipulation Study to Investigate Seed Growth Dynamics in Soybean. ASA-CSSA-SSSA International Annual Meeting. November 10-13, San Antonio, Texas
• Type: Conference Papers and Presentations Status: Published Year Published: 2019 Citation: Sciarresi,, C. , M. Salmer�n*, C. Proctor, E.R. Haramoto, L.E. Lindsey, G. Inveninato Carmona, R. Elmore, S. Everhart, W. Looker, M. Marroquin-Guzman, J. McMechan, J. Wehrbein, and R. Werle. 2020. Evaluating short-season soybean management adaptations for cover crop rotations. Second International Crop Modelling Symposium (iCROPM2020). February 35, Montpellier, France.

Progress 10/01/17 to 09/30/18

Outputs
Target Audience:Target audiences of this project include grain crop producers in Kentucky and neighboring producing states (Midwest and Upper Midsouth producers), the scientific community, and graduate and undergraduate students. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?Training activities:This project has provided one-on-one mentoring for one Master graduate student, Maria Morrogh Bernard that graduated in the Fall of 2018. In addition, the project has provided partial support for two other Master graduate students currentlyin the PI research program (expected graduation in the Fall fo 2019) to conduct their research and attend research conferences. Professional development - attendance to conferences and meetings: The PI has participated in 4oral presentations or posters presented at research meetings (see list below, the asterisk indicates the presenting author). De Salvo, J.*†, Lee, C., Salmerón, M. (2018). Differences in yield productivity and stability by corn hybrid maturity. ASA-CSSA International Annual Meetings. 4-8 November. Baltimore, MD. (poster) Proctor, C.*, Salmerón, M.,Drewnoski, M., Elmore, R.G., Everhart, S.R., Haramoto, E., Lindsey, L., McMecha, A.J., Parsons, J., Redfearn, D.D., Werle, R. (2018). Evaluation of Yield Across a Range of Soybean Relative Maturity Groups. ASA-CSSA International Annual Meetings. 4-8 November. Baltimore, MD. (presentation) Morrogh Bernard, M.*† & Salmerón, M. (2018). Physiological Differences in Yield Determination across Soybean Maturity Groups. ASA-CSSA International Annual Meetings. 4-8 November. Baltimore, MD. (abstract) Cintia Sciarresi.*, Haramoto, E., Salmeron, M. (2018). Optimizing cover crop performance by maturity group selection as an integrated pest management strategy. ASA-CSSA International Annual Meetings. 4-8 November. Baltimore, MD. (presentation) Other professional development: Atthended a Phenomics Workshop at the Arid Land Phenomics Institute. University of Arizona, Maricopa Agricultural Center, Maricopa, AZ (March 12-15, 2018). Attended the 7th AgMIP Global Workshop (AgMIP: Agricultural Model and Intercomparison Project) in San Jose, Costa Rica. (AgMIP) International Meeting in Costa Rica (April 24-26, 2018) How have the results been disseminated to communities of interest? Nothing Reported What do you plan to do during the next reporting period to accomplish the goals? Nothing Reported

Impacts
What was accomplished under these goals? Goal 1: Estimate soybean yield potential without water limitations for different MG cultivars and planting dates with the aid of experimental studies and crop simulation models. Field trials conducted in 2017 were repeated in 2018 in two environments (Lexington with planting date in May and June). In 2017, the trials had been stablished in threeenvironments: Lexington, planted in May and June, and Princeton, planted in May. The main factor rested was the effect of irrigation (irrigated vs. rainfed), and the second factor was the soybean maturity group (MG). Cultivars ranging fromMG2 to 5 (16 cultivars in total) were included in the study. Some cultivars changed from one year to the next, but were replaced by cultivars of a similar maturity. The yield potential in these trials under irrigated conditions was highly dependent on the environment and MG choice, ranging from 56 to 87 bu/ac in 2017, and from 30 to 77 bu/ac in 2018. The yield response to irrigation ranged from no response to a 30% yield increase in 2017, and no response to irrigation in 2018 (year with higher precipitation). The effect of cultivar selection within a MG was relatively small relative to the effect of MG selection. In 2017, MG 2 to 4 had the highest yield potential for the May planting date in Lexington (83 bu/ac), whereas MG 3 and 4 where best for the June planting date (71 bu/ac). At Princeton, MG 4 where the best choice (81 bu/ac), and selection of MG 3 cultivars reduced yields by 14%. in 2018, MG 4 had the highest yield under irrigation (77 bu/ac) when planted in May, and MG 2 to 4 had siimilar yields (46 bu/ac) when planted in June.These results evidence the need to optimize MG selection at each environment to maximize yield potential, but that the results can be highly variable form one environment to another, and from year to year. Further data from more years combined with crop model simulations is required to provide robust recommendations. Goal 2: Study the effect of environmental conditions on mechanistic processes underlying biomass production and yield. Reaching reproductive stages during the time of year with highest solar radiation intensities could allow targeting higher yield potentials. Results from 2017 show that beginning flowering (R1) in MG 2 cultivars occurred on June 19, June 29, and July 21 at Lexington (planted on May), Princeton (planted on May), and Lexington (planted on June), respectively (Figure 2). Therefore, reproductive stages started during the summer solstice for the earlier MG cultivars used, but took place as daily solar radiation intensity declined. Reproductive stages of MG 4 cultivars started 10 days after MG 2 on average. Results suggest that combining earlier planting dates with relatively earlier MG cultivars could position the duration of flowering and pod setting stages closer to times of higher solar radiation intensity. Other environmental conditoins and yield physiological traits in data from 2017 will be analyzed and combined with data from 2018 to adress this objective. Goal 3: Investigate grain yield productivity and water use efficiency (WUE) of complex genotype x management x environment interactions with long term crop simulations. Data collected in 2017 and 2018 will be used for crop model calibration and evaluation, to adress objective 4.

Publications

• Type: Journal Articles Status: Accepted Year Published: 2017 Citation: Salmeron, M.*, Purcell L.C., Vories, E.D. & Shannon, G. (2017). Simulation of soybean genotype-by-environment interactions for yield under irrigation in the Midsouth with DSSAT-CROPGRO. Agricultural Systems 150: 120-129.
• Type: Conference Papers and Presentations Status: Accepted Year Published: 2018 Citation: Proctor, C.*, Salmer�n, M.,Drewnoski, M., Elmore, R.G., Everhart, S.R., Haramoto, E., Lindsey, L., McMecha, A.J., Parsons, J., Redfearn, D.D., Werle, R. (2018). Evaluation of Yield Across a Range of Soybean Relative Maturity Groups. ASA-CSSA International Annual Meetings. 4-8 November. Baltimore, MD. (presentation)
• Type: Conference Papers and Presentations Status: Accepted Year Published: 2018 Citation: De Salvo, J.* , Lee, C., Salmer�n, M. (2018). Differences in yield productivity and stability by corn hybrid maturity. ASA-CSSA International Annual Meetings. 4-8 November. Baltimore, MD. (poster)
• Type: Conference Papers and Presentations Status: Accepted Year Published: 2018 Citation: Cintia Sciarresi.*, Haramoto, E., Salmeron, M. (2018). Optimizing cover crop performance by maturity group selection as an integrated pest management strategy. ASA-CSSA International Annual Meetings. 4-8 November. Baltimore, MD. (presentation)

Progress 01/03/17 to 09/30/17

Outputs
Target Audience:Target audiences of this project include grain crop producers in Kentucky and neighboring producing states (Midwest and Upper Midsouth producers), the scientific community, and graduate and undergraduate students. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?Training activities: This project has provided one-on-one mentoring for a Master graduate student, Maria Morrogh Bernard. The graduate student started working in the PI research program at University of Kentucky in the Summer of 2016 and is expected to graduate in the summer of 2018. Professional development - attendance to conferences and meetings: The PI has participated in 5 oral presentations or posters presented at research meetings (see list below, the asterisk indicates the presenting author). Morrogh Bernard, M.*† & Salmerón, M. (2017). Optimizing yield and water use efficiency of soybean production in Kentucky - experimental and modeling approach. Kentucky Water Research Institute (KWRRI) Symposium. 22-25 October. Lexington, KY. (presentation) Morrogh Bernard, M.*† & Salmerón, M. (2017). Increased partitioning to reproductive organs with early maturities in double crop soybean. ASA-CSSA- SSSA International Annual Meetings. 22-25 October. Tampa, FL. (poster) Snyder, E. †, Knott, C., Van Sanford, D. & Salmerón, M. (2017). Can Predicting Soft Red Winter Wheat Development Assist Agronomic Management in Kentucky? ASA-CSSA- SSSA International Annual Meetings. 22-25 October. Tampa, FL. (presentation). I adviced Ethan Snyder in some of the data analysis. Salmerón, M.*, Purcell, L, Popp, M. Weeks, W. (2016). Soyrisk - a Decision Support Tool for Managing Risk and Profitability Using Simulated Soybean Yields for the Midsouth. ASA-CSSA- SSSA International Annual Meetings. 7-9 November. Phoenix, AZ. (poster) Snyder, E.*, Knott, C., Van Sanford, D. & Salmerón, M. (2016). Genotypic and phenotypic characterization of VRN and PPD alleles in soft red winter wheat. ASA-CSSA- SSSA International Annual Meetings. 7-9 November. Phoenix, AZ. (poster). I adviced Ethan Snyder in some of the data analysis and revised the poster. Other professional development: Obtained a Remote Pilot Certificate (RPC) issued by the FAA (2017). Attended the workshop 'Field Scale Agricultural Remote Sensing: Suas, Drones, and Beyond' during the ASA and CSSA Annual Meeting in Tampa, FL (Nov 4, 2017). Attended the UT-UK Grant Writing Seminar in Knoxville, TN (March 16 -17, 2017) Attended the Spring 2017 National Science Foundation Grants Conference in Louisville, KY (June 2017) How have the results been disseminated to communities of interest? Nothing Reported What do you plan to do during the next reporting period to accomplish the goals? Nothing Reported

Impacts
What was accomplished under these goals? Goal 1: Estimate soybean yield potential without water limitations for different MG cultivars and planting dates with the aid of experimental studies and crop simulation models. Field trials were stablished with MG 2 to 5 (16 cultivars in total) and at three different environments in 2017: Lexington, planted on May 16; Princeton, planted on May 23; and Lexington, planted on June 14. The yield potential in these trials under irrigated conditions was highly dependent on the environment and MG choice, ranging from 56 to 87 bu/ac. The yield response to irrigation ranged from no response to a 30% yield increase.The effect of cultivar selection within a MG was relatively small relative to the effect of MG selection. MG 2 to 4 had the highest yield potential for the May planting date in Lexington (83 bu/ac), whereas MG 3 and 4 where best for the June planting date (71 bu/ac). At Princeton, MG 4 where the best choice (81 bu/ac), and selection of MG 3 cultivars reduced yields by 14%. These results evidence the need to optimize MG selection at each environment to maximize yield potential. Further data from more years is required to provide robust recommendations. Goal 2: Study the effect of environmental conditions on mechanistic processes underlying biomass production and yield. Environmental conditoins and yield physiological traits were collected across the wide range of treatments studied to adress this objective. Goal 3: Investigate grain yield productivity and water use efficiency (WUE) of complex genotype x management x environment interactions with long term crop simulations. Data collected in 2017 and 2018 will be used for crop model calibration and evaluation, to adress objective 4.

Publications

• Type: Other Status: Published Year Published: 2017 Citation: Knott C, Lee C, and Salmerón M. 2017. Growth and Development. In Comprehensive Soybean Management Guide. C. Knott, C. Lee, C. Venard (eds.). ID-249. Available at http://www2.ca.uky.edu/agcomm/pubs/ID/ID249/ID249.pdf
• Type: Conference Papers and Presentations Status: Published Year Published: 2017 Citation: Morrogh Bernard, M.*⿠ & Salmerón, M. (2017). Optimizing yield and water use efficiency of soybean production in Kentucky ⿿ experimental and modeling approach. Kentucky Water Research Institute (KWRRI) Symposium. 22-25 October. Lexington, KY. (presentation)
• Type: Conference Papers and Presentations Status: Published Year Published: 2017 Citation: 2. Morrogh Bernard, M.*⿠ & Salmerón, M. (2017). Increased partitioning to reproductive organs with early maturities in double crop soybean. ASA-CSSA- SSSA International Annual Meetings. 22-25 October. Tampa, FL. (poster)