Location: Water Management Research2022 Annual Report
U.S. dairy industry’s economic value is estimated at $51.4 billion. About 30% of the total U.S. milk production comes from the Western states with 20% of it from California. Alfalfa production in California is heavily dependent on irrigation. Competition for declining water resources for domestic, industrial, and agricultural uses, combined with frequent droughts, have resulted in reduced alfalfa acreage. With high milk producing dairy cows requiring high-quality forage, sustainable management strategies are needed for alfalfa production in the West with maximized water productivity and forage quality. The overall goal of this multidisciplinary project is to develop new tools and strategies for alfalfa production in the Western U.S. that conserve scarce water resources and lead to high yield and quality dairy forage. Objective 1: Develop new tools and strategies for management of alfalfa production in the Western U.S. that conserves scarce water resources, maintains water quality, and leads to high-quality dairy forage and the delivery of environmental services. Sub-objective 1A: Determine the effects of irrigation and cutting schedules management on forage yield, quality, water use efficiency and water extraction patterns of non-dormant reduced-lignin and conventional alfalfa varieties under semi-arid growing conditions. Sub-objective 1B: Utilize remotely sensed data products to quantify differences in consumptive water use and water productivity for commercial alfalfa produced with different irrigation techniques, on different soil types, and considering inter-annual variability of growing conditions. Objective 2: Develop agronomic management strategies for production of alfalfa forage with improved yield, quality, nutritional and economic value. Sub-objective 2A: Optimize yield and quality of reduced-lignin alfalfa varieties by altering cutting schedules. Sub-objective 2B: Determine effects of specific traits on growth, yield, quality and plant stand persistence of new and conventional varieties.
Objective 1, Sub-objective 1A: The research goal for this study is to develop a sustainable irrigation strategy for alfalfa that can ensure optimum forage yield, stand persistence, and nutritional and economic values. Field experiments with frequent and infrequent irrigation are planned for alfalfa varieties with reduced- and non-reduced lignin traits. Yield, quality, and plant biophysical parameters of alfalfa will be determined and analyzed to evaluate the interactive effect of irrigation frequency and varietal traits. If the pre-selected irrigation level is too low in the first year, adjustments will be made to avoid the loss of alfalfa stands and the experimental treatments. Sub-objective 1B: The research goal for this study is to utilize remote sensing data to evaluate sub-surface drip irrigation for increasing alfalfa water use efficiency and water productivity compared to flood irrigation on dairy farms in the San Joaquin Valley of California. We will assess methodological accuracy and uncertainty of model estimation of crop evapotranspiration using satellite imagery and evaluate the hypothesis that sub-surface drip irrigation increases water use efficiency in actual production settings. Remote-sensing data products will be combined with USDA crop statistics to evaluate soil type, irrigation water source, and irrigation technology associated with optimal water use for alfalfa production. If the daily evapotranspiration estimates provided by commercial systems are not adequate for evaluating time-dependent variability, short-term targeted field experiments will be conducted using eddy-covariance and supporting sensor systems. Objective 2, Sub-objective 2A: The research goal of this study is to develop a sustainable cutting schedule management strategy for reduced-lignin alfalfa varieties that can ensure optimum yield, dairy quality forage, stand persistence, and nutritional and economic values. The field experiment treatments include 3 cutting schedules (28-day, 35-day, and staggered/alternating between 21- and 35-day) and 8 varieties. Treatment effects on alfalfa yield, quality, stand persistence, and nutritional and economic values will be determined annually. This study will be located at a University of California field facility, and we rely on farm labor support from the university. If the farm support becomes unavailable, we will provide labor support from ARS project employees and work with the university collaborator to continue the project as planned. Sub-objective 2B: The research goal of this study is to evaluate 20 diverse alfalfa varieties for growth, biomass, and quality dynamics, yield forming traits, and plant biophysical characteristics to improve variety development and to develop a growth model using a regression analysis approach for predicting growth dynamics, forage yield and quality. Plant samples will be collected at each harvest for forage quality analysis. For model development, plant height, biomass, leaf area index, photosynthetic rate, and stomatal conductance will be measured. Planting is in the spring and if some varieties do not establish well, they will be classified as poor performers.
Under Sub-objective 1A, the initial year of full production with field experiments involving irrigation, cutting schedules and alfalfa variety interactions was completed. Backlogged plant samples were processed for quality analysis. Irrigation treatments were applied as non-frequent irrigation at only one irrigation per cut and frequent irrigation at once a week, both at 110% evapotranspiration (ET) levels. This was based on potential ET values obtained from a California Irrigation Management Information System (CIMIS) weather station located near the study area. Alfalfa yield was measured following the 28 day and 35 day cuttings schedule treatments. One day before plot harvest, alfalfa samples were hand-collected for quality analysis. Soil moisture was measured at different soil depths using a neutron gauge every two to three weeks during the growing season. Leaf stomatal conductance was measured using a porometer. The data generated will be used for testing an alfalfa crop model to simulate and determine growth, yield, and forage quality dynamics. Forage yield and applied water use efficiency data were analyzed to prepare an abstract for presentation at the 2022 World Alfalfa Congress. Under Sub-objective 1B, protocols were developed for utilizing remote sensing data products to determine water productivity of alfalfa under various management strategies and water productivity trends were analyzed for a 12 year period. Preliminary field experiments were conducted for a three month period in plot trials, using the eddy-covariance and other methods to estimate actual crop utilization of applied irrigation. A second field experiment was conducted in conjunction with ongoing research into groundwater recharge in winter-irrigated alfalfa. A proposed agreement with a cooperating farmer is under evaluation to conduct new field research extending previous work on calibrating remote sensing of crop water requirements (OpenET). Field data from this project year will be used to improve error estimation of the eddy-covariance method applied to calibrate remote sensing models. Research published in Agricultural Water Management documented interannual trends in water productivity for alfalfa, compared to wheat and barley, for the period 2009-2020 in the East Snake Plain of Idaho. This published technique will be applied to analyze recent satellite models (OpenET) to determine water productivity for cultivation of alfalfa in California. A newly hired postdoctoral scientist is analyzing the OpenET. Under Sub-objective 2A, the research goal is to develop a sustainable cutting schedule management strategy for reduced-lignin alfalfa varieties that can ensure optimum yield, dairy quality forage, stand persistence, nutritional and economic values. This is the third production year following crop establishment. The field experiment includes three cutting schedules (28-day basis: 28 days, 35 days and staggered i.e. alternating between 21 and 35 days) and eight alfalfa varieties including reduced-lignin and conventional types. Parameters measured involved forage yield, quality and stand persistence. Plant samples were analyzed for quality. Soil samples were taken for nutrient analysis. Following alfalfa’s termination, forage winter wheat in January and corn in June of 2022 were planted. The rotational benefit of alfalfa on winter wheat and corn forage yield and quality will be examined. Partial research results were presented at the 2022 North American Alfalfa Improvement Conference. Results on alfalfa yield-quality tradeoff of higher quality varieties under different cutting schedules were presented at the 2022 World Alfalfa Congress. Under Sub-objective 2B, research continued with alfalfa to determine delayed cutting schedule (35-day basis) effect on forage yield and quality of 20 diverse varieties. Weekly destructive plant sampling of four varieties was conducted during early-, mid- and late-cropping season for modeling plant growth dynamics. Leaf area index and stomatal conductance measurements were also taken on these four varieties three times during the cropping season. Crop establishment and initial yield data were published in the December 2021 Issue of the University of California Agronomy Progress Report Extension Publication.
1. Forage yield and quality of a winter canola–pea mixed cropping system. Forage crop–dairy farming is an important agricultural industry that involves an intensive system requiring high-input forage crops, primarily annual grass-type crops in monocropping approaches. Winter canola and pea have the potential to provide forage crop diversity options, but information on yield and quality of the canola–pea mixed cropping system is limited. ARS scientists in Parlier, California, collaborated with researchers at New Mexico State University to study winter canola and pea in mono- and mixed-cropping using different seeding ratio combinations to assess yield and quality. Canola–pea mixed cropping achieved high yields and land productivity. This cropping strategy has potential to improve mechanical harvestability of vining pea and strengthen the diversity and sustainability of forage crop–dairy farming in the Southern Great Plains under limited irrigation and may be applicable in other regions with similar agroecosystems. This cropping strategy can be used by dairy and crop producers to diversify their forage crops and strength forage crop-dairy farming systems.
Kelley, J.R., Olson, B. 2022. Interannual variability of water productivity on the Eastern Snake Plain in Idaho, United States. Agricultural Water Management. 265. Article 107532. https://doi.org/10.1016/j.agwat.2022.107532.
Angadi, S., Umesh, M., Begna, S.H., Gowda, P.H. 2021. Light interception, agronomic performance, and nutritive quality of annual forage legumes as affected by shade. Field Crops Research. 275. Article 108358. https://doi.org/10.1016/j.fcr.2021.108358.
Paye, W., Begna, S.H., Ghimire, R., Angadi, S., Singh, P., Umesh, M., Darapuneni, M. 2021. Winter canola yield and nitrogen use efficiency in a semiarid irrigated condition. Agronomy Journal. 113(2):2053-2067. https://doi.org/10.1002/agj2.20611.
Begna, S.H., Angadi, S., Mesbah, A., Umesh, M., Stamm, M. 2021. Forage yield and quality of winter canola-pea mixed cropping system. Sustainability. 13(4). Article 2122. https://doi.org/10.3390/su13042122.