TY - JOUR
T1 - Alfalfa water productivity and yield gaps in the U.S. central Great Plains
AU - Fink, Kaylin P.
AU - Grassini, Patricio
AU - Rocateli, Alexandre
AU - Bastos, Leonardo M.
AU - Kastens, Jude
AU - Ryan, Luke P.
AU - Lin, Xiaomao
AU - Patrignani, Andres
AU - Lollato, Romulo P.
N1 - Funding Information:
This research was funded by the USDA grant number USDA-NIFA-OP-006691. We thank the Kansas alfalfa farmers who provided their time and data by participating in the survey, as well as the County Extension Agents within the Kansas University Research and Extension system who provided contact for representative farmers in their regions. The questionnaire applied to farmers was approved by the Committee for Research Involving Human Subjects (Kansas State University Application number 9941). This is contribution number 22–235-J of the Kansas State University Agricultural Experiment Station system.
Publisher Copyright:
© 2022 The Authors
PY - 2022/12/1
Y1 - 2022/12/1
N2 - Context: Yield gap (Yg) analyses using farmer-reported yield and management data have been performed for a number of annual grain crops, but it lacks for perennial forages. The U.S. accounts for 21 % of the global alfalfa production with a large rainfed area located in the central Great Plains, serving as an interesting case-study for Yg in perennial forages. Most existing alfalfa Yg analyses quantified the magnitude of the Yg but failed to identify associated management practices to reduce it. Challenging this analysis, a systematic benchmark for alfalfa water productivity [WP, kg dry matter per mm evapotranspiration (ETc)] that allows for the quantification of Yg in farmer fields does not exist. Objectives: Our objectives were to (i) benchmark alfalfa WP, (ii) quantify Yg in alfalfa farmer fields, and (iii) identify management opportunities to improve alfalfa yield. Methods: We conducted a systematic review of literature and compiled a database on alfalfa yield and ETc (n = 68 papers and 1027 treatment means) from which a WP boundary function was derived. We collected management and yield data from 394 commercial rainfed alfalfa fields during 2016–2019 in central Kansas. We then used satellite imagery to define the growing season (and corresponding water supply) for each field. The boundary function was then used to calculate Yg of each field, and conditional inference trees (CIT) explored the impact of management practices associated with increased yield. Results: Our boundary function suggested an alfalfa WP of 34 kg ha-1 mm-1. Farmer-reported yield ranged from 0.9 to 19.0 Mg ha-1, averaging 7.6 Mg ha-1. Alfalfa water-limited yield potential (Yw) ranged from 11.1 to 23.2 Mg ha-1, resulting in an average yield gap of 54–60 % of Yw. Row spacing, seeding rates, and management of phosphorus fertilizer were major agronomic practices explaining alfalfa yields in farmer fields, followed by surrogate variables as sowing season, stand age, and soil pH. Conclusions: Our study provided the first systematic analysis estimating attainable alfalfa WP as function of ETc, suggesting that large alfalfa Yg exist in the U.S. central Great Plains. We also identified key agronomic practices associated with increased alfalfa yield. Significance: The WP here derived can be used for future studies aiming at quantifying alfalfa Yg across the globe. This was an initial step in quantifying Yg and its associated causes at farmer fields, and we highlight limitations and future directions for perennial forages yield gap analyses.
AB - Context: Yield gap (Yg) analyses using farmer-reported yield and management data have been performed for a number of annual grain crops, but it lacks for perennial forages. The U.S. accounts for 21 % of the global alfalfa production with a large rainfed area located in the central Great Plains, serving as an interesting case-study for Yg in perennial forages. Most existing alfalfa Yg analyses quantified the magnitude of the Yg but failed to identify associated management practices to reduce it. Challenging this analysis, a systematic benchmark for alfalfa water productivity [WP, kg dry matter per mm evapotranspiration (ETc)] that allows for the quantification of Yg in farmer fields does not exist. Objectives: Our objectives were to (i) benchmark alfalfa WP, (ii) quantify Yg in alfalfa farmer fields, and (iii) identify management opportunities to improve alfalfa yield. Methods: We conducted a systematic review of literature and compiled a database on alfalfa yield and ETc (n = 68 papers and 1027 treatment means) from which a WP boundary function was derived. We collected management and yield data from 394 commercial rainfed alfalfa fields during 2016–2019 in central Kansas. We then used satellite imagery to define the growing season (and corresponding water supply) for each field. The boundary function was then used to calculate Yg of each field, and conditional inference trees (CIT) explored the impact of management practices associated with increased yield. Results: Our boundary function suggested an alfalfa WP of 34 kg ha-1 mm-1. Farmer-reported yield ranged from 0.9 to 19.0 Mg ha-1, averaging 7.6 Mg ha-1. Alfalfa water-limited yield potential (Yw) ranged from 11.1 to 23.2 Mg ha-1, resulting in an average yield gap of 54–60 % of Yw. Row spacing, seeding rates, and management of phosphorus fertilizer were major agronomic practices explaining alfalfa yields in farmer fields, followed by surrogate variables as sowing season, stand age, and soil pH. Conclusions: Our study provided the first systematic analysis estimating attainable alfalfa WP as function of ETc, suggesting that large alfalfa Yg exist in the U.S. central Great Plains. We also identified key agronomic practices associated with increased alfalfa yield. Significance: The WP here derived can be used for future studies aiming at quantifying alfalfa Yg across the globe. This was an initial step in quantifying Yg and its associated causes at farmer fields, and we highlight limitations and future directions for perennial forages yield gap analyses.
KW - Evapotranspiration
KW - Medicago sativa L.
KW - On-farm data
KW - Water use efficiency
KW - Yield potential
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U2 - 10.1016/j.fcr.2022.108728
DO - 10.1016/j.fcr.2022.108728
M3 - Article
AN - SCOPUS:85139838564
SN - 0378-4290
VL - 289
JO - Field Crops Research
JF - Field Crops Research
M1 - 108728
ER -