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Field evaluations of the CropManage decision support tool for improving irrigation and nutrient use of cool season vegetables in California

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  • Cahn, Michael
  • Smith, Richard
  • Melton, Forrest

Abstract

Vegetable growers on the central coast of California are under regulatory pressure to reduce nitrate loading to ground and surface water supplies. California also implemented legislation that limits agricultural pumping in regions such as the central coast where the aquifers have been over-extracted for crop irrigation. Growers could potentially use less N fertilizer, address water quality concerns, and conserve water by improving water management and matching nitrogen applications to the N uptake pattern of their crops. Two tools available to growers, the soil nitrate quick test (SNQT) and reference evapotranspiration (ETo) data have been previously shown to improve the management of water and fertilizer nitrogen in vegetable production systems. However, adoption of these practices has not been widespread. These techniques can be time consuming to use, and vegetable growers often have many crops to manage. To address such time constraints, the CropManage online application (cropmanage.ucanr.edu) was developed to facilitate implementation of the SNQT and evapotranspiration-based irrigation scheduling. CropManage additionally helps growers account for plant available N from background levels of nitrate in irrigation water. Trials were conducted in commercial vegetable fields in the Salinas Valley during 2012–2019 to evaluate CropManage fertilizer and irrigation recommendations relative to the grower practice. Results demonstrated that in many cases fertilizer or irrigation reductions could be attained by following CropManage recommendations without jeopardizing yield. In lettuce, the total fertilizer N applied under CropManage guidance was reduced by an average of 31 % compared to the grower standard practice. Lettuce yield within the CropManage treatment averaged 107 % of the grower practice. CropManage guidance in broccoli reduced N and applied water by 24 % and 27 %, respectively, compared to the grower standard practice, while average yield was similar between treatments. Management tools such as CropManage can support operational efficiencies and compliance with regulatory targets designed to improve groundwater quality.

Suggested Citation

  • Cahn, Michael & Smith, Richard & Melton, Forrest, 2023. "Field evaluations of the CropManage decision support tool for improving irrigation and nutrient use of cool season vegetables in California," Agricultural Water Management, Elsevier, vol. 287(C).
    • Handle: RePEc:eee:agiwat:v:287:y:2023:i:c:s0378377423002664
    DOI: 10.1016/j.agwat.2023.108401
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    References listed on IDEAS

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    1. Gallardo, M. & Giménez, C. & Martínez-Gaitán, C. & Stöckle, C.O. & Thompson, R.B. & Granados, M.R., 2011. "Evaluation of the VegSyst model with muskmelon to simulate crop growth, nitrogen uptake and evapotranspiration," Agricultural Water Management, Elsevier, vol. 101(1), pages 107-117.
    2. Pereira, L.S. & Paredes, P. & Melton, F. & Johnson, L. & Wang, T. & López-Urrea, R. & Cancela, J.J. & Allen, R.G., 2020. "Prediction of crop coefficients from fraction of ground cover and height. Background and validation using ground and remote sensing data," Agricultural Water Management, Elsevier, vol. 241(C).
    3. Gallardo, Marisa & Elia, Antonio & Thompson, Rodney B., 2020. "Decision support systems and models for aiding irrigation and nutrient management of vegetable crops," Agricultural Water Management, Elsevier, vol. 240(C).
    4. Giménez, C. & Thompson, R.B. & Prieto, M.H. & Suárez-Rey, E. & Padilla, F.M. & Gallardo, M., 2019. "Adaptation of the VegSyst model to outdoor conditions for leafy vegetables and processing tomato," Agricultural Systems, Elsevier, vol. 171(C), pages 51-64.
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