Note: This is part of a Research Update series that highlights projects funded by the California Department of Food and Agriculture (CDFA) Fertilizer Research and Education Program (FREP) Grant Program.
Project Title: Adapting CropManage Irrigation and Nitrogen Management Decision Support Tool for Central Valley Crops
Project Leaders: Michael Cahn (UCCE), Patrick Brown (UCD), Allan Fulton (UCCE)
Project Status: Complete (3-year project)
Overview: This FREP-funded project provides information on the expansion of CropManage (CM) decision support tool to include some of the Central Valley (CV) crops including almonds, processing tomato, and alfalfa.
Background: To prevent nitrate contamination of surface and groundwater resources in California,the Central Valley Regional Water Quality Control Board (CVRWQCC) requires growers to implement best management practices (BMPs) to minimize environmental impacts of nitrogen (N) fertilizer applications. Considering that nitrate from fertilizers can be readily leached to the groundwater, with excess irrigation, growers should optimize N and water management using appropriate decision support tools. CropManage (CM) is an online tool for assisting growers with efficiently managing water and N fertilizer to match the specific needs of their crops. CM initially started with a focus on annual Central Coast crops such as leafy greens, cane berries, and strawberries. Due to increasing interest to expand CM to include CV crops, this project focused on updating CM software to include almonds, walnuts, and processing tomatoes and improve the CM user-interface.
Approach: In the first year of the project, the researchers developed and tested preliminary algorithms and user interfaces for processing tomatoes, alfalfa, and almonds. They achieved this by adding models that estimate crop evapotranspiration (ET) based on reference ET, canopy cover (i.e. figure 1) and development, and water and N requirements. The CM interface now allows users to enter information such as degree of water stress to improve fruit quality (tomato) and to prevent hull rot (almond); projected yield; leaf N values; age of the orchard; and soil amendments. All three crop models are now available on the production version of CM. In addition, the researchers updated the CM user interface to improve navigation and data presentation; included online user help and support; and added irrigation and nutrient management terms.
Figure 1. Comparisons of CM, satellite estimates, and ground measurements of canopy cover in a commercial processing tomato field.
During the second year, the project leads finalized algorithms and user interfaces for processing tomatoes, almonds, and alfalfa. They also added a module to import soil moisture data from commercial companies and other third-party providers. The project team surveyed CM users about interface modifications made during CM workshops in 2018 and 2019. An additional survey was conducted in collaboration with the California Department of Food and Agriculture (CDFA)-FREP staff during 2019 on the applicability and general use of CM. A user feedback link was added to the menu so that errors and suggestions for improvement can be quickly reported to the software engineers.
In the third year, the researchers updated the user interface so users can enter measurements of canopy cover and compare with modeled estimates. Additionally, satellite estimates of canopy cover from the National Aeronautics and Space Administration (NASA) Satellite Irrigation Management System (SIMS) are automatically imported and displayed on the same canopy graph. Afterwards, the researchers conducted training workshops for alfalfa, processing tomato, and almonds for farm advisors and specialists that work with CV crops.
Results:
User interface: The updated CM interface improves a user’s experience by simplifying how they navigate to their plantings and ranches. The user can filter by the first letter or complete name of a ranch, and by name, lot name, crop type, or year of a planting. Users can also designate ranches or plantings to a favorite list that displays only the plantings and/or ranches which are of immediate interest. The planting summary tile allows users to quickly review upcoming and past events and tasks (Figure 2). Users can also add an irrigation, fertilizer, and soil sampling events from the planting tile. Also, information entered regarding water, fertilizer, and soil samples can be reviewed by opening an event.
Figure 2. Updated user interface in CM displaying events for a processing tomato crop.
Processing tomato: Preliminary field testing of CM for processing tomato was conducted in two commercial fields in Dixon, CA, during the 2019 season. Recommended water for fields 1 and 2 were 28.5 and 22.9 inches, respectively. The grower, however, applied 18.2 and 17.7 inches to fields 1 and 2, respectively, which is substantially less than the CM recommendations. As the purpose of this testing was to observe if the grower irrigations were close to the CM estimates, the researchers speculated that the wet spring provided a substantial amount of moisture in the soil profile. Hence, there was no need to irrigate to full crop ET until later in the season. However, the canopy cover in both fields declined substantially later in the season indicating either a disease issue or that the crop may have been water stressed (Figure 3).
Figure 3. Comparisons of CM, satellite estimates, and ground measurements of canopy cover in a commercial processing tomato field.
Alfalfa: The addition of alfalfa to CM was completed in August of 2018. Users can now enter cutting dates, which defines the canopy development curve and crop coefficient (Kc) values. Since alfalfa fixes N, no fertilizer N recommendation is provided; however, users can enter soil test values and fertilizer events. Alfalfa, as well as other deep-rooted crops such as processing tomato and almonds, required changes to the root development algorithm and soil database to include depths of 0 to 4 ft. This addition required major updates to the CM database and soil module. Users can also input the depth of impermeable layers that limit the root growth of their crop.
Almonds: The addition of almonds to CM required major changes to the user interface and algorithms. The irrigation algorithm is similar to processing tomato, where the Kc values are estimated based on a canopy development curve (Figure 4) and users can define periods when water stress should be imposed on the crop. Since water and N requirements of trees changes as they age, the parameters for the irrigation and N models are defined for orchards of different ages: for example, almond 1-2 years, almond 3-4 years, etc. The user must indicate the age of the orchard each year as well as the date when the leaves emerged in the spring. In collaboration with the Almond Board of California (ABC), the researchers developed an interface between CM and the California Almond Sustainability Program (CASP) so that almond growers have an option to export data entered into CM to the CASP website.
Figure 4. Canopy curve of almonds used for estimating the crop coefficient (Kc) for the irrigation recommendation. Users can view and adjust the canopy curve to match the specific conditions of their orchards.
Soil moisture display: The soil moisture display was tested for several field sites using tensiometers that were interfaced with Campbell dataloggers. Linking the datafile to a CM planting was facilitated with an improved user interface. The graphical chart allows users to display the sensors and locations of interest and adjust the scaling.
User support improvements: The CM team enhanced user support by adding information icons to explain irrigation and nutrient management terms throughout the software. WordPress software was integrated into CM to provide online help and user support. Through a link in the CM menu, users can now search for help, look up terms in a glossary, and read tutorials. Finally, users can now send their feedback to the CM administrators using the provided link.
Project Summary
CropManage offers online irrigation and N management decision support, and now has expanded capabilities to provide recommendations for CV crops such as alfalfa, almond, and processing tomato. The project was able to educate more than 1,800 clienteles about nutrient and water management tools for improving fertilizer use efficiency. The significant increase in the number of CM enrollments and recommendations highlights the success of the project. Since almond, alfalfa, and processing tomato were recently added to CM, CV growers and consultants are becoming familiar with the software. The researchers anticipate CM adoption to increase as they continue to offer more workshops and trainings in the region.