Project Overview
Local crop variety trial data is an important tool for producers to understand how specific crop varieties might perform on their farm, given site-specific conditions including temperature/climate, precipitation, and soil type. Historically, university or government-funded research and extension programs have generated the majority of the crop variety trial data available to the public, but in recent years, these localized/region-specific datasets have become increasingly difficult to find, especially for specialty vegetable crops.
To address this issue, the Vegetable Variety Navigator (VVN) was created in 2020. The VVN is a database of public variety trial results that can be analyzed and visualized to inform growers about how a particular vegetable variety might perform compared to others in their location (or globally). The VVN currently utilizes data from 288 public variety trial sources worldwide to generate site-specific yield and quality predictions for several varieties of broccoli, cucumber, and sweet pepper.
In this study, sixteen on-farm variety trials for broccoli, cucumber, and sweet pepper were conducted at the University of Nebraska-Lincoln East Campus Research Farm to validate the predictive capabilities of the VVN.
Farmer Takeaways
- The Vegetable Variety Navigator (VVN) decision-support tool can help growers better predict crop yield and quality performance. Validation using recent on-farm trial data showed the VVN improved relative yield predictions for broccoli, cucumber, and sweet pepper.
- However, improvements are needed as the difference between observed and predicted yields was over 20% for all crops and prediction methods.
Project Objectives and Approach
Sixteen variety trials of broccoli, cucumber, and sweet pepper were conducted on five eastern Nebraska farms from 2020 to 2022 to evaluate the Vegetable Variety Navigator’s (VVN) ability to predict variety performance. Crops were organically managed (at most sites), and ripe fruit was harvested, sorted, counted, and weighed.
The difference between observed relative yields from these trials and relative yield predictions from VVN data subsets was used to assess VVN accuracy and predictive potential.
Key Findings
- Integrating vegetable variety trial data into a decision-support tool (VVN) can inform expectations for crop yield and quality, especially in regions with limited data. Validation using 284 observations from 2020-2022 trials showed the VVN improved relative yield predictions for broccoli, cucumber, and sweet pepper by 21% to 51%.
- While the VVN increases grower confidence in variety selection, improvements are needed as the difference between observed and predicted yields was over 20% for all crops and prediction methods. Future accuracy enhancements could involve calculating relative yields within and among studies by crop type and environment.
- Regional-specific variety trial data is valuable for cucumbers, but not necessarily for broccoli or sweet pepper. The current Variety Variety Navigator (VVN) uses aridity index and soil texture for data filtering, but clustering data by climatic or geographic zones may improve yield predictions, especially for cucumbers. Citizen-science and crowd-sourced approaches may be more sustainable for generating region-specific data. Future VVN development will aim to integrate qualitative and quantitative data for more robust predictions.
Location
NebraskaCollaborators
Caleb Wehrbein, University of Nebraska, Lincoln
Region
Plains
Topic
Plant Breeding, Varieties, and Seeds
Category
Vegetables/Fruits
Year Published
2024
