Estimating hard winter wheat yield with historical and novel methods

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Main Authors: Maria C. M. Sciencia, Cody F. Creech, Katherine A. Frels, Amanda C. Easterly
Format: Artículo Open Access
Published: Wiley 2025
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author Maria C. M. Sciencia
Cody F. Creech
Katherine A. Frels
Amanda C. Easterly
author_facet Maria C. M. Sciencia
Cody F. Creech
Katherine A. Frels
Amanda C. Easterly
Maria C. M. Sciencia
Cody F. Creech
Katherine A. Frels
Amanda C. Easterly
collection Wiley Open Access
contents Estimating hard winter wheat yield with historical and novel methods Maria C. M. Sciencia Cody F. Creech Katherine A. Frels Amanda C. Easterly Agronomy Journal AbstractEstimating potential crop yield during the growing season allows growers to adjust inputs, set reasonable harvest expectations, and guide marketing decisions. Therefore, the ability to estimate yield is a valuable yet difficult goal for growers. To evaluate the potential of several methods of wheat (Triticum aestivum L.) grain yield prediction, this experiment used published methods based on phenological characteristics: stand and tiller/spike counts, and newer methods that employ image‐ and reflectance‐based approaches, such as fractional green canopy cover (FGCC) and normalized difference vegetation index (NDVI) readings. This experiment was conducted across six locations (Banner, Box Butte, Cheyenne, Intensively Managed at Cheyenne, Deuel, and Kimball counties) in western Nebraska during 2019–2020, 2020–2021, and 2021–2022 for a total of 11 site‐years. Treatments consisted of seven winter wheat varieties that were evaluated in the Winter Wheat State Variety Trials. Stand count did not show a significant correlation with wheat yield (0.09) nor model fit for yield estimation. Spike count was significantly correlated with yield (0.54), but efforts to use it to estimate final yield were not significant. Due to the inconsistency of yield prediction with historical methods, analyses of novel methods of yield estimation were warranted. NDVI and FGCC readings correlate with wheat yield and model fit efforts were successful. NDVI at Feekes 10 correlated significantly at 0.39, while FGCC had correlations of 0.56, 0.50, and 0.68 at Feekes 2, 4, and 10 (respectively). This experiment suggests that NDVI and FGCC are methods that could be used to replace outdated and laborious approaches. 10.1002/agj2.70021 http://creativecommons.org/licenses/by/4.0/
doi_str_mv 10.1002/agj2.70021
format Artículo Open Access
id wiley_oa_10_1002_agj2_70021
institution Wiley Open Access
license_str_mv http://creativecommons.org/licenses/by/4.0/
publishDate 2025
publisher Wiley
record_format wiley_oa
spellingShingle Estimating hard winter wheat yield with historical and novel methods
Maria C. M. Sciencia
Cody F. Creech
Katherine A. Frels
Amanda C. Easterly
Agronomy Journal
Estimating hard winter wheat yield with historical and novel methods Maria C. M. Sciencia Cody F. Creech Katherine A. Frels Amanda C. Easterly Agronomy Journal AbstractEstimating potential crop yield during the growing season allows growers to adjust inputs, set reasonable harvest expectations, and guide marketing decisions. Therefore, the ability to estimate yield is a valuable yet difficult goal for growers. To evaluate the potential of several methods of wheat (Triticum aestivum L.) grain yield prediction, this experiment used published methods based on phenological characteristics: stand and tiller/spike counts, and newer methods that employ image‐ and reflectance‐based approaches, such as fractional green canopy cover (FGCC) and normalized difference vegetation index (NDVI) readings. This experiment was conducted across six locations (Banner, Box Butte, Cheyenne, Intensively Managed at Cheyenne, Deuel, and Kimball counties) in western Nebraska during 2019–2020, 2020–2021, and 2021–2022 for a total of 11 site‐years. Treatments consisted of seven winter wheat varieties that were evaluated in the Winter Wheat State Variety Trials. Stand count did not show a significant correlation with wheat yield (0.09) nor model fit for yield estimation. Spike count was significantly correlated with yield (0.54), but efforts to use it to estimate final yield were not significant. Due to the inconsistency of yield prediction with historical methods, analyses of novel methods of yield estimation were warranted. NDVI and FGCC readings correlate with wheat yield and model fit efforts were successful. NDVI at Feekes 10 correlated significantly at 0.39, while FGCC had correlations of 0.56, 0.50, and 0.68 at Feekes 2, 4, and 10 (respectively). This experiment suggests that NDVI and FGCC are methods that could be used to replace outdated and laborious approaches. 10.1002/agj2.70021 http://creativecommons.org/licenses/by/4.0/
title Estimating hard winter wheat yield with historical and novel methods
topic Agronomy Journal
url https://acsess.onlinelibrary.wiley.com/doi/10.1002/agj2.70021