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Agronomy
Volume 15
Issue 5
10.3390/agronomy15051140
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Correction to Agronomy 2022, 12(12), 3194.
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Correction

Correction: Di et al. A New Framework for Winter Wheat Yield Prediction Integrating Deep Learning and Bayesian Optimization. Agronomy 2022, 12, 3194

by
Yan Di
1,2,
Maofang Gao
1,2,*,
Fukang Feng
1,2,
Qiang Li
1,2 and
Huijie Zhang
3,*
1
Key Laboratory of Agricultural Remote Sensing, Ministry of Agriculture and Rural Affairs, Beijing 100081, China
2
Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China
3
Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China
*
Authors to whom correspondence should be addressed.
Agronomy 2025, 15(5), 1140; https://doi.org/10.3390/agronomy15051140
Submission received: 26 March 2025 / Accepted: 21 April 2025 / Published: 7 May 2025
(This article belongs to the Section Precision and Digital Agriculture)
Versions Notes

Text Correction

There was an error in the original publication [1]. In Section 3.3, the formula for R2 was incorrectly presented.
A correction has been made to 3. Methodology, 3.3. Model Performance Evaluation, Paragraph 1:
R 2 = 1 − ∑ i = 1 n     ( y i − o i ) 2 ∑ i = 1 n     ( y i − y ‾ ) 2
The wrong statement in the same section should also be corrected.
Wrong statement: “R2 is a measure of the strength of the linear relationship between the predicted and measured values of the model, with larger R2 indicating that the measured and predicted values have similar trends.”
Modified statement: “R2 measures how well a model explains the variance in the dependent variable, with higher values indicating a better fit.”
The authors state that the scientific conclusions are unaffected. This correction was approved by the Academic Editor. The original publication has also been updated.

Reference

  1. Di, Y.; Gao, M.; Feng, F.; Li, Q.; Zhang, H. A New Framework for Winter Wheat Yield Prediction Integrating Deep Learning and Bayesian Optimization. Agronomy 2022, 12, 3194. [Google Scholar] [CrossRef]
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Share and Cite

MDPI and ACS Style

Di, Y.; Gao, M.; Feng, F.; Li, Q.; Zhang, H. Correction: Di et al. A New Framework for Winter Wheat Yield Prediction Integrating Deep Learning and Bayesian Optimization. Agronomy 2022, 12, 3194. Agronomy 2025, 15, 1140. https://doi.org/10.3390/agronomy15051140

AMA Style

Di Y, Gao M, Feng F, Li Q, Zhang H. Correction: Di et al. A New Framework for Winter Wheat Yield Prediction Integrating Deep Learning and Bayesian Optimization. Agronomy 2022, 12, 3194. Agronomy. 2025; 15(5):1140. https://doi.org/10.3390/agronomy15051140

Chicago/Turabian Style

Di, Yan, Maofang Gao, Fukang Feng, Qiang Li, and Huijie Zhang. 2025. "Correction: Di et al. A New Framework for Winter Wheat Yield Prediction Integrating Deep Learning and Bayesian Optimization. Agronomy 2022, 12, 3194" Agronomy 15, no. 5: 1140. https://doi.org/10.3390/agronomy15051140

APA Style

Di, Y., Gao, M., Feng, F., Li, Q., & Zhang, H. (2025). Correction: Di et al. A New Framework for Winter Wheat Yield Prediction Integrating Deep Learning and Bayesian Optimization. Agronomy 2022, 12, 3194. Agronomy, 15(5), 1140. https://doi.org/10.3390/agronomy15051140

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