Home > Research > Publications & Outputs > A predictive model of wheat grain yield based o...

Electronic data

Links

Text available via DOI:

View graph of relations

A predictive model of wheat grain yield based on canopy reflectance indices and the theoretical definition of yield potential

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Published

Standard

A predictive model of wheat grain yield based on canopy reflectance indices and the theoretical definition of yield potential. / Pennacchi, João; Virlet, Nicolas; Barbosa, João Paulo Rodrigues Alves Delfino et al.
In: Theoretical and Experimental Plant Physiology, Vol. 34, No. 4, 31.12.2022, p. 537-550.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Pennacchi, J, Virlet, N, Barbosa, JPRAD, Parry, M, Feuerhelm, D, Hawkesford, MJ & Carmo-Silva, E 2022, 'A predictive model of wheat grain yield based on canopy reflectance indices and the theoretical definition of yield potential', Theoretical and Experimental Plant Physiology, vol. 34, no. 4, pp. 537-550. https://doi.org/10.1007/s40626-022-00263-z

APA

Pennacchi, J., Virlet, N., Barbosa, J. P. R. A. D., Parry, M., Feuerhelm, D., Hawkesford, M. J., & Carmo-Silva, E. (2022). A predictive model of wheat grain yield based on canopy reflectance indices and the theoretical definition of yield potential. Theoretical and Experimental Plant Physiology, 34(4), 537-550. https://doi.org/10.1007/s40626-022-00263-z

Vancouver

Pennacchi J, Virlet N, Barbosa JPRAD, Parry M, Feuerhelm D, Hawkesford MJ et al. A predictive model of wheat grain yield based on canopy reflectance indices and the theoretical definition of yield potential. Theoretical and Experimental Plant Physiology. 2022 Dec 31;34(4):537-550. Epub 2022 Nov 9. doi: 10.1007/s40626-022-00263-z

Author

Pennacchi, João ; Virlet, Nicolas ; Barbosa, João Paulo Rodrigues Alves Delfino et al. / A predictive model of wheat grain yield based on canopy reflectance indices and the theoretical definition of yield potential. In: Theoretical and Experimental Plant Physiology. 2022 ; Vol. 34, No. 4. pp. 537-550.

Bibtex

@article{c91b33ca0008484bb5ef4227055903b4,
title = "A predictive model of wheat grain yield based on canopy reflectance indices and the theoretical definition of yield potential",
abstract = "Predicting crop yields through simple methods would be helpful for crop breeding programs and could be deployed at farm level to achieve accurate crop management practices. This research proposes a new method for predicting wheat grain yieldsthroughout the crop growth cycle based on canopy cover (CC) and reflectance indices, named Yield p Model. The model was evaluated by comparing grain yields with the outputs of the proposed model using phenotypic data collected for a wheat population grown under field conditions for the 2015 and 2016 seasons. Accumulated radiation (RAD), Normalized Difference Vegetation Index (NDVI), Photochemical Reflectance Index (PRI), Water Index (WI), Harvest Index (HI) and CC indices were the components of the model. We found that the biomass accumulation predicted by the model was responsive throughout the crop cycle and the grain yield predicted was correlated to measured grain yield. The model was able to early predict grain yield based on biomass accumulated at anthesis. Evaluation of the model components enabled an improved understanding of the main factors limiting yield formation throughout the crop cycle. The proposed Yield p Model explores a new concept of yield modelling and can be the starting point for the development of cheap and robust, on-farm, yield prediction during the crop cycle.",
author = "Jo{\~a}o Pennacchi and Nicolas Virlet and Barbosa, {Jo{\~a}o Paulo Rodrigues Alves Delfino} and Martin Parry and David Feuerhelm and Hawkesford, {Malcolm J.} and Elizabete Carmo-Silva",
year = "2022",
month = dec,
day = "31",
doi = "10.1007/s40626-022-00263-z",
language = "English",
volume = "34",
pages = "537--550",
journal = "Theoretical and Experimental Plant Physiology",
number = "4",

}

RIS

TY - JOUR

T1 - A predictive model of wheat grain yield based on canopy reflectance indices and the theoretical definition of yield potential

AU - Pennacchi, João

AU - Virlet, Nicolas

AU - Barbosa, João Paulo Rodrigues Alves Delfino

AU - Parry, Martin

AU - Feuerhelm, David

AU - Hawkesford, Malcolm J.

AU - Carmo-Silva, Elizabete

PY - 2022/12/31

Y1 - 2022/12/31

N2 - Predicting crop yields through simple methods would be helpful for crop breeding programs and could be deployed at farm level to achieve accurate crop management practices. This research proposes a new method for predicting wheat grain yieldsthroughout the crop growth cycle based on canopy cover (CC) and reflectance indices, named Yield p Model. The model was evaluated by comparing grain yields with the outputs of the proposed model using phenotypic data collected for a wheat population grown under field conditions for the 2015 and 2016 seasons. Accumulated radiation (RAD), Normalized Difference Vegetation Index (NDVI), Photochemical Reflectance Index (PRI), Water Index (WI), Harvest Index (HI) and CC indices were the components of the model. We found that the biomass accumulation predicted by the model was responsive throughout the crop cycle and the grain yield predicted was correlated to measured grain yield. The model was able to early predict grain yield based on biomass accumulated at anthesis. Evaluation of the model components enabled an improved understanding of the main factors limiting yield formation throughout the crop cycle. The proposed Yield p Model explores a new concept of yield modelling and can be the starting point for the development of cheap and robust, on-farm, yield prediction during the crop cycle.

AB - Predicting crop yields through simple methods would be helpful for crop breeding programs and could be deployed at farm level to achieve accurate crop management practices. This research proposes a new method for predicting wheat grain yieldsthroughout the crop growth cycle based on canopy cover (CC) and reflectance indices, named Yield p Model. The model was evaluated by comparing grain yields with the outputs of the proposed model using phenotypic data collected for a wheat population grown under field conditions for the 2015 and 2016 seasons. Accumulated radiation (RAD), Normalized Difference Vegetation Index (NDVI), Photochemical Reflectance Index (PRI), Water Index (WI), Harvest Index (HI) and CC indices were the components of the model. We found that the biomass accumulation predicted by the model was responsive throughout the crop cycle and the grain yield predicted was correlated to measured grain yield. The model was able to early predict grain yield based on biomass accumulated at anthesis. Evaluation of the model components enabled an improved understanding of the main factors limiting yield formation throughout the crop cycle. The proposed Yield p Model explores a new concept of yield modelling and can be the starting point for the development of cheap and robust, on-farm, yield prediction during the crop cycle.

U2 - 10.1007/s40626-022-00263-z

DO - 10.1007/s40626-022-00263-z

M3 - Journal article

VL - 34

SP - 537

EP - 550

JO - Theoretical and Experimental Plant Physiology

JF - Theoretical and Experimental Plant Physiology

IS - 4

ER -