Defining the Ideal Phenological Stage for Estimating Corn Yield Using Multispectral Images
Image-based spectral models assist in estimating the yield of maize. During the vegetative and reproductive phenological phases, the corn crop undergoes changes caused by biotic and abiotic stresses. These variations can be quantified using spectral models, which are tools that help producers to man...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-09-01
|
| Series: | Agronomy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4395/13/9/2390 |
| _version_ | 1797581653597487104 |
|---|---|
| author | Carlos Alberto Matias de Abreu Júnior George Deroco Martins Laura Cristina Moura Xavier João Vitor Meza Bravo Douglas José Marques Guilherme de Oliveira |
| author_facet | Carlos Alberto Matias de Abreu Júnior George Deroco Martins Laura Cristina Moura Xavier João Vitor Meza Bravo Douglas José Marques Guilherme de Oliveira |
| author_sort | Carlos Alberto Matias de Abreu Júnior |
| collection | DOAJ |
| description | Image-based spectral models assist in estimating the yield of maize. During the vegetative and reproductive phenological phases, the corn crop undergoes changes caused by biotic and abiotic stresses. These variations can be quantified using spectral models, which are tools that help producers to manage crops. However, defining the correct time to obtain these images remains a challenge. In this study, the possibility to estimate corn yield using multispectral images is hypothesized, while considering the optimal timing for detecting the differences caused by various phenological stages. Thus, the main objective of this work was to define the ideal phenological stage for taking multispectral images to estimate corn yield. Multispectral bands and vegetation indices derived from the Planet satellite were considered as predictor variables for the input data of the models. We used root mean square error percentage and mean absolute percentage error to evaluate the accuracy and trend of the yield estimates. The reproductive phenological phase R2 was found to be optimal for determining the spectral models based on the images, which obtained the best root mean square error percentage of 9.17% and the second-best mean absolute percentage error of 7.07%. Here, we demonstrate that it is possible to estimate yield in a corn plantation in a stage before the harvest through Planet multispectral satellite images. |
| first_indexed | 2024-03-10T23:07:35Z |
| format | Article |
| id | doaj.art-817dc65f065c4c2d846d1ef9e146dec8 |
| institution | Directory Open Access Journal |
| issn | 2073-4395 |
| language | English |
| last_indexed | 2024-03-10T23:07:35Z |
| publishDate | 2023-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Agronomy |
| spelling | doaj.art-817dc65f065c4c2d846d1ef9e146dec82023-11-19T09:11:36ZengMDPI AGAgronomy2073-43952023-09-01139239010.3390/agronomy13092390Defining the Ideal Phenological Stage for Estimating Corn Yield Using Multispectral ImagesCarlos Alberto Matias de Abreu Júnior0George Deroco Martins1Laura Cristina Moura Xavier2João Vitor Meza Bravo3Douglas José Marques4Guilherme de Oliveira5Institute of Agrarian Sciences, Federal University of Uberlândia, Monte Carmelo 38500-000, BrazilInstitute of Agrarian Sciences, Federal University of Uberlândia, Monte Carmelo 38500-000, BrazilInstitute of Agrarian Sciences, Federal University of Uberlândia, Monte Carmelo 38500-000, BrazilInstitute of Geography, Federal University of Uberlândia, Monte Carmelo 38500-000, BrazilInstitute of Agrarian Sciences, Federal University of Uberlândia, Monte Carmelo 38500-000, BrazilLallemand Soluções Biológicas LTDA, Patos de Minas 38706-420, BrazilImage-based spectral models assist in estimating the yield of maize. During the vegetative and reproductive phenological phases, the corn crop undergoes changes caused by biotic and abiotic stresses. These variations can be quantified using spectral models, which are tools that help producers to manage crops. However, defining the correct time to obtain these images remains a challenge. In this study, the possibility to estimate corn yield using multispectral images is hypothesized, while considering the optimal timing for detecting the differences caused by various phenological stages. Thus, the main objective of this work was to define the ideal phenological stage for taking multispectral images to estimate corn yield. Multispectral bands and vegetation indices derived from the Planet satellite were considered as predictor variables for the input data of the models. We used root mean square error percentage and mean absolute percentage error to evaluate the accuracy and trend of the yield estimates. The reproductive phenological phase R2 was found to be optimal for determining the spectral models based on the images, which obtained the best root mean square error percentage of 9.17% and the second-best mean absolute percentage error of 7.07%. Here, we demonstrate that it is possible to estimate yield in a corn plantation in a stage before the harvest through Planet multispectral satellite images.https://www.mdpi.com/2073-4395/13/9/2390corn phenological stagesremote monitoringyield predictionspatial distribution of yield |
| spellingShingle | Carlos Alberto Matias de Abreu Júnior George Deroco Martins Laura Cristina Moura Xavier João Vitor Meza Bravo Douglas José Marques Guilherme de Oliveira Defining the Ideal Phenological Stage for Estimating Corn Yield Using Multispectral Images Agronomy corn phenological stages remote monitoring yield prediction spatial distribution of yield |
| title | Defining the Ideal Phenological Stage for Estimating Corn Yield Using Multispectral Images |
| title_full | Defining the Ideal Phenological Stage for Estimating Corn Yield Using Multispectral Images |
| title_fullStr | Defining the Ideal Phenological Stage for Estimating Corn Yield Using Multispectral Images |
| title_full_unstemmed | Defining the Ideal Phenological Stage for Estimating Corn Yield Using Multispectral Images |
| title_short | Defining the Ideal Phenological Stage for Estimating Corn Yield Using Multispectral Images |
| title_sort | defining the ideal phenological stage for estimating corn yield using multispectral images |
| topic | corn phenological stages remote monitoring yield prediction spatial distribution of yield |
| url | https://www.mdpi.com/2073-4395/13/9/2390 |
| work_keys_str_mv | AT carlosalbertomatiasdeabreujunior definingtheidealphenologicalstageforestimatingcornyieldusingmultispectralimages AT georgederocomartins definingtheidealphenologicalstageforestimatingcornyieldusingmultispectralimages AT lauracristinamouraxavier definingtheidealphenologicalstageforestimatingcornyieldusingmultispectralimages AT joaovitormezabravo definingtheidealphenologicalstageforestimatingcornyieldusingmultispectralimages AT douglasjosemarques definingtheidealphenologicalstageforestimatingcornyieldusingmultispectralimages AT guilhermedeoliveira definingtheidealphenologicalstageforestimatingcornyieldusingmultispectralimages |