Global Wheat Head Detection 2021: An Improved Dataset for Benchmarking Wheat Head Detection Methods

Etienne David^{1

2}, Mario Serouart^{1

2}, Daniel Smith³, Simon Madec^{1

3}, Kaaviya Velumani^{2

4}, Shouyang Liu⁵, Xu Wang⁶, Francisco Pinto⁷, Shahameh Shafiee⁸, Izzat S A Tahir⁹, Hisashi Tsujimoto¹⁰, Shuhei Nasuda¹¹, Bangyou Zheng¹², Norbert Kirchgessner¹³, Helge Aasen¹³, Andreas Hund¹³, Pouria Sadhegi-Tehran¹⁴, Koichi Nagasawa¹⁵, Goro Ishikawa¹⁶, Sébastien Dandrifosse¹⁷, Alexis Carlier¹⁷, Benjamin Dumont¹⁸, Benoit Mercatoris¹⁷, Byron Evers⁶, Ken Kuroki¹⁹, Haozhou Wang¹⁹, Masanori Ishii¹⁹, Minhajul A Badhon²⁰, Curtis Pozniak²¹, David Shaner LeBauer²², Morten Lillemo⁸, Jesse Poland⁶, Scott Chapman^{3

12}, Benoit de Solan¹, Frédéric Baret², Ian Stavness²⁰, Wei Guo¹⁹

Affiliations

¹ Arvalis, Institut du Végétal, 3 Rue Joseph et Marie Hackin, 75116 Paris, France.
² UMR1114 EMMAH, INRAE, Centre PACA, Bâtiment Climat, Domaine Saint-Paul, 228 Route de l'Aérodrome, CS 40509, 84914 Avignon Cedex, France.
³ School of Food and Agricultural Sciences, The University of Queensland, Gatton, 4343 QLD, Australia.
⁴ Hiphen SAS, 120 Rue Jean Dausset, Agroparc, Bâtiment Technicité, 84140 Avignon, France.
⁵ Plant Phenomics Research Center, Nanjing Agricultural University, Nanjing, China.
⁶ Wheat Genetics Resource Center, Dep. of Plant Pathology, Kansas State Univ., 4024 Throckmorton Plant Sciences Center, Manhattan, Kansas, USA.
⁷ Global Wheat Program, International Maize and Wheat Improvement Centre (CIMMYT), Mexico, D.F., Mexico.
⁸ Faculty of Biosciences, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432 Ås, Norway.
⁹ Agricultural Research Corporation, Wheat Research Program, P.O. Box 126, Wad Medani, Sudan.
¹⁰ Arid Land Research Center, Tottori University, Tottori 680-0001, Japan.
¹¹ Laboratories of Plant Genetics and Plant Breeding, Graduate School of Agriculture, Kyoto University, Japan.
¹² CSIRO Agriculture and Food, Queensland Biosciences Precinct, 306 Carmody Road, St Lucia, 4067 QLD, Australia.
¹³ Institute of Agricultural Sciences, ETH Zurich, Universitätstrasse 2, 8092 Zurich, Switzerland.
¹⁴ Plant Sciences Department, Rothamsted Research, Harpenden, UK.
¹⁵ Institute of Crop Science, National Agriculture and Food Research Organization, Japan.
¹⁶ Hokkaido Agricultural Research Center, National Agriculture and Food Research Organization, Japan.
¹⁷ Biosystems Dynamics and Exchanges, TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium.
¹⁸ Plant Sciences, TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium.
¹⁹ Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Midori-cho, Nishitokyo City, Tokyo, Japan.
²⁰ Department of Computer Science, University of Saskatchewan, Canada.
²¹ Department of Plant Sciences, University of Saskatchewan, Canada.
²² College of Agriculture and Life Sciences, University of Arizona, Tucson, Arizona, USA.

PMID: 34778804
PMCID: PMC8548052
DOI: 10.34133/2021/9846158

Global Wheat Head Detection 2021: An Improved Dataset for Benchmarking Wheat Head Detection Methods

Etienne David et al. Plant Phenomics. 2021.

. 2021 Sep 22:2021:9846158.

doi: 10.34133/2021/9846158. eCollection 2021.

Authors

Affiliations

¹ Arvalis, Institut du Végétal, 3 Rue Joseph et Marie Hackin, 75116 Paris, France.
² UMR1114 EMMAH, INRAE, Centre PACA, Bâtiment Climat, Domaine Saint-Paul, 228 Route de l'Aérodrome, CS 40509, 84914 Avignon Cedex, France.
³ School of Food and Agricultural Sciences, The University of Queensland, Gatton, 4343 QLD, Australia.
⁴ Hiphen SAS, 120 Rue Jean Dausset, Agroparc, Bâtiment Technicité, 84140 Avignon, France.
⁵ Plant Phenomics Research Center, Nanjing Agricultural University, Nanjing, China.
⁶ Wheat Genetics Resource Center, Dep. of Plant Pathology, Kansas State Univ., 4024 Throckmorton Plant Sciences Center, Manhattan, Kansas, USA.
⁷ Global Wheat Program, International Maize and Wheat Improvement Centre (CIMMYT), Mexico, D.F., Mexico.
⁸ Faculty of Biosciences, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432 Ås, Norway.
⁹ Agricultural Research Corporation, Wheat Research Program, P.O. Box 126, Wad Medani, Sudan.
¹⁰ Arid Land Research Center, Tottori University, Tottori 680-0001, Japan.
¹¹ Laboratories of Plant Genetics and Plant Breeding, Graduate School of Agriculture, Kyoto University, Japan.
¹² CSIRO Agriculture and Food, Queensland Biosciences Precinct, 306 Carmody Road, St Lucia, 4067 QLD, Australia.
¹³ Institute of Agricultural Sciences, ETH Zurich, Universitätstrasse 2, 8092 Zurich, Switzerland.
¹⁴ Plant Sciences Department, Rothamsted Research, Harpenden, UK.
¹⁵ Institute of Crop Science, National Agriculture and Food Research Organization, Japan.
¹⁶ Hokkaido Agricultural Research Center, National Agriculture and Food Research Organization, Japan.
¹⁷ Biosystems Dynamics and Exchanges, TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium.
¹⁸ Plant Sciences, TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium.
¹⁹ Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Midori-cho, Nishitokyo City, Tokyo, Japan.
²⁰ Department of Computer Science, University of Saskatchewan, Canada.
²¹ Department of Plant Sciences, University of Saskatchewan, Canada.
²² College of Agriculture and Life Sciences, University of Arizona, Tucson, Arizona, USA.

PMID: 34778804
PMCID: PMC8548052
DOI: 10.34133/2021/9846158

Abstract

The Global Wheat Head Detection (GWHD) dataset was created in 2020 and has assembled 193,634 labelled wheat heads from 4700 RGB images acquired from various acquisition platforms and 7 countries/institutions. With an associated competition hosted in Kaggle, GWHD_2020 has successfully attracted attention from both the computer vision and agricultural science communities. From this first experience, a few avenues for improvements have been identified regarding data size, head diversity, and label reliability. To address these issues, the 2020 dataset has been reexamined, relabeled, and complemented by adding 1722 images from 5 additional countries, allowing for 81,553 additional wheat heads. We now release in 2021 a new version of the Global Wheat Head Detection dataset, which is bigger, more diverse, and less noisy than the GWHD_2020 version.

PubMed Disclaimer

Conflict of interest statement

The authors declare that there is no conflict of interest regarding the publication of this article.

Figures

**Figure 1**
Sample images of the Global Wheat Head Detection 2021. The blue boxes correspond to the interactively labeled heads.

**Figure 2**
Distribution of the development stage. The x-axis presents the number of subdataset per development stage.

**Figure 3**
Distribution of the images in the two first dimensions defined by the UMAP algorithm for the GWHD 2021 dataset. The additional subdatasets as well as the training and test datasets from GWHD_2020 are represented by colors.

See this image and copyright information in PMC

References

1. Sambasivan N., Kapania S., Highfill H., Akrong D., Paritosh P., Aroyo L. M. Everyone wants to do the model work, not the data work: data cascades in high-stakes AI. New York, NY, USA: 2021. - DOI
1. Deng J., Dong W., Socher R., Li L.-J., Li K., Fei-Fei L. ImageNet: a large-scale hierarchical image database. 2009 IEEE Conference on Computer Vision and Pattern Recognition; 2009; pp. 248–255.
1. Lin T.-Y., et al. Microsoft coco: common objects in context. European conference on computer vision. 2014. pp. 740–755.
1. Cruz J. A., Yin X., Liu X., et al. Multi-modality imagery database for plant phenotyping. Machine Vision and Applications. 2016;27(5):735–749. doi: 10.1007/s00138-015-0734-6. - DOI
1. Guo W., Zheng B., Potgieter A. B., et al. Aerial imagery analysis – quantifying appearance and number of sorghum heads for applications in breeding and agronomy. Frontiers in Plant Science. 2018;9:p. 1544. doi: 10.3389/fpls.2018.01544. - DOI - PMC - PubMed

LinkOut - more resources

Full Text Sources

Save citation to file

Email citation

Add to Collections

Add to My Bibliography

Your saved search

Create a file for external citation management software

Your RSS Feed

Global Wheat Head Detection 2021: An Improved Dataset for Benchmarking Wheat Head Detection Methods

Affiliations

Global Wheat Head Detection 2021: An Improved Dataset for Benchmarking Wheat Head Detection Methods

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

References

LinkOut - more resources

Full Text Sources