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Article

Evaluation of Image-Based Phenotyping Methods for Measuring Water Yam (Dioscorea alata L.) Growth and Nitrogen Nutritional Status under Greenhouse and Field Conditions

1
Group of Plant Nutrition, Institute of Agricultural Sciences, ETH Zurich, 8315 Zurich, Switzerland
2
Group of Crop Science, Institute of Agricultural Sciences, ETH Zurich, 8092 Zurich, Switzerland
3
Agroecology and Environment, Agroscope, 8046 Zurich, Switzerland
4
Centre Suisse de Recherches Scientifiques, 01 BP 1303 Abidjan, Cote D’Ivoire
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Département d’Agrophysiologie des Plantes, Université Peleforo Gon Coulibaly, BP 1328 Korhogo, Cote D’Ivoire
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Institut de l’Environnement et Recherches Agricoles, 04 BP 8645 Ouagadougou, Burkina Faso
7
Laboratory of Plant Physiology, Université Félix Houphouët Boigny, 01 BP V34 Abidjan, Cote D’Ivoire
*
Author to whom correspondence should be addressed.
Both authors contributed equally to this work.
Academic Editor: Andreas Stahl
Agronomy 2021, 11(2), 249; https://doi.org/10.3390/agronomy11020249
Received: 12 December 2020 / Revised: 18 January 2021 / Accepted: 26 January 2021 / Published: 29 January 2021
New management practices must be developed to improve yam productivity. By allowing non-destructive analyses of important plant traits, image-based phenotyping techniques could help developing such practices. Our objective was to determine the potential of image-based phenotyping methods to assess traits relevant for tuber yield formation in yam grown in the glasshouse and in the field. We took plant and leaf pictures with consumer cameras. We used the numbers of image pixels to derive the shoot biomass and the total leaf surface and calculated the ‘triangular greenness index’ (TGI) which is an indicator of the leaf chlorophyll content. Under glasshouse conditions, the number of pixels obtained from nadir view (view from the top) was positively correlated to shoot biomass, and total leaf surface, while the TGI was negatively correlated to the SPAD values and nitrogen (N) content of diagnostic leaves. Pictures taken from nadir view in the field showed an increase in soil surface cover and a decrease in TGI with time. TGI was negatively correlated to SPAD values measured on diagnostic leaves but was not correlated to leaf N content. In conclusion, these phenotyping techniques deliver relevant results but need to be further developed and validated for application in yam. View Full-Text
Keywords: leaf surface; soil surface cover; growth rate; nitrogen leaf content; SPAD; triangular greenness index (TGI) leaf surface; soil surface cover; growth rate; nitrogen leaf content; SPAD; triangular greenness index (TGI)
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MDPI and ACS Style

Frossard, E.; Liebisch, F.; Hgaza, V.K.; Kiba, D.I.; Kirchgessner, N.; Müller, L.; Müller, P.; Pouya, N.; Ringger, C.; Walter, A. Evaluation of Image-Based Phenotyping Methods for Measuring Water Yam (Dioscorea alata L.) Growth and Nitrogen Nutritional Status under Greenhouse and Field Conditions. Agronomy 2021, 11, 249. https://doi.org/10.3390/agronomy11020249

AMA Style

Frossard E, Liebisch F, Hgaza VK, Kiba DI, Kirchgessner N, Müller L, Müller P, Pouya N, Ringger C, Walter A. Evaluation of Image-Based Phenotyping Methods for Measuring Water Yam (Dioscorea alata L.) Growth and Nitrogen Nutritional Status under Greenhouse and Field Conditions. Agronomy. 2021; 11(2):249. https://doi.org/10.3390/agronomy11020249

Chicago/Turabian Style

Frossard, Emmanuel, Frank Liebisch, Valérie Kouamé Hgaza, Delwendé Innocent Kiba, Norbert Kirchgessner, Laurin Müller, Patrick Müller, Nestor Pouya, Cecil Ringger, and Achim Walter. 2021. "Evaluation of Image-Based Phenotyping Methods for Measuring Water Yam (Dioscorea alata L.) Growth and Nitrogen Nutritional Status under Greenhouse and Field Conditions" Agronomy 11, no. 2: 249. https://doi.org/10.3390/agronomy11020249

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