PreprintArticleVersion 1Preserved in Portico This version is not peer-reviewed
Evaluation of Image-Based Phenotyping Methods for Measuring Water Yam (Dioscorea alata L.) Growth and Nitrogen Nutritional Status under Greenhouse and Field Conditions
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. Agronomy2021, 11, 249.
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.
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. Agronomy2021, 11, 249.
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.
Abstract
Management practices must be developed to improve yam production sustainability. Image-based phenotyping techniques could help developing such practices based on non-destructive analyses of important plant traits. Our objective was to determine the potential of image-based phenotyping methods to assess traits relevant for tuber yield formation in yam grown in glasshouse and 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 plant nitrogen (N) nutritional status. Under glasshouse conditions, the number of pixels obtained from nadir view (image taken top down) was positively correlated to the shoot biomass, and the total leaf surface, while the TGI was negatively correlated to the N content of diagnostic leaves. Under field conditions, pictures taken from the nadir view showed an increase in soil surface cover and a decrease in TGI with time. TGI was negatively correlated to SPAD measured on specific leaves but was not correlated to the N content of these leaves. In conclusion, these phenotyping techniques deliver relevant results but need to be further developed and validated for application in yam.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.