Non-destructive estimation of the leaf weight and leaf area in common bean
Regression models to predict leaf area and leaf weight in common bean (Phaseolus vulgaris) were fitted using the three leaflets of the leaves. A total of 1504 leaves from 40 genotypes were collected, covering a large range of leaf sizes. Width, length, area, and weight were measured for each leaflet. The total leaf area and weight was obtained by the sum of left, central, and right leaflets. The dataset was randomly divided into training and validation sets. The training set was used for model fitting and selection, and the validation dataset was used to obtain statistics for model prediction ability. The leaf area and leaf weight were modeled using different linear regression models based on the length and width of the leaflet. Polynomial regressions involving both length and width of the leaflet provided very good models to estimate the expected area (R2 = 0.978) and weight (R2 = 0.820) of leaves.
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Format: | Artículo biblioteca |
Language: | English |
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MDPI
2022
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Subjects: | FRIJOL (PHASEOLUS), COMMON BEANS, PHASEOLUS VULGARIS, SUPERFICIE FOLIAR, LEAF AREA, ANATOMIA DE LA PLANTA, PLANT ANATOMY, LEAF MORPHOLOGY, MODEL VALIDATION, Sede Central, |
Online Access: | https://repositorio.catie.ac.cr/handle/11554/11687 |
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dig-catie-11554-116872023-11-16T16:23:54Z Non-destructive estimation of the leaf weight and leaf area in common bean Suárez Salazar, Juan C. Casanoves, Fernando Di Rienzo, Julio Pasquale Losciale FRIJOL (PHASEOLUS) COMMON BEANS PHASEOLUS VULGARIS PHASEOLUS VULGARIS SUPERFICIE FOLIAR LEAF AREA ANATOMIA DE LA PLANTA PLANT ANATOMY LEAF MORPHOLOGY MODEL VALIDATION Sede Central Regression models to predict leaf area and leaf weight in common bean (Phaseolus vulgaris) were fitted using the three leaflets of the leaves. A total of 1504 leaves from 40 genotypes were collected, covering a large range of leaf sizes. Width, length, area, and weight were measured for each leaflet. The total leaf area and weight was obtained by the sum of left, central, and right leaflets. The dataset was randomly divided into training and validation sets. The training set was used for model fitting and selection, and the validation dataset was used to obtain statistics for model prediction ability. The leaf area and leaf weight were modeled using different linear regression models based on the length and width of the leaflet. Polynomial regressions involving both length and width of the leaflet provided very good models to estimate the expected area (R2 = 0.978) and weight (R2 = 0.820) of leaves. 2022-03-16T19:17:46Z 2022-03-16T19:17:46Z 2022 Artículo https://repositorio.catie.ac.cr/handle/11554/11687 openAccess en Agronomy https://doi.org/10.3390/agronomy12030711 14 páginas application/pdf Basel (Switzerland) MDPI Agronomy; Vol. 12, no. 3 |
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FRIJOL (PHASEOLUS) COMMON BEANS PHASEOLUS VULGARIS PHASEOLUS VULGARIS SUPERFICIE FOLIAR LEAF AREA ANATOMIA DE LA PLANTA PLANT ANATOMY LEAF MORPHOLOGY MODEL VALIDATION Sede Central FRIJOL (PHASEOLUS) COMMON BEANS PHASEOLUS VULGARIS PHASEOLUS VULGARIS SUPERFICIE FOLIAR LEAF AREA ANATOMIA DE LA PLANTA PLANT ANATOMY LEAF MORPHOLOGY MODEL VALIDATION Sede Central |
spellingShingle |
FRIJOL (PHASEOLUS) COMMON BEANS PHASEOLUS VULGARIS PHASEOLUS VULGARIS SUPERFICIE FOLIAR LEAF AREA ANATOMIA DE LA PLANTA PLANT ANATOMY LEAF MORPHOLOGY MODEL VALIDATION Sede Central FRIJOL (PHASEOLUS) COMMON BEANS PHASEOLUS VULGARIS PHASEOLUS VULGARIS SUPERFICIE FOLIAR LEAF AREA ANATOMIA DE LA PLANTA PLANT ANATOMY LEAF MORPHOLOGY MODEL VALIDATION Sede Central Suárez Salazar, Juan C. Casanoves, Fernando Di Rienzo, Julio Non-destructive estimation of the leaf weight and leaf area in common bean |
description |
Regression models to predict leaf area and leaf weight in common bean (Phaseolus vulgaris) were fitted using the three leaflets of the leaves. A total of 1504 leaves from 40 genotypes were collected, covering a large range of leaf sizes. Width, length, area, and weight were measured for each leaflet. The total leaf area and weight was obtained by the sum of left, central, and right leaflets. The dataset was randomly divided into training and validation sets. The training set was used for model fitting and selection, and the validation dataset was used to obtain statistics for model prediction ability. The leaf area and leaf weight were modeled using different linear regression models based on the length and width of the leaflet. Polynomial regressions involving both length and width of the leaflet provided very good models to estimate the expected area (R2 = 0.978) and weight (R2 = 0.820) of leaves. |
author2 |
Pasquale Losciale |
author_facet |
Pasquale Losciale Suárez Salazar, Juan C. Casanoves, Fernando Di Rienzo, Julio |
format |
Artículo |
topic_facet |
FRIJOL (PHASEOLUS) COMMON BEANS PHASEOLUS VULGARIS PHASEOLUS VULGARIS SUPERFICIE FOLIAR LEAF AREA ANATOMIA DE LA PLANTA PLANT ANATOMY LEAF MORPHOLOGY MODEL VALIDATION Sede Central |
author |
Suárez Salazar, Juan C. Casanoves, Fernando Di Rienzo, Julio |
author_sort |
Suárez Salazar, Juan C. |
title |
Non-destructive estimation of the leaf weight and leaf area in common bean |
title_short |
Non-destructive estimation of the leaf weight and leaf area in common bean |
title_full |
Non-destructive estimation of the leaf weight and leaf area in common bean |
title_fullStr |
Non-destructive estimation of the leaf weight and leaf area in common bean |
title_full_unstemmed |
Non-destructive estimation of the leaf weight and leaf area in common bean |
title_sort |
non-destructive estimation of the leaf weight and leaf area in common bean |
publisher |
MDPI |
publishDate |
2022 |
url |
https://repositorio.catie.ac.cr/handle/11554/11687 |
work_keys_str_mv |
AT suarezsalazarjuanc nondestructiveestimationoftheleafweightandleafareaincommonbean AT casanovesfernando nondestructiveestimationoftheleafweightandleafareaincommonbean AT dirienzojulio nondestructiveestimationoftheleafweightandleafareaincommonbean |
_version_ |
1787226194736840704 |