Analysis of the Similarity between in Silico Ideotypes and Phenotypic Profiles to Support Cultivar Recommendation—A Case Study on <i>Phaseolus vulgaris</i> L.
Cultivar recommendation is a key factor in cropping system management. Classical approaches based on comparative multi-environmental trials can hardly explore the agro-climatic and management heterogeneity farmers may have to face. Moreover, they struggle to keep up with the number of genotypes comm...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-11-01
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| Series: | Agronomy |
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| Online Access: | https://www.mdpi.com/2073-4395/10/11/1733 |
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| author | Livia Paleari Fosco M. Vesely Riccardo A. Ravasi Ermes Movedi Sofia Tartarini Mattia Invernizzi Roberto Confalonieri |
| author_facet | Livia Paleari Fosco M. Vesely Riccardo A. Ravasi Ermes Movedi Sofia Tartarini Mattia Invernizzi Roberto Confalonieri |
| author_sort | Livia Paleari |
| collection | DOAJ |
| description | Cultivar recommendation is a key factor in cropping system management. Classical approaches based on comparative multi-environmental trials can hardly explore the agro-climatic and management heterogeneity farmers may have to face. Moreover, they struggle to keep up with the number of genotypes commercially released each year. We propose a new approach based on the integration of in silico ideotyping and functional trait profiling, with the common bean (<i>Phaseoulus vulgaris</i> L.) in Northern Italy as a case study. Statistical distributions for six functional traits (light extinction coefficient, radiation use efficiency, thermal time to first pod and maturity, seed weight, plant height) were derived for 24 bean varieties. The analysis of soil, climate and management in the study area led us to define 21 homogeneous contexts, for which ideotypes were identified using the crop model STICS (Simulateur mulTIdisciplinaire pour les Cultures Standard), the E-FAST (Extended Fourier Amplitude Sensitivity Test) sensitivity analysis method, and the distributions of functional traits. For each context, the 24 cultivars were ranked according to the similarity (weighted Euclidean distance) with the ideotype. Context-specific ideotypes mainly differed for phenological adaptation to specific combinations of climate and management (sowing time) factors, and this reflected in the cultivar recommendation for the different contexts. Feedbacks from bean technicians in the study area confirmed the reliability of the results and, in turn, of the proposed methodology. |
| first_indexed | 2024-03-10T15:01:58Z |
| format | Article |
| id | doaj.art-3b5ffb0b1dff43f99e6748c569a9b442 |
| institution | Directory Open Access Journal |
| issn | 2073-4395 |
| language | English |
| last_indexed | 2024-03-10T15:01:58Z |
| publishDate | 2020-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Agronomy |
| spelling | doaj.art-3b5ffb0b1dff43f99e6748c569a9b4422023-11-20T20:06:43ZengMDPI AGAgronomy2073-43952020-11-011011173310.3390/agronomy10111733Analysis of the Similarity between in Silico Ideotypes and Phenotypic Profiles to Support Cultivar Recommendation—A Case Study on <i>Phaseolus vulgaris</i> L.Livia Paleari0Fosco M. Vesely1Riccardo A. Ravasi2Ermes Movedi3Sofia Tartarini4Mattia Invernizzi5Roberto Confalonieri6Cassandra Lab, Department of Environmental Science and Policy, Università degli Studi di Milano, via Celoria 2, 20133 Milan, ItalyCassandra Lab, Department of Environmental Science and Policy, Università degli Studi di Milano, via Celoria 2, 20133 Milan, ItalyCassandra Lab, Department of Environmental Science and Policy, Università degli Studi di Milano, via Celoria 2, 20133 Milan, ItalyCassandra Lab, Department of Environmental Science and Policy, Università degli Studi di Milano, via Celoria 2, 20133 Milan, ItalyCassandra Lab, Department of Environmental Science and Policy, Università degli Studi di Milano, via Celoria 2, 20133 Milan, ItalyCassandra Lab, Department of Environmental Science and Policy, Università degli Studi di Milano, via Celoria 2, 20133 Milan, ItalyCassandra Lab, Department of Environmental Science and Policy, Università degli Studi di Milano, via Celoria 2, 20133 Milan, ItalyCultivar recommendation is a key factor in cropping system management. Classical approaches based on comparative multi-environmental trials can hardly explore the agro-climatic and management heterogeneity farmers may have to face. Moreover, they struggle to keep up with the number of genotypes commercially released each year. We propose a new approach based on the integration of in silico ideotyping and functional trait profiling, with the common bean (<i>Phaseoulus vulgaris</i> L.) in Northern Italy as a case study. Statistical distributions for six functional traits (light extinction coefficient, radiation use efficiency, thermal time to first pod and maturity, seed weight, plant height) were derived for 24 bean varieties. The analysis of soil, climate and management in the study area led us to define 21 homogeneous contexts, for which ideotypes were identified using the crop model STICS (Simulateur mulTIdisciplinaire pour les Cultures Standard), the E-FAST (Extended Fourier Amplitude Sensitivity Test) sensitivity analysis method, and the distributions of functional traits. For each context, the 24 cultivars were ranked according to the similarity (weighted Euclidean distance) with the ideotype. Context-specific ideotypes mainly differed for phenological adaptation to specific combinations of climate and management (sowing time) factors, and this reflected in the cultivar recommendation for the different contexts. Feedbacks from bean technicians in the study area confirmed the reliability of the results and, in turn, of the proposed methodology.https://www.mdpi.com/2073-4395/10/11/1733variety choicecrop modellingSTICSE-FAST sensitivity analysis methodyield stabilityparameter distributions |
| spellingShingle | Livia Paleari Fosco M. Vesely Riccardo A. Ravasi Ermes Movedi Sofia Tartarini Mattia Invernizzi Roberto Confalonieri Analysis of the Similarity between in Silico Ideotypes and Phenotypic Profiles to Support Cultivar Recommendation—A Case Study on <i>Phaseolus vulgaris</i> L. Agronomy variety choice crop modelling STICS E-FAST sensitivity analysis method yield stability parameter distributions |
| title | Analysis of the Similarity between in Silico Ideotypes and Phenotypic Profiles to Support Cultivar Recommendation—A Case Study on <i>Phaseolus vulgaris</i> L. |
| title_full | Analysis of the Similarity between in Silico Ideotypes and Phenotypic Profiles to Support Cultivar Recommendation—A Case Study on <i>Phaseolus vulgaris</i> L. |
| title_fullStr | Analysis of the Similarity between in Silico Ideotypes and Phenotypic Profiles to Support Cultivar Recommendation—A Case Study on <i>Phaseolus vulgaris</i> L. |
| title_full_unstemmed | Analysis of the Similarity between in Silico Ideotypes and Phenotypic Profiles to Support Cultivar Recommendation—A Case Study on <i>Phaseolus vulgaris</i> L. |
| title_short | Analysis of the Similarity between in Silico Ideotypes and Phenotypic Profiles to Support Cultivar Recommendation—A Case Study on <i>Phaseolus vulgaris</i> L. |
| title_sort | analysis of the similarity between in silico ideotypes and phenotypic profiles to support cultivar recommendation a case study on i phaseolus vulgaris i l |
| topic | variety choice crop modelling STICS E-FAST sensitivity analysis method yield stability parameter distributions |
| url | https://www.mdpi.com/2073-4395/10/11/1733 |
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