Publicação
Previsão de produção da casta Touriga Franca na Região do Douro com base nas componentes de rendimento
| Resumo: | Yield predicting is a great advantage for winegrowers' competitiveness. To determine which variables explain most of the yield's variation at harvest in a Touriga Franca parcel at Quinta do Vale D. Maria (Douro), a sample of 98 grapevines was selected and its yield components studied through2013. Using an 18 grapevine subsample, 3 yield predicting models were achieved. The first uses "bunch number/vine", "average stem weight/bunch", "berry weight/spur" and "average berry number/ bunch" and explains 92% of yield variation per vine with the smallest statistical deviation measures, offering the best quality estimate. The second uses "fertility index/spur" and "bunch number" to explain 73% of yield variation per vine, with intermediate deviation measures. The third model allows a yield estimate through bunch number per vine, with a R2 of 0,72 , but higher deviation measures than the previous one. The last two models are determined through observation, avoiding bunch destruction. The choice of which model to use depends on the quality of the estimate and the practicality desired by the winegrower. This work showed good results relating to yield predicting for Touriga Franca, a poorly studied variety despite its importance in Douro. The implementing of these procedures will enable production control in the biggest parcel in Quinta do Vale D. Maria. |
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| Autores principais: | Lima, Isabel Maria Sarmento de Beires de Abreu e |
| Assunto: | Vitis vinifera Touriga Franca Douro yield prediction yield components |
| Ano: | 2014 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade de Lisboa |
| Idioma: | português |
| Origem: | Repositório da Universidade de Lisboa |
| Resumo: | Yield predicting is a great advantage for winegrowers' competitiveness. To determine which variables explain most of the yield's variation at harvest in a Touriga Franca parcel at Quinta do Vale D. Maria (Douro), a sample of 98 grapevines was selected and its yield components studied through2013. Using an 18 grapevine subsample, 3 yield predicting models were achieved. The first uses "bunch number/vine", "average stem weight/bunch", "berry weight/spur" and "average berry number/ bunch" and explains 92% of yield variation per vine with the smallest statistical deviation measures, offering the best quality estimate. The second uses "fertility index/spur" and "bunch number" to explain 73% of yield variation per vine, with intermediate deviation measures. The third model allows a yield estimate through bunch number per vine, with a R2 of 0,72 , but higher deviation measures than the previous one. The last two models are determined through observation, avoiding bunch destruction. The choice of which model to use depends on the quality of the estimate and the practicality desired by the winegrower. This work showed good results relating to yield predicting for Touriga Franca, a poorly studied variety despite its importance in Douro. The implementing of these procedures will enable production control in the biggest parcel in Quinta do Vale D. Maria. |
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