Comparison of methods for the quantification of botrytis bunch rot in white wine grapes

• G.N. Hill ^[3] ; K.J. Evans ^[1] ; R.M. Beresford ^[3] ; R.G. Dambergs ^[2]
  1. [1] University of Tasmania

     University of Tasmania

     Australia

     
  2. [2] Australian Wine Research Institute

     Australian Wine Research Institute

     Australia

     
  3. [3] The New Zealand Institute for Plant and Food Research Limited

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• Localización: Australian journal of grape and wine research, ISSN 1322-7130, Vol. 20, Nº 3, 2014, págs. 432-441
• Idioma: inglés
• Texto completo no disponible (Saber más ...)
• Dialnet Métricas: 3 Citas
• Resumen

  • Background and Aims Quantification of botrytis bunch rot (BBR) in wine grapes, caused by Botrytis cinerea, is commonly done by visual estimation of the proportion of the area of individual bunches affected by BBR. Visual estimation was compared with four other quantification methods: digital image analysis, near-infrared and mid-infrared spectroscopy, and quantitative real-time polymerase chain reaction.

    Methods and Results Visual estimation was found to vary significantly (P < 0.05) among assessors. Image analysis software (RotBot) was developed to measure BBR severity from digital images of grape bunches. A published quantitative real-time polymerase chain reaction method was modified for use with mature grape berries. All quantification methods showed a significant relationship (P < 0.05) with visual estimation.

    Conclusions Near-infrared and mid-infrared spectroscopy require further calibration to quantify accurately BBR of low severity. Quantitative real-time polymerase chain reaction was the most accurate method but is unsuitable for routine use in the vineyard. RotBot was the most suitable and practical alternative to visual estimation, requiring no specialised equipment.

    Significance of the Study Visual estimation was demonstrated to be prone to assessor bias. RotBot software is a suitable alternative that can be implemented immediately for objective quantification of BBR severity in white wine grapes. RotBot could be developed further and deployed in mobile devices for rapid sensing in the vineyard and easy collection of disease assessment data by wineries.