Quality characterisation via image forming methods differentiates grape juice produced from integrated, organic or biodynamic vineyards in the first year after conversion

Abstract

In this study, the effects on grape juice quality resulting from the conversion of vineyard plots from integrated to organic and biodynamic management vs. integrated management were assessed using image forming methods. In addition, grape yield, Botrytis infection and the chemical composition of wood prunings and grapes were assessed. The images of replicate, encoded samples representing five different treatments were: (i) grouped into pairs displaying similar image features, (ii) characterised with respect to the quality domains ‘strength of form expression’ and ‘resistance to deterioration’ and (iii) ranked according to the quality characterisation. Based on the image analyses, all samples pairs were correctly grouped, i.e. the five production methods were precisely separated. The treatments were characterised as follows: (i) Integrated (INT): weakest form expression, most advanced deterioration; (ii) Conversion to Biodynamic without horn silica (BD0): strongest form expression, advanced deterioration; (iii) Conversion to Organic (ORG): weak form expression, low deterioration; (iv) Conversion to Biodynamic with 3 × horn silica (BD3): medium form expression, low deterioration; (v) Conversion to Biodynamic with 4 × horn silica (BD4): strong form expression, low deterioration. Principal component analysis (PCA) of field assessment and chemical analysis data revealed that the two treatments with the strongest form expression, BD0 and BD4, were characterised by high vigour, as indicated by high prune weight and primary amino nitrogen (NOPA). With respect to the resistance to deterioration, as depicted by image forming methods, no parallels were found with PCA.

Keywords:

• Capillary dynamolysis
• biocrystallization
• picture creating methods
• production systems
• biodynamic grape production

Acknowledgements

The authors gratefully acknowledge funding from Software AG Foundation and Damus Foundation, Germany. Statistical analysis guidance by Prof. Dr Hans-Peter Piepho, Bioinformatics Department, Institute of Crop Science, Faculty of Agricultural Sciences, University of Hohenheim, and Stefan Mihalache, Institute of Mathematics, University of Cologne, is kindly appreciated.