Building Variable Productivity Ratios for Improving Large Scale Spatially Explicit Pruning Biomass Assessments

Abstract

Biomass assessments of agro–residues performed at large geographical scales generally base calculations on single constant pruning productivity ratios (RSRs). Reliability of biomass assessments shall be improved if RSRs respond to prevailing regional crop growing conditions. The present paper describes the methodology applied to create geographically varying pruning RSR ratios–tons of dry matter per hectare—for five crop groups: vineyard, olive, fruit species, citrus and dry fruits. A newly created database containing 230 records–from seven EU28 countries—is submitted to statistical analysis. Results reveal that agro-climatic conditions are able to explain a not negligible share of the pruning productivity as dependent variable. Subsequent regression analysis provides two equations—for vineyard and citrus—achieving a reasonable good fitting (R2 0.18 and 0.42 respectively) between RSR and the agroclimatic variables. Analysis of olive, fruit species and dry fruits scatter and whisker plots were useful for zoning and inducing ramp functions. A Geographical Information System (GIS) was utilised to apply the functions to the agroclimatic raster coverages in order to obtain RSR raster grids. Zonal statistic procedures applied by European regional units (NUTs0, NUTs2, NUTs3) provide a specific crop RSR ratio per administrative unit as a principal output of the present work.

Keywords

• pruning
• biomass
• resources assessment
• regression analysis
• geographical information systems