Networking 13 Berry Minerals to Sustain a High Yield of Firm Cranberry Fruits
Leon Etienne Parent
The N fertilization to reach high cranberry (<i>Vaccinium macrocarpon</i>) yields resulted in high proportions of soft berries. Our objective was to define the mineral nutrient balance of cranberry to reach a high yield of firm berries. The database comprised 393 observations on <i>cv</i>. ‘Stevens’. Berries were analyzed for total S, N, P, K, Ca, Mg, B, Cu, Zn, Mn, Fe, Al, and Si. Random Forest and XGBoost machine learning models were run to predict yield and firmness classes using raw concentrations, centered log ratios (<i>clr</i>) accounting for nutrient interactions, and weighted log ratios (<i>wlr</i>) that also considered the importance of each dual interaction. The <i>wlr</i> returned the most accurate models. The <i>wlr</i> standards elaborated from the high-yielding and nutritionally balanced subpopulation most often differed between the high-yield class and the high-firmness class. The <i>wlr</i> Cu level was significantly (<i>p</i> ≤ 0.01) too high to reach the high-yielding class in the nutritionally imbalanced subpopulation. There was excessive Al and shortage of Si and Mg to reach high berry firmness in the nutritionally imbalanced subpopulation (<i>p</i> ≤ 0.01), indicating the large influence of soil genesis on berry firmness. Despite statistical evidence, cranberry response to Al and Si corrective measures should be tested to elaborate site-specific recommendations based on soil and tissue tests.
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