Articles
Cranberry elemental balances impact fruit yield and firmness
Article number
1440_4
Pages
29 – 36
Language
English
Abstract
Cranberry (Vaccinium macrocarpon Ait.) is an acid-loving plant grown primarily in acidic sandy soils.
Nitrogen (N) is a key nutrient in commercial cranberry production, increasing berry yield while decreasing berry firmness.
Nitrogen must be properly balanced with other tissue components to reach high berry yield and sufficient firmness.
This is problematic especially in organic farming where partially mineralized N from organic fertilization can show carryover effects.
The objective of this paper was to determine the nutrient balance required to reach high cranberry yield and firmness.
We collected 364 observations in field trials where N, P, K, Mg, Cu, and B were varied.
Nutrients were expressed as centered log ratios to represent nutrient balances across pairwise interactions.
The k-nearest-neighbors machine learning model classified berry yield and firmness in relation with berry mineral composition expressed as centered log ratio balances, the farming system and temperature in September.
Specimens showing high berry yield and firmness were delineated in the confusion matrix as those producing more than 40 Mg ha‑1 and those showing resistance to penetration exceeding 6 N mm‑1. The k-nearest-neighbors model returned area under the receiver operating characteristic curve of 0.766 for yield and 0.938 for firmness.
The B, Fe, and Al balances impacted berry yield and firmness more than other elemental balances.
The B strengthens tissue structure, can immobilize Al in roots and could reduce pest damage in interaction with Fe.
We suggest clr balance ranges to reach high berry yield and firmness concomitantly.
Depending on cranberry sorbitol content and phenological stage, boron fertilization could improve berry firmness in both organic and conventional farming systems.
Nitrogen (N) is a key nutrient in commercial cranberry production, increasing berry yield while decreasing berry firmness.
Nitrogen must be properly balanced with other tissue components to reach high berry yield and sufficient firmness.
This is problematic especially in organic farming where partially mineralized N from organic fertilization can show carryover effects.
The objective of this paper was to determine the nutrient balance required to reach high cranberry yield and firmness.
We collected 364 observations in field trials where N, P, K, Mg, Cu, and B were varied.
Nutrients were expressed as centered log ratios to represent nutrient balances across pairwise interactions.
The k-nearest-neighbors machine learning model classified berry yield and firmness in relation with berry mineral composition expressed as centered log ratio balances, the farming system and temperature in September.
Specimens showing high berry yield and firmness were delineated in the confusion matrix as those producing more than 40 Mg ha‑1 and those showing resistance to penetration exceeding 6 N mm‑1. The k-nearest-neighbors model returned area under the receiver operating characteristic curve of 0.766 for yield and 0.938 for firmness.
The B, Fe, and Al balances impacted berry yield and firmness more than other elemental balances.
The B strengthens tissue structure, can immobilize Al in roots and could reduce pest damage in interaction with Fe.
We suggest clr balance ranges to reach high berry yield and firmness concomitantly.
Depending on cranberry sorbitol content and phenological stage, boron fertilization could improve berry firmness in both organic and conventional farming systems.
Publication
Authors
R. Jamaly, S.É. Parent, N. Ziadi, L.E. Parent
Keywords
aluminum, boron, iron, machine learning, nutrient diagnosis
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