Predicting weed and lowbush blueberry biomass using the point intercept method | Zendy

Josée-Anne Lévesque | Zendy; Robert L. Bradley | Zendy; Mireille Bellemare | Zendy; Jean Lafond | Zendy; Maxime C. Paré | Zendy

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Predicting weed and lowbush blueberry biomass using the point intercept method

Author(s) -

Josée-Anne Lévesque,

Robert L. Bradley,

Mireille Bellemare,

Jean Lafond,

Maxime C. Paré

Publication year - 2018

Publication title -

canadian journal of plant science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.338

H-Index - 59

eISSN - 1918-1833

pISSN - 0008-4220

DOI - 10.1139/cjps-2017-0201

Subject(s) - biomass (ecology) , weed , yield (engineering) , crop , sampling (signal processing) , agronomy , environmental science , horticulture , biology , computer science , materials science , filter (signal processing) , metallurgy , computer vision

Lowbush blueberry is an important crop in the Saguenay–Lac-Saint-Jean region of Quebec. Accurate evaluation of agronomic practices currently requires destructive sampling and loss of productive fields. We showed that the point intercept method is a rapid and reliable nondestructive alternative for predicting biomass and yield of lowbush blueberry and competing species.

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