Performance of LAI-2200 Plant Canopy Analyzer on Leaf Area Index of Jatropha Nut Estimation

Lena, Bruno Patias; Folegatti, M.V.; Francisco, João Paulo; Santos, Otávio Neto Almeida; Andrade, I.P.S.

doi:10.3923/ja.2016.191.197

Cited by 6 publications

(2 citation statements)

References 13 publications

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“…Significant scientific effort (e.g. Calders et al., 2018; Goude et al., 2019; Lena et al., 2016) has sought to investigate and quantify variation between direct and indirect methods of estimating canopy parameters, across a range of canopy types, although uncertainties still exist. Working at a similar site to ours, Calders et al.…”

Section: Introductionmentioning

confidence: 99%

A Raspberry Pi‐based camera system and image processing procedure for low cost and long‐term monitoring of forest canopy dynamics

2021

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Section: Introductionmentioning

confidence: 99%

A Raspberry Pi‐based camera system and image processing procedure for low cost and long‐term monitoring of forest canopy dynamics

2021

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“…Electronic analyzers based on gap fraction or transmittance have been widely used to evaluate crops such as corn (Zea mays L.) (Ariza-Carricondo et al, 2019), sugarcane (Saccharum officinarum L.) (Lisboa et al, 2018), acid lime [Citrus latifolia (Yu.Tanaka) Tanaka] (Coelho Filho et al, 2012), and soybean [Glycine max (L.) Merr.] (Malone et al, 2002;Pierozan Junior & Kawakami, 2013;Mbangiwa et al, 2019), as well as isolated plants of jatropha (Jatropha curcas L.) (Lena et al, 2016) and eucalyptus (Eucalyptus urophylla x grandis) plantations (Giunti Neto et al, 2015). However, in all these studies, the authors reported the need for calibration to improve the quality of the data gathered with those devices, but did not consider canopy height as an auxiliary variable.…”

Section: Introductionmentioning

confidence: 99%

Improving indirect measurements of the leaf area index using canopy height

Gonçalves

Silva

Gasparotto

et al. 2020

Pesq. agropec. bras.

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The objective of this work was to evaluate the use of plant height as a calibration variable for improving indirect measurements of the leaf area index (LAI). Three experiments were conducted with different crops - corn (Zea mays), soybean (Glycine max), and sugarcane (Saccharum officinarum) -, to compare the performance of the LAI measured indirectly (LAIind) and corrected by the calibration variable with the LAI measured directly (LAIref). Without the proposed correction, the LAIind tended to be overestimated by 20%, on average, compared with the LAIref, for the three crops. After crop height was used to adjust the LAIind, a strong positive relationship was observed between the LAIref and the corrected LAIind (R2 = 0.96); overestimation was reduced to 4% and the root-mean-square error decreased to 0.35 m2 m-2. The variable canopy height is promising for the correction of the LAI of the soybean, corn, and sugarcane crops.

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Estimating the leaf area index of bell peppers according to growth stage using ray-tracing simulation and a long short-term memory algorithm

Lee

Kang

Moon

et al. 2020

Hortic. Environ. Biotechnol.

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Performance of LAI-2200 Plant Canopy Analyzer on Leaf Area Index of Jatropha Nut Estimation

Cited by 6 publications

References 13 publications

A Raspberry Pi‐based camera system and image processing procedure for low cost and long‐term monitoring of forest canopy dynamics

A Raspberry Pi‐based camera system and image processing procedure for low cost and long‐term monitoring of forest canopy dynamics

Improving indirect measurements of the leaf area index using canopy height

Estimating the leaf area index of bell peppers according to growth stage using ray-tracing simulation and a long short-term memory algorithm

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