Articles
Applications of radiative transfer models to greenhouse vegetation
Article number
1296_46
Pages
357 – 362
Language
English
Abstract
In greenhouse horticulture, efficiency of climate control and plant protection can be improved by having an accurate impression of plant status, such as photosynthesis or chemical composition.
Recent advances in remote sensing technologies have brought about a range of innovations in precision agriculture, with the potential for adaptation to greenhouses.
Simple, traditionally used indices employ only one or two spectral bands, in which the contributions of various pigments and leaf or canopy structure can highly overlap.
Consequently, such indices may be insufficient for applications.
State-of-the-art models have been developed that can better interpret hyper- and multispectral leaf and canopy imagery by employing the biochemical and radiative transfer properties of vegetation.
An example is the soil-canopy observation of photosynthesis and energy balance (SCOPE) model, which was developed specifically for crop canopies.
Here we present one of the pillars of SCOPE, the leaf radiative transfer (RT) model Fluspect.
Fluspect simulates leaf chlorophyll fluorescence, reflectance and transmittance spectra.
The model can be inverted to obtain estimates of leaf chlorophylls, carotenoids, anthocyanins, xanthophyll epoxidation, water and dry matter content.
Moreover, it can be linked to a model for leaf photosynthesis and when inverted, provide a method to estimate photosynthesis directly from leaf spectral information.
We test the model against a tomato data set, with measured hyperspectral images, chlorophyll, sugar, acid, starch, dry matter content and nutrients.
The first study of the data set, using partial least square regression, showed that hyperspectral images have a high correlation with important fruit and leaf compounds.
We compared these results to Fluspect retrievals and conventional vegetation indices.
In the paper, we discuss the potential added value of using RT models in greenhouse horticulture.
Recent advances in remote sensing technologies have brought about a range of innovations in precision agriculture, with the potential for adaptation to greenhouses.
Simple, traditionally used indices employ only one or two spectral bands, in which the contributions of various pigments and leaf or canopy structure can highly overlap.
Consequently, such indices may be insufficient for applications.
State-of-the-art models have been developed that can better interpret hyper- and multispectral leaf and canopy imagery by employing the biochemical and radiative transfer properties of vegetation.
An example is the soil-canopy observation of photosynthesis and energy balance (SCOPE) model, which was developed specifically for crop canopies.
Here we present one of the pillars of SCOPE, the leaf radiative transfer (RT) model Fluspect.
Fluspect simulates leaf chlorophyll fluorescence, reflectance and transmittance spectra.
The model can be inverted to obtain estimates of leaf chlorophylls, carotenoids, anthocyanins, xanthophyll epoxidation, water and dry matter content.
Moreover, it can be linked to a model for leaf photosynthesis and when inverted, provide a method to estimate photosynthesis directly from leaf spectral information.
We test the model against a tomato data set, with measured hyperspectral images, chlorophyll, sugar, acid, starch, dry matter content and nutrients.
The first study of the data set, using partial least square regression, showed that hyperspectral images have a high correlation with important fruit and leaf compounds.
We compared these results to Fluspect retrievals and conventional vegetation indices.
In the paper, we discuss the potential added value of using RT models in greenhouse horticulture.
Publication
Authors
N. Vilfan, J.A. Dieleman, A. Elings, G. Polder
Keywords
hyperspectral imagery, leaf reflectance, Fluspect, pigment content, tomato
Groups involved
- Division Precision Horticulture and Engineering
- Division Greenhouse and Indoor Production Horticulture
- Working Group Organic Greenhouse Horticulture
- Working Group Protected Cultivation, Nettings and Screens for Mild Climates
- Working Group Light in Horticulture
- Working Group Vegetable Grafting
- Working Group Computational Fluid Dynamics in Agriculture
- Working Group Mechanization, Digitization, Sensing and Robotics
- Working Group Modelling Plant Growth, Environmental Control, Greenhouse Environment
- Working Group Greenhouse Environment and Climate Control
- Working Group Design and Automation in Integrated Indoor Production Systems
- Commission Agroecology and Organic Farming Systems
- Division Landscape and Urban Horticulture
Online Articles (148)