TY - JOUR
T1 - From fluorescence to biomass
T2 - A comprehensive analysis via crop modeling and sensing techniques
AU - Ntakos, Georgios
AU - Prikaziuk, Egor
AU - Vilfan, Nastassia
AU - van der Wal, Tamme
AU - van der Tol, Christiaan
PY - 2025/3
Y1 - 2025/3
N2 - User-friendly handheld plant phenotyping devices, such as the MultispeQ, provide quick and easy measurements that effectively capture the dynamic nature of photosynthesis. This study demonstrates the added value of integrating measurements of such devices with both process-based and empirical modeling approaches for estimating the maximum leaf photosynthetic capacity (Amax) and biomass production (DMP) of potato crops. Utilizing leaf fluorescence measurements, such as the efficiency of photosystem II (ϕ2) and the electron transport rate, gathered from two fields in the Netherlands from May to September 2019, we determined the Amax to be 34 kg CO2 ha−1 hr−1 with a standard deviation of 6.6 kg CO2 ha−1 hr−1. By incorporating dynamic photosynthetic parameters, leaf area index (LAI) retrieval, and crop modeling techniques to scale assimilation from the leaf to the canopy level, we successfully reduced the discrepancy between simulated and measured dry matter production in 16 out of 18 cases, offering significant advantages over fixed, literature-based photosynthetic parameter values.
AB - User-friendly handheld plant phenotyping devices, such as the MultispeQ, provide quick and easy measurements that effectively capture the dynamic nature of photosynthesis. This study demonstrates the added value of integrating measurements of such devices with both process-based and empirical modeling approaches for estimating the maximum leaf photosynthetic capacity (Amax) and biomass production (DMP) of potato crops. Utilizing leaf fluorescence measurements, such as the efficiency of photosystem II (ϕ2) and the electron transport rate, gathered from two fields in the Netherlands from May to September 2019, we determined the Amax to be 34 kg CO2 ha−1 hr−1 with a standard deviation of 6.6 kg CO2 ha−1 hr−1. By incorporating dynamic photosynthetic parameters, leaf area index (LAI) retrieval, and crop modeling techniques to scale assimilation from the leaf to the canopy level, we successfully reduced the discrepancy between simulated and measured dry matter production in 16 out of 18 cases, offering significant advantages over fixed, literature-based photosynthetic parameter values.
KW - Biomass
KW - Crop growth modeling
KW - Fluorescence
KW - MultispeQ
KW - Photosynthesis
KW - Remote sensing
U2 - 10.1016/j.atech.2025.100807
DO - 10.1016/j.atech.2025.100807
M3 - Article
AN - SCOPUS:85216641121
SN - 2772-3755
VL - 10
JO - Smart Agricultural Technology
JF - Smart Agricultural Technology
M1 - 100807
ER -