@inproceedings{b008a4ef52a44aa0b34c1e5cd3ba4637,
title = "Early detection of corn and sunflower stress induced by chemical spraying",
abstract = "Herbicides inhibit plant growth by affecting different bio-chemical pathways or bio-physical states. Stress that was induced by inhibiting lipid metabolism or photosynthesis on corn and sunflower was detected using leaf spectral reflectance. Leaf spectral signatures were measured at six time points during two weeks by a spectro-radiometer. Phenotypes were evaluated by an expert at the same time points. Spectral processing models were used to compare the spectral response of a control group to treated plants using statistical T-tests. Results revealed that spectral reflectance can be used to detect the stress induced by inhibiting photosynthesis on corn and sunflower at the same time that the first visual symptoms appeared. Also, early detection can be accomplished with a lower confidence two days before visual symptoms appear.",
keywords = "Detection, Herbicides, Leaf, Spectrometry",
author = "S. Gad and Y. Edan and T. Sandovsky and I. Harary and T. Nacson and E. Kosover and {Levi Bar Shalom}, A. and V. Alchanatis",
note = "Publisher Copyright: {\textcopyright} Wageningen Academic Publishers 2019; 12th European Conference on Precision Agriculture, ECPA 2019 ; Conference date: 08-07-2019 Through 11-07-2019",
year = "2019",
month = jan,
day = "1",
doi = "10.3920/978-90-8686-888-9_34",
language = "American English",
series = "Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019",
publisher = "Wageningen Academic Publishers",
pages = "279--285",
editor = "Stafford, {John V.}",
booktitle = "Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019",
address = "Netherlands",
}