Hyperspectral technologies for assessing seed germination and Trifloxysulfuron-Methyl response in amaranthus palmeri (Palmer amaranth)

Maor Matzrafi, Ittai Herrmann, Christian Nansen, Tom Kliper, Yotam Zait, Timea Ignat, Dana Siso, Baruch Rubin, Arnon Karnieli, Hanan Eizenberg*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

29 Scopus citations


Weed infestations in agricultural systems constitute a serious challenge to agricultural sustainability and food security worldwide. Amaranthus palmeri S. Watson (Palmer amaranth) is one of the most noxious weeds causing significant yield reductions in various crops. The ability to estimate seed viability and herbicide susceptibility is a key factor in the development of a long-term management strategy, particularly since the misuse of herbicides is driving the evolution of herbicide response in various weed species. The limitations of most herbicide response studies are that they are conducted retrospectively and that they use in vitro destructive methods. Development of a non-destructive method for the prediction of herbicide response could vastly improve the efficacy of herbicide applications and potentially delay the evolution of herbicide resistance. Here, we propose a toolbox based on hyperspectral technologies and data analyses aimed to predict A. palmeri seed germination and response to the herbicide trifloxysulfuron-methyl. Complementary measurement of leaf physiological parameters, namely, photosynthetic rate, stomatal conductence and photosystem II efficiency, was performed to support the spectral analysis. Plant response to the herbicide was compared to image analysis estimates using mean gray value and area fraction variables. Hyperspectral reflectance profiles were used to determine seed germination and to classify herbicide response through examination of plant leaves. Using hyperspectral data, we have successfully distinguished between germinating and non-germinating seeds, hyperspectral classification of seeds showed accuracy of 81.9 and 76.4%, respectively. Sensitive and resistant plants were identified with high degrees of accuracy (88.5 and 90.9%, respectively) from leaf hyperspectral reflectance profiles acquired prior to herbicide application. A correlation between leaf physiological parameters and herbicide response (sensitivity/resistance) was also demonstrated. We demonstrated that hyperspectral reflectance analyses can provide reliable information about seed germination and levels of susceptibility in A. palmeri. The use of reflectance-based analyses can help to better understand the invasiveness of A. palmeri, and thus facilitate the development of targeted control methods. It also has enormous potential for impacting environmental management in that it can be used to prevent ineffective herbicide applications. It also has potential for use in mapping tempo-spatial population dynamics in agro-ecological landscapes.

Original languageAmerican English
Article number474
JournalFrontiers in Plant Science
StatePublished - 3 Apr 2017

Bibliographical note

Publisher Copyright:
© 2017 Matzrafi, Herrmann, Nansen, Kliper, Zait, Ignat, Siso, Rubin, Karnieli and Eizenberg.


  • Herbicide resistance evolution
  • Hyperspectral imaging and sensing
  • Precision agriculture
  • Proximal sensing
  • Trifloxysulfuron-methyl


Dive into the research topics of 'Hyperspectral technologies for assessing seed germination and Trifloxysulfuron-Methyl response in amaranthus palmeri (Palmer amaranth)'. Together they form a unique fingerprint.

Cite this