Spectral analysis of winter wheat leaves for detection and differentiation of diseases and insects

By Lin Yuan, Yanbo Huang, R. Loraamm, Chenwei Nie, Jihua Wang, Jingcheng Zhang. 2014

157 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Ecology, Plant Science

View Paper: https://www.semanticscholar.org/paper/e5212b0109eaa918274a6977186bb45a410bf37e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Analytical Chemistry

1. Andrew P. French
2. N. Harrison
3. Amy Lowe
4. Fulya Baysal-Gurel
5. Samuel C. Hassler

In Ecology

1. Andrew P. French
2. N. Harrison
3. Amy Lowe
4. Fulya Baysal-Gurel
5. Samuel C. Hassler

In Plant Science

1. Andrew P. French
2. N. Harrison
3. Amy Lowe
4. Fulya Baysal-Gurel
5. Samuel C. Hassler

Citations in the corpus

• Advanced methods of plant disease detection. A review (2014, unknown): “A study on the differentiation of winter wheat disease due to pathogens (yellow rust, powdery mildew) and insects (wheat aphid) infestation was recently carried out by Yuan et al. (2014).”
• Hyperspectral image analysis techniques for the detection and classification of the early onset of plant disease and stress (2017, methodology): “Partial least square regression (PLSR) Fishers linear determinant analysis Wheat (yellow rust) Wheat (aphid) Wheat (powdery mildew) Wheat (powdery mildew) [36] [37] 92% 60% 90%”