LRES Seminar Series presents Ricardo Lima, Ph.D student Sao Paulo State University- Brazil
- Monday, February 22, 2021 at 1:10pm
"An integrated approach to quantifying plant stress for assessing yield loss potential in wheat stem sawfly infested wheat fields"
Wheat stem sawfly (WSS), Cephus cinctus Norton, is a major pest of cereal crops grown in the Northern Great Plains of North America. Annually, WSS causes losses that have been estimated at US $44–80 million in Montana. During the larval stage, WSS larvae consume parenchymous tissue lining the stem interior and this feeding disrupts the physiological capacity of the infested stem, leading to a reduction in height, reduced seed weight, and lower grain quality. Essentially the only reliable way to confirm a sawfly infestation is by dissecting stems and checking for larval presence and injury. However, performing this practice to quantify infestation over large areas is extremely laborious and not really achievable. So, with technological developments in agriculture in recent years, and because plant biotic stress due to herbivores generally results in changes in leaf reflectance, remotely sensed data have shown promising results by providing valuable information on defining the status and severity of pest infestations. Therefore, our objective was to develop methodology based on the spectral reflectance profile of infested spring wheat (Triticum aestivum L.) plants, to evaluate the severity of WSS injury. To accomplish this, we performed multiple greenhouse and field studies. First, we characterized the primary metabolic response and reflectance profile of wheat plants infested by WSS. Next, we quantified infestation at multiple sampling points (N=145) in a commercial wheat field near Big Sandy, Montana. For this, we analyzed a series of multispectral satellite images and ground reference hyperspectral data to characterize WSS infestation. We used a random forest supervised classification model to predict a relationship between the vegetation index GNDVI and WSS infestation patterns (75 % overall accuracy). Our study, using remotely sensed data, reports an improved methodology with potential to quantify landscape-level severity of WSS infestation.
Host: Dr. Cathy Zabinski
Msc. José Ricardo Lima Pinto, PhD Student
Engenheiro Agrônomo (Agronomist Engineer)
Doutorando em Agronomia - Entomologia Agrícola (PhD Student in Agricultural Entomology)
Departamento de Ciências da Produção Agrícola (Department of Agricultural Production Sciences)
FCAV/UNESP (São Paulo State University) 14884-900 JABOTICABAL, SP, Brasil (Brazil)
Phone number: +55 16 3209 7861 (Ofice)
- Department of Land Resources and Environmental Sciences