Soybean Aphid (Hemiptera: Aphididae) Affects Soybean Spectral Reflectance.

Soybean aphid, Aphis glycines Matsumura (Hemiptera: Aphididae), is the most economically important insect pest of soybean in the north central United States. Scouting-based integrated pest management (IPM) programs could become more efficient and more widely adopted by using plant spectral reflectance to estimate soybean aphid injury. Our objective was to determine whether plant spectral reflectance is affected by soybean aphid feeding. Field trials were conducted in 2013 and 2014 using caged plots. Early-, late-, and noninfested treatments were established to create a gradient of soybean aphid pressure. Whole-plant soybean aphid densities were recorded weekly. Measurements of plant spectral reflectance occurred on two sample dates per year. Simple linear regression models were used to test the effect of cumulative aphid-days (CAD) on plant spectral reflectance at 680 nm (RED) and 800 nm (NIR), normalized difference vegetation index (NDVI), and relative chlorophyll content. Data indicated that CAD had no effect on canopy-level RED reflectance, but CAD decreased canopy-level NIR reflectance and NDVI. Canopy- and leaf-level measurements typically indicated similar plant spectral response to increasing CAD. CAD generally had no effect on relative chlorophyll content. The present study provides the first documentation that remote sensing holds potential for detecting changes in plant spectral reflectance induced by soybean aphid. The use of plant spectral reflectance in soybean aphid management may assist future IPM programs to reduce sampling costs and prevent prophylactic insecticide sprays.

Linear Support Vector Machine Classification of Plant Stress From Soybean Aphid (Hemiptera: Aphididae) Using Hyperspectral Reflectance.

Spectral remote sensing has the potential to improve scouting and management of soybean aphid (Aphis glycines Matsumura), which can cause yield losses of over 40% in the North Central Region of the United States. We used linear support vector machines (SVMs) to determine 1) whether hyperspectral samples could be classified into treat/no-treat classes based on the economic threshold (250 aphids per plant) and 2) how many wavelengths or features are needed to generate an accurate model without overfitting the data. A range of aphid infestation levels on soybean was created using caged field plots in 2013, 2014, 2017, and 2018 in Minnesota and in 2017 and 2018 in Iowa. Hyperspectral measurements of soybean canopies in each plot were recorded with a spectroradiometer. SVM training and testing were performed using 15 combinations of normalized canopy reflectance at wavelengths of 720, 750, 780, and 1,010 nm. Pairwise Bonferroni-adjusted t-tests of Cohen's kappa values showed four wavelength combinations were optimal, namely model 1 (780 nm), model 2 (780 and 1,010 nm), model 3 (780, 1,010, and 720 nm), and model 4 (780, 1,010, 720, and 750 nm). Model 2 showed the best overall performance, with an accuracy of 89.4%, a sensitivity of 81.2%, and a specificity of 91.6%. The findings from this experiment provide the first documentation of successful classification of remotely sensed spectral data of soybean aphid-induced stress into threshold-based classes.

Optimizing band selection for spectral detection of Aphis glycines Matsumura in soybean.

BACKGROUND: Soybean aphid, Aphis glycines Matsumura (Hemiptera: Aphididae), is a significant insect pest of soybean in North America. Accurate estimation of A. glycines densities requires costly, time-intensive weekly counts of adults and nymphs on plants. Field studies were conducted in 2013 and 2014 to assess the potential for spectral-based remote sensing to more efficiently quantify cumulative aphid-days (CADs) using soybean canopy reflectance. RESULTS: Narrow-band wavelengths in the near-infrared spectral range were associated with CAD, but those in the visible spectral range were not associated with CAD. Simple linear regression models of CAD on reflectance were generally better than quadratic and cubic regression models. Simulated wide-band sensors centered at 740-1100 nm yielded better regression models than ones centered at 600-740 nm, regardless of bandwidth. Among the simulated wide-band sensors, increasing sensor bandwidth worsened CAD estimation or required more simulated sensors to optimize CAD estimation. Optimal combinations of spectral bands explained 83-96% of the experimentally manipulated variation in CAD. CONCLUSION: Near-infrared wavelengths at 780 ± 50 nm can effectively estimate A. glycines abundance on soybean. Our approach of simulating wide-band multispectral sensors from ground-based hyperspectral data helped to refine spectral sensors and holds potential to reduce the cost and complexity of treat/no-treat classification tasks. This study will contribute to future research aiming to quantify insect injury using customized commercial-grade sensors for detection, quantification, and differentiation of A. glycines from other stressors. © 2018 Society of Chemical Industry.

Effects of Foliar Insecticides on Leaf-Level Spectral Reflectance of Soybean.

Pest-induced changes in plant reflectance are crucial for the development of pest management programs using remote sensing. However, it is unknown if plant reflectance data is also affected by foliar insecticides applied for pest management. Our study assessed the effects of foliar insecticides on leaf reflectance of soybean. A 2-yr field trial and a greenhouse trial were conducted using randomized complete block and completely randomized designs, respectively. Treatments consisted of an untreated check, a new systemic insecticide (sulfoxaflor), and two representatives of the most common insecticide classes used for soybean pest management in the north-central United States (i.e., λ-cyhalothrin and chlorpyrifos). Insecticides were applied at labeled rates recommended for controlling soybean aphid; the primary insect pest in the north-central United States. Leaf-level reflectance was measured using ground-based spectroradiometers. Sulfoxaflor affected leaf reflectance at some red and blue wavelengths but had no effect at near-infrared or green wavelengths. Chlorpyrifos affected leaf reflectance at some green, red, and near-infrared wavelengths but had no effect at blue wavelengths. λ-cyhalothrin had the least effect on spectral reflectance among the insecticides, with changes to only a few near-infrared wavelengths. Our results showing immediate and delayed effects of foliar insecticides on soybean reflectance indicate that application of some insecticides may confound the use of remote sensing for detection of not only insects but also plant diseases, nutritional and water deficiencies, and other crop stressors.

Potential for Sulfoxaflor to Improve Conservation Biological Control of Aphis glycines (Hemiptera: Aphididae) in Soybean.

Soybean aphid, Aphis glycines Matsumura, is one of the most important insect pests of soybean in the north central United States. Management of A. glycines currently relies on applications of broad-spectrum insecticides. However, broad-spectrum insecticides can negatively impact the natural enemies associated with aphids. Selective insecticides, on the other hand, are promising control tactics for reducing the negative impact of insecticide applications. Here, we compared the effects of sulfoxaflor (a new selective insecticide) and broad-spectrum insecticides on A. glycines and predators in a two-year field experiment. We sampled A. glycines and aphid predator populations using visual whole-plant inspection. In addition, sweep-net sampling was performed to monitor predator populations. To evaluate the toxicity of the insecticides on predator populations, laboratory bioassays were performed on Hippodamia convergens Guérin-Méneville, Orius insidiosus (Say), and Chrysoperla rufilabris (Burmeister). Field results showed that sulfoxaflor was as effective as the broad-spectrum insecticide in suppressing soybean aphid populations and was less impactful on predator populations. The laboratory bioassays showed that sulfoxaflor was moderately harmful to O. insidiosus, harmless to slightly harmful to H. convergens, and harmless to C. rufilabris These studies suggest that sulfoxaflor holds promise for improving integration of chemical and biological controls for A. glycines management.

Spatial Distribution and Coexisting Patterns of Adults and Nymphs of Tibraca limbativentris (Hemiptera: Pentatomidae) in Paddy Rice Fields.

The rice stem stink bug, Tibraca limbativentris Stål (Hemiptera: Pentatomidae), is a primary insect pest of paddy rice in South America. Knowledge of its spatial distribution can support sampling plans needed for timely decisions about pest control. This study aimed to investigate the spatial distribution of adults and nymphs of T. limbativentris and determine the spatial coexistence of these stages of development. Fifteen paddy rice fields were scouted once each season to estimate insect densities. Scouting was performed on regular grids with sampling points separated by ∼50 m. Moran's I and semivariograms were used to determine spatial distribution patterns. Spatial coexistence of nymphs and adults was explored via spatial point process. Here, adults and nymphs had typically contrasting spatial distribution patterns within the same field; however, the frequency of aggregation was not different between these developmental stages. Adults and nymphs were aggregated in seven fields and randomly distributed in the other eight fields. Uniform distribution of adults or nymphs was not observed. The study-wide semivariogram ranges were ∼40 m for adults and ∼55 m for nymphs. Nymphs and adults spatially coexisted on 67% of the fields. Coexisting patterns were classified using one of the following processes: stage-independent, bidirectional attractive, unidirectional attractive, bidirectional inhibiting, or unidirectional inhibiting. The information presented herein can be important for developing sampling plans for decision-making, implementing tactics for site-specific management, and monitoring areas free of T. limbativentris.

O percevejo-do-colmo Tibraca limbativentris Stål (Hemiptera: Pentatomidae) é uma praga primária na cultura do arroz irrigado na América do Sul. O conhecimento de sua distribuição espacial é essencial para desenvolver planos de amostragem e para o controle desta praga. Nosso objetivo foi investigar a distribuição espacial de adultos e ninfas de T. limbativentris e determinar a coexistência espacial entre os estágios de desenvolvimento. As densidades de adultos e ninfas foram estimadas em quinze campos de arroz irrigado. A amostragem foi realizada em grades regulares com pontos de amostragem separados por ∼50 m. Moran's I e semivariogramas foram usados para determinar os padrões de distribuição espacial. A coexistência espacial foi explorada pela análise de processos pontuais. Foi observado que adultos e ninfas tiveram padrões contrastantes de distribuição espacial dentro do mesmo campo; no entanto, a frequência de agregação não foi diferente entre esses estágios de desenvolvimento. Adultos e ninfas estavam agregados em sete campos e distribuídos aleatoriamente nos outros oito campos. Não foi observada a distribuição uniforme de adultos ou ninfas. O alcance médio dos semivariogramas foi de ∼40 m para os adultos e ∼55 m para as ninfas. Ninfas e adultos coexistiram espacialmente em 67% dos campos. Os padrões de coexistência foram classificados usando um dos seguintes processos: independente do estágio de desenvolvimento, atração bilateral, atração unilateral, inibição bilateral, ou inibição unilateral. Nosso estudo poderá contribuir para o desenvolvimento de planos de amostragem para tomada de decisão e implementação de táticas para o manejo de sítios específicos.