Methods to optimize optical sensing of biotic plant stress - combined effects of hyperspectral imaging at night and spatial binning.

In spatio-temporal plant monitoring, optical sensing (including hyperspectral imaging), is being deployed to, non-invasively, detect and diagnose plant responses to abiotic and biotic stressors. Early and accurate detection and diagnosis of stressors are key objectives. Level of radiometric repeatability of optical sensing data and ability to accurately detect and diagnose biotic stress are inversely correlated.

Compatibility of synthetic and biological pesticides with a biocontrol agent Phytoseiulus longipes (Acari: Phytoseiidae).

Phytoseiulus longipes is a predatory mite of Tetranychus evansi, which is an invasive pest in Africa and elsewhere. The introduction of this predator in Africa has considerable potential, but little is known about the compatibility of P. longipes with commonly used pesticides.

Calibration to maximize temporal radiometric repeatability of airborne hyperspectral imaging data.

Many studies provide insight into calibration of airborne remote sensing data but very few specifically address the issue of temporal radiometric repeatability. In this study, we acquired airborne hyperspectral optical sensing data from experimental objects (white Teflon and colored panels) during 52 flight missions on three separate days. Data sets were subjected to four radiometric calibration methods: no radiometric calibration (radiance data), empirical line method calibration based on white calibration boards (ELM calibration), and two atmospheric radiative transfer model calibrations: 1) radiometric calibration with irradiance data acquired with a drone-mounted down-welling sensor (ARTM), and 2) modeled sun parameters and weather variables in combination with irradiance data from drone-mounted down-welling sensor (ARTM+).

Modeling and validation of oviposition by a polyphagous insect pest as a function of temperature and host plant species.

Modeling oviposition as a function of female insect age, temperature, and host plant suitability may provide valuable insight into insect population growth of polyphagous insect pests at a landscape level. In this study, we quantified oviposition by beet leafhoppers, Circulifer (= Neoaliturus) tenellus (Baker) (Hemiptera: Cicadellidae), on four common non-agricultural host plant species [Erodium cicutarium (L.) L'Hér.

Data-driven vermiculite distribution modelling for UAV-based precision pest management.

In recent decades, unmanned aerial vehicles (UAVs) have gained considerable popularity in the agricultural sector, in which UAV-based actuation is used to spray pesticides and release biological control agents. A key challenge in such UAV-based actuation is to account for wind speed and UAV flight parameters to maximize precision-delivery of pesticides and biological control agents. This paper describes a data-driven framework to predict density distribution patterns of vermiculite dispensed from a hovering UAV as a function of UAV's movement state, wind condition, and dispenser setting.