TRACES OF GLYPHOSATE IN CORN (Zea mays L.) AND AVOCADO (Persea americana Mill.) WEEDS SUPPORTED BY VANT AND RAMAN SPECTROSCOPY

Abstract

Since the 1990s, radiometric and biophotonic sensor applications have provided reliable alternatives and rapid non-invasive diagnostics for the detection and delimitation of pests and diseases, as well as pesticide traces. Active sensors have been shown to be more accurate in detecting the heterogeneity of environmental factors based on thermal and infrared characteristics, chlorophyll fluorescence, and plant reflectance. Unmanned Aerial Vehicles (UAVs) equipped with infrared cameras locate and delimit weed abundance and diversity using Normalized Difference Vegetation Index (NDVI) algorithms, which highlight heterogeneous chlorophyll activity and herbicide-limited photosynthesis in crops. The resulting map serves as the foundation for collecting plant samples. In this study, the technology of these sensors was applied to determine glyphosate traces using Raman spectroscopy, which allowed a quick, low-cost, simple, and practical diagnosis with immediate results. These are essential characteristics for surveillance and monitoring activities, as well as the basis for a geo-referenced inventory of pesticides in production units. Of the 44 weed samples collected, eight were positive for glyphosate traces: two in corn and six in avocado. Weeds are identified as positive to glyphosate traces in Raman spectroscopy in the carotenoid and phenylpropanoid reduction ranges (1186 and 1213 cm-1) as a result of a decrease in the immune response. The vibrations presented by the amines in glyphosate and the C-OH of the carboxyl group are detected in the range of 1565 and 1567 cm-1.