Plants naturally contain high levels of the stress-responsive fluorophore chlorophyll. Chlorophyll fluorescence imaging (CFI) is a powerful tool to measure photosynthetic efficiency in plants and provides the ability to detect damage from a range of biotic and abiotic stresses before visible symptoms occur. However, most CFI systems are complex, expensive systems that use pulse amplitude modulation (PAM) fluorometry. Here, we test a simple CFI system, that does not require PAM fluorometry, but instead simply images fluorescence emitted by plants. We used this technique to visualize stress induced by the photosystem II-inhibitory herbicide atrazine. After applying atrazine as a soil drench, CFI and color images were taken at 15-minute intervals, alongside measurements from a PAM fluorometer and a leaf reflectometer. Pixel intensity of the CFI images was negatively correlated with the quantum yield of photosystem II (ΦPSII) (p < 0.0001) and positively correlated with the measured reflectance in the spectral region of chlorophyll fluorescence emissions (p < 0.0001). A fluorescence-based stress index was developed using the reflectometer measurements based on wavelengths with the highest (741.2 nm) and lowest variability (548.9 nm) in response to atrazine damage. This index was correlated with ΦPSII (p < 0.0001). Low-cost CFI imaging can detect herbicide-induced stress (and likely other stressors) before there is visual damage.

The spread of invasive alien species (IAS) is recognized as the most severe threat to biodiversity outside of climate change and anthropogenic habitat destruction. IAS negatively impact ecosystems, local economies, and residents. They are especially problematic because once established, they give rise to positive feedbacks, increasing the likelihood of further invasions and spread. The integration of remote sensing (RS) to the study of invasion, in addition to contributing to our understanding of invasion processes and impacts to biodiversity, has enabled managers to monitor invasions and predict the spread of IAS, thus supporting biodiversity conservation and management action. This chapter focuses on RS capabilities to detect and monitor invasive plant species across terrestrial, riparian, aquatic, and human-modified ecosystems. All of these environments have unique species assemblages and their own optimal methodology for effective detection and mapping, which we discuss in detail.

Field studies were conducted in 2016 and 2017 in Clinton, NC, to determine the interspecific and intraspecific interference of Palmer amaranth (Amaranthus palmeri S. Watson) or large crabgrass [Digitaria sanguinalis (L.) Scop.] in ‘Covington’ sweetpotato [Ipomoea batatas (L.) Lam.]. Amaranthus palmeri and D. sanguinalis were established 1 d after sweetpotato transplanting and maintained season-long at 0, 1, 2, 4, 8 and 0, 1, 2, 4, 16 plants m⁻¹ of row in the presence and absence of sweetpotato, respectively. Predicted yield loss for sweetpotato was 35% to 76% for D. sanguinalis at 1 to 16 plants m⁻¹ of row and 50% to 79% for A. palmeri at 1 to 8 plants m⁻¹ of row. Weed dry biomass per meter of row increased linearly with increasing weed density. Individual dry biomass of A. palmeri and D. sanguinalis was not affected by weed density when grown in the presence of sweetpotato. When grown without sweetpotato, individual weed dry biomass decreased 71% and 62% from 1 to 4 plants m⁻¹ row for A. palmeri and D. sanguinalis, respectively. Individual weed dry biomass was not affected above 4 plants m⁻¹ row to the highest densities of 8 and 16 plants m⁻¹ row for A. palmeri and D. sanguinalis, respectively.

The effect of plant phenology and canopy structure of four crops and four weed species on reflectance spectra were evaluated in 2016 and 2017 using in situ spectroscopy. Leaf-level and canopy-level reflectance were collected at multiple phenologic time points in each growing season. Reflectance values at 2 wk after planting (WAP) in both years indicated strong spectral differences between species across the visible (VIS; 350–700 nm), near-infrared (NIR; 701–1,300 nm), shortwave-infrared I (SWIR1; 1,301–1,900 nm), and shortwave-infrared II (SWIR2; 1,901–2,500 nm) regions. Results from this study indicate that plant spectral reflectance changes with plant phenology and is influenced by plant biophysical characteristics. Canopy-level differences were detected in both years across all dates except for 1 WAP in 2017. Species with similar canopy types (e.g., broadleaf prostrate, broadleaf erect, or grass/sedge) were more readily discriminated from species with different canopy types. Asynchronous phenology between species also resulted in spectral differences between species. SWIR1 and SWIR2 wavelengths are often not included in multispectral sensors but should be considered for species differentiation. Results from this research indicate that wavelengths in SWIR1 and SWIR2 in conjunction with VIS and NIR reflectance can provide differentiation across plant phenologies and, therefore should be considered for use in future sensor technologies for species differentiation.

Cover crops (CCs) have shown great potential for suppressing annual weeds within agronomic cropping systems across the United States. However, the weed suppressive potential of CCs may be moderated by environmental and management factors that are specific to certain geographic areas and their associated characteristics. This may be particularly true within the U.S. Southeast, where higher mean annual temperature and precipitation generate favorable conditions for both CC and weed growth. To understand the effects of this regional context on CCs and weeds, a meta-analysis examining paired comparisons of weed biomass and/or weed density under CC and bare ground conditions from studies conducted within the Southeast was conducted. Data were identified and extracted from 28 journal articles in which weed biomass and/or weed density were measured along with cash crop yield data, if they were provided. Fourteen studies provided 142 comparisons for weed biomass; 23 studies provided 139 comparisons for weed density; and 22 studies, pooled over both weed response variables, provided 144 comparisons for cash crop yield. CCs had a negative effect on weed density (P = 0.0016) but no effect on either weed biomass (P = 0.16) or cash crop yield (P = 0.88). The mean relative reduction in weed density under CCs was 44%. Subsequent analyses indicated that CC biomass was the key factor associated with this reduction. Weed density suppression was linearly related to CC biomass; a 50% decrease in weed density was associated with 6,600 kg ha⁻¹ of CC biomass. Edaphic, geographic, and other management factors had no bearing on this suppressive effect. This highlights the importance of generating adequate CC biomass if weed suppression is the primary objective of CC use and the potential for CCs to reduce weed density over diverse soil, climate, and farm management conditions.

Cover crops can improve soil health by increasing soil organic matter, soil porosity, permeability, and crop yield. Yet, land planted to cover crops are often limited by economic constraints. Perennial living mulch (LM) cover crops may provide better benefits to soil health because they are actively growing throughout the year and self‐regenerate without reseeding. The objective of this study was to compare the impact of a white clover (Trifolium repens L.) LM vs. annual cover crops on soil health traits. Treatments were established on a Cecil sandy loam soil in the fall of 2014 and annual cover crop treatments re‐established each fall of the following 3 yr. White clover re‐established in the LM without reseeding. Corn (Zea mays L.) was planted into the treatments in the spring of each year. Soils were sampled at the V4/V5, V12, and R5 stages of corn development and analyzed for chemical traits. Surface soil characteristics were measured after corn harvest in 2018. Soils in the LM system had lower lime buffering capacity and greater pH, base saturation, cation exchange capacity (CEC), Ca, K₂O, Mg, P₂O₅, and total organic C concentrations than other treatments. Soil NH₃ and NO₃ had seasonal fluctuations associated with mineral N fertilizer and were lower in the LM treatment. After 3 yr, the soil bulk density was lower and porosity, water infiltration, and labile C were greater in surface soils from the LM treatment than in the surface soils of the other treatments. Use of a perennial LM cover crops expedited soil health regeneration compared to other treatments.