Cover crops are becoming an increasingly important tool for weed suppression. Biomass production in cover crops is one of the most important predictors of weed suppressive ability. A significant challenge for growers is that cover crop growth can be patchy within fields, making biomass estimation difficult. This study tested ground-based structure-from-motion (SfM) for estimating and mapping cereal rye (Secale cereale L.) biomass. SfM generated 3D point clouds from red, green, and blue (RGB) videos collected by a handheld GoPro camera over five fields in North Carolina during the 2022 to 2023 winter season. A model for predicting biomass was generated by relating measured biomass at termination using a density–height index (DH) from point cloud pixel density multiplied by crop height. Overall biomass ranged from 320 to 9,200 kg ha−1, and crop height ranged from 10 to 120 cm. Measured biomass at termination was linearly related to DH (r2 = 0.813) through levels of 9,000 kg ha−1. Based on independent data validation, predicted biomass and measured biomass were linearly related (r2 = 0.713). In the field maps generated by kriging, measured biomass data were autocorrelated at a range of 5.4 to 42.2 m, and predicted biomass data were autocorrelated at a range of 3.4 to 12.0 m. However, the spatial arrangement of high- and low-performing areas was similar for predicted and measured biomass, particularly in fields with greatest patchiness and spatial correlation in biomass values. This study provides proof-of-concept that ground-based SfM can potentially be used to nondestructively estimate and map cover crop biomass production and identify low-performing areas at higher risk for weed pressure and escapes.

Recent innovations in 3D imaging technology have created unprecedented potential for better understanding weed responses to management tactics. Although traditional 2D imaging methods for mapping weed populations can be limited in the field by factors such as shadows and tissue overlap, 3D imaging mitigates these challenges by using depth data to create accurate plant models. Three-dimensional imaging can be used to generate spatiotemporal maps of weed populations in the field and target weeds for site-specific weed management, including automated precision weed control. This technology will also help growers monitor cover crop performance for weed suppression and detect late-season weed escapes for timely control, thereby reducing seedbank persistence and slowing the evolution of herbicide resistance. In addition to its many applications in weed management, 3D imaging offers weed researchers new tools for understanding spatial and temporal heterogeneity in weed responses to integrated weed management tactics, including weed–crop competition and weed community dynamics. This technology will provide simple and low-cost tools for growers and researchers alike to better understand weed responses in diverse agronomic contexts, which will aid in reducing herbicide use, mitigating herbicide-resistance evolution, and improving environmental health.

Aerogels are a promising material for aerospace applications and have recently been explored for biomedical applications also. In both environments, exposure to radiation is inevitable, such as from radiation in space or, radiation-based sterilization and tracking of implants. X-ray radiation, in particular, is of a concern. Here, polyurea-crosslinked silica aerogel (PCSA) samples were exposed to approximately 170- and 500-Gy X-irradiation at room temperature under varying environmental conditions and characterized using electron spin resonance (ESR) technique. Results obtained for PCSA were compared with those from polyether-ether ketone (PEEK) and ultra-high molecular weight polyethylene (UHMWPE) which served as benchmarks for this study. PEEK is known to be very radiation resistant, while UHMWPE is known to be less radiation resistant. All materials (PCSA, PEEK, and UHMWPE) were exposed to the same treatments and exposure conditions. Two exposure times were tested: 10 min and 30 min which corresponded to “low” and “high” conditions, as well as comparisons of nitrogen vs. air environments during exposure and post-exposure storage. Results showed significant quantities of free radicals produced in PCSA after exposure to X-irradiation which scaled with radiation dosage; quantities were in-between those produced in PEEK and UHMWPE. The storage conditions (air vs. nitrogen) also played an important role in the free radical levels detected and are reported in this study.