The productivity of wheat in the Mediterranean region is under threat due to climate-change-related environmental factors, including fungal diseases that can negatively impact wheat yield and quality. Wheat phenotyping tools utilizing affordable, high-throughput plant phenotyping (HTPP) techniques, such as aerial and ground RGB images and quick canopy and leaf sensors, can aid in assessing crop status and selecting tolerant wheat varieties. This study focused on the impact of fungal diseases on wheat productivity in the Mediterranean region, considering the need for a precise selection of tolerant wheat varieties. This research examined the use of affordable HTPP methods, including imaging and active multispectral sensors, to aid in crop management for improved wheat health and to support commercial field phenotyping programs. This study evaluated 40 advanced lines of bread wheat (Triticum aestivum L.) at five locations across northern Spain, comparing fungicide-treated and untreated blocks under fungal disease pressure (Septoria, brown rust, and stripe rust observed). Measurements of leaf-level pigments and canopy vegetation indexes were taken using portable sensors, field cameras, and imaging sensors mounted on unmanned aerial vehicles (UAVs). Significant differences were observed in Dualex flavonoids and the nitrogen balance index (NBI) between treatments in some locations (p < 0.001 between Elorz and Ejea). Measurements of canopy vigor and color at the plot level showed significant differences between treatments at all sites, highlighting indexes such as the green area (GA), crop senescence index (CSI), and triangular greenness index (TGI) in assessing the effects of fungicide treatments on different wheat cultivars. RGB vegetation indexes from the ground and UAV were highly correlated (r = 0.817 and r = 0.810 for TGI and NGRDI). However, the Greenseeker NDVI sensor was found to be more effective in estimating grain yield and protein content (R² = 0.61–0.7 and R² = 0.45–0.55, respectively) compared to the aerial AgroCam GEO NDVI (R² = 0.25–0.35 and R² = 0.12–0.21, respectively). We suggest as a practical consideration the use of the GreenSeeker NDVI as more user-friendly and less affected by external environmental factors. This study emphasized the throughput benefits of RGB UAV HTPPs with the high similarity between ground and aerial results and highlighted the potential for HTPPs in supporting the selection of fungal-disease-resistant bread wheat varieties.

Proximal remote sensing devices are novel tools that enable the study of plant health status through the measurement of specific characteristics, including the color or spectrum of light reflected or transmitted by the leaves or the canopy. The aim of this study is to compare the RGB and multispectral data collected during five years (2016–2020) of four fruiting vegetables (melon, tomato, eggplant, and peppers) with trial treatments of non-grafted and grafted onto resistant rootstocks cultivated in a Meloidogyne incognita (a root-knot nematode) infested soil in a greenhouse. The proximal remote sensing of plant health status data collected was divided into three levels. Firstly, leaf level pigments were measured using two different handheld sensors (SPAD and Dualex). Secondly, canopy vigor and biomass were assessed using vegetation indices derived from RGB images and the Normalized Difference Vegetation Index (NDVI) measured with a portable spectroradiometer (Greenseeker). Third, we assessed plant level water stress, as a consequence of the root damage by nematodes, using stomatal conductance measured with a porometer and indirectly using plant temperature with an infrared thermometer, and also the stable carbon isotope composition of leaf dry matter.. It was found that the interaction between treatments and crops (ANOVA) was statistically different for only four of seventeen parameters: flavonoid (p < 0.05), NBI (p < 0.05), NDVI (p < 0.05) and the RGB CSI (Crop Senescence Index) (p < 0.05). Concerning the effect of treatments across all crops, differences existed only in two parameters, which were flavonoid (p < 0.05) and CSI (p < 0.001). Grafted plants contained fewer flavonoids ($\overline{\mathrm{x}}$ = 1.37) and showed lower CSI ($\overline{\mathrm{x}}$ = 11.65) than non-grafted plants ($\overline{\mathrm{x}}$ = 1.98 and $\overline{\mathrm{x}}$ = 17.28, respectively, p < 0.05 and p < 0.05) when combining all five years and four crops. We conclude that the grafted plants were less stressed and more protected against nematode attack. Leaf flavonoids content and the CSI index were robust indicators of root-knot nematode impacts across multiple crop types.

Proximal remote sensing devices are novel tools that enable the study of plant health status through the measurement of specific characteristics, including the color or spectrum of light reflected or transmitted by the leaves or the canopy. Among these, RGB images can provide spatially detailed information about crop status including estimates of biomass, chlorophyll (and chlorosis) and fractional vegetation cover. The aim of this study is to compare the RGB data collected during five years (2016–2020) of four fruiting vegetables (melon, tomato, eggplant and peppers) with trial treatments of non-grafted and grafted onto resistant rootstocks cultivated in a Meloidogyne incognita (a root-knot nematode, RKN) infested soil in a greenhouse. The proximal remote sensing of plant health status data collected were divided into three levels. Firstly, leaf level pigments were measured using two different handheld sensors (SPAD and Dualex). Secondly, canopy vigor and biomass were assessed using vegetation indices derived from RGB images and the Normalized Difference Vegetation Index (NDVI) measured with a portable spectroradiometer (Greenseeker). Thirdly, we assessed plant level water stress, as a consequence of the root damage by nematodes, directly using stomatal conductance measured with a porometer, and indirectly using plant temperature with an infrared thermometer and also the stable carbon and nitrogen isotope composition of leaf dry matter. Among the measured parameters, carbon and nitrogen percentage exhibited the highest positive correlation (r = 0.90), whereas flavonoids and NBI (Nitrogen Balance Index) showed the highest inverse correlation (r = −0.87). It was found that the interaction between treatments and crops (ANOVA) was statistically different for only 4 of 17 parameters (flavonoid (p = 0.002), NBI (p = 0.044), NDVI (p = 0.004) and CSI (RGB-based Crop Senescence Index) (p = 0.002). Concerning the effect of treatments across all crops, differences existed only in two parameters, which were flavonoids (p = 0.003) and CSI (p = 0.001). Grafted plants contained less flavonoids ($\bar{\mathrm{x}}$ = 1.37) and showed lower CSI ($\bar{\mathrm{x}}$ = 11.65) than non-grafted plants ($\bar{\mathrm{x}}$ = 1.98 and $\bar{\mathrm{x}}$ = 17.28, respectively, p = 0.020 and p = 0.029) when combining all five years and four crops. We conclude that the grafted plants were less stressed and more protected against nematode attack. Leaf flavonoids and the RGB indexes (CSI) were robust indicators of root-knot nematode impacts across multiple crop types.