The agricultural sector is currently confronting multifaceted challenges such as an increased food demand, slow adoption of sustainable farming, a need for climate-resilient food systems, resource inequity, and the protection of small-scale farmers’ practices. These issues are integral to food security and environmental health. Remote sensing technologies can assist precision agriculture in effectively addressing these complex problems by providing farmers with high-resolution lenses. The use of vegetation indices (VIs) is an essential component of remote sensing, which combines the variability of spectral reflectance value (derived from remote sensing data) with the growth stage of crops. A wide array of VIs can be used to classify the crops and evaluate their state and health. However, precisely this high number leads to difficulty in selecting the best VI and their combination for specific objectives. Without thorough documentation and analysis of appropriate VIs, users might find it difficult to use remote sensing data or obtain results with very low accuracy. Thus, the objective of this review is to conduct a critical analysis of the existing state of the art on the effective use of VIs for the discrimination and monitoring of several important agricultural crops (wheat, corn, sunflower, soybean, rape, potatoes, and forage crops), grasslands and meadows. This data could be highly useful for all the stakeholders involved in agricultural activities. The current review has shown that VIs appear to be suitable for mapping and monitoring agricultural crops, forage crops, meadows and pastures. Sentinel-1 and Sentinel-2 data were the most utilized sources, while some of the frequently used VIs were EVI, LAI, NDVI, GNDVI, PSRI, and SAVI. In most of the studies, an array of VIs needed to be employed to achieve a good discrimination of crops or prediction of yields. The main challenges in using VIs are related to the variation of the spectral characteristics during the vegetation period and to the similarities of the spectral signatures of various crops and semi-natural meadows. Thus, further studies are needed to establish appropriate models for the use of satellite data that would prove to have greater accuracy and provide more relevant information for the efficient monitoring of agricultural crops.

Although essential for achieving high crop yields required for the growing population worldwide, nitrogen, (N) in large amounts, along with its inefficient use, results in environmental pollution and increased greenhouse gas (GHG) emissions. Therefore, improved nitrogen use efficiency (NUE) has a significant role to play in the development of more sustainable crop production systems. Considering that wheat is one of the major crops cultivated in the world and contributes in high amounts to the large N footprint, designing sustainable wheat crop patterns, briefly defined by us in this review as the 3 Qs (high quantity, good quality and the quintessence of natural environment health) is urgently required. There are numerous indices used to benchmark N management for a specific crop, including wheat, but the misunderstanding of their specific functions could result in an under/overestimation of crop NUE. Thus, a better understanding of N dynamics in relation to wheat N cycling can enhance a higher efficiency of N use. In this sense, the aim of our review is to provide a critical analysis on the current knowledge with respect to wheat NUE. Further, considering the key traits involved in N uptake, assimilation, distribution and utilization efficiency, as well as genetics (G), environment (E) and management (M) interactions, we suggest a series of future perspectives that can enhance a better efficiency of N in wheat.

The agricultural sector is currently confronting multifaceted challenges such as an increased food demand, a slow adoption of sustainable farming, a need for climate-resilient food systems, resource inequity, and protection of the small-scale farmers’ practices, all issues integral to food security and environmental health. Remote sensing technologies can assist precision agriculture to effectively address these complex problems, by providing farmers with a high-resolution lens. The use of vegetation indices (VIs) is an essential component of remote sensing, which combine the variability of spectral reflectance value (derived from remote sensing data) with the growth stage of crops. Currently a wide array of VIs is available that could be used to provide a classification and an evaluation of the state and health of crops. However precisely this high number leads to difficulties in selecting the best VI and combination of VIs for a specific objective. Without a thorough documentation and analysis of appropriate VIs, users might be confronted with difficulties in using remote sensing data or even with a very low accuracy of the results. Thus, the objective of this review is to conduct a critical analysis of the existing state of the art on the most important features related to the effective use of VIs for the discrimination and monitoring of the most important agricultural crops (wheat, corn, sunflower, soybean, rape, potatoes, and forage crops), grasslands and meadows. This data could be highly useful for all the stakeholders involved in agricultural activities (from farmers, researchers up to institutions dealing with the centralization and monitoring of agricultural crops).

Assessing the efficiency of nitrogen application is a valuable first step in establishing an optimum N fertilizer management plan. The aim of this study was to elaborate a sustainable N management system for sown grassland installed in temperate regions, through manipulation of nitrogen use efficiency and nitrogen response efficiency (NRE) indicators. Research was performed in western Romania. The biological material consists in two forage species of major importance for the forage base worldwide, namely Trifolium pratense L. and Lolium multiflorum Lam., in pure stands and in mixture. Both forage species were sown at two different spacings between rows (12.5 and 25.0 cm) and were fertilized with nitrogen (N) in three doses (N0-control, N50-fertilized with 50 kg N ha⁻¹ and N100-fertilized with 100 kg N ha⁻¹). The studies were made in 2016 and 2017, years very different from each other in matter of rainfalls. The results revealed a different behavior of the three sward types analyzed: while in Trifolium pratense monoculture and in the mixture of the two species studied, less N was removed than was applied; on the other hand Lolium multiflorum monoculture used a high proportion of the N applied, being at the limit to access N from the organic pool or residual N from fertilizer applications to a preceding crop.

Reynoutria japonica Houtt (RJ) is an extremely invasive plant species, found nowadays in a wide range of habitats, including those polluted with heavy metals (HM). The aim of this study was to investigate HM dynamics in RJ–soil interactions in five habitats historically polluted with HM located in Baia Mare city, Romania. The concentrations of major metal elements (Cd, Cu, Pb, Zn) in plant tissues (roots, stems, leaves) and soil samples collected from the study sites were analyzed via portable ED-XRF spectroscopy (converted), and the translocation factor (TF) and bioconcentration factor (BCF) were calculated. The mean values of HM in soil samples collected from the study sites exceeded the threshold limit values established by Romanian legislation. Generally, the highest concentration of Cd was recorded in the above-ground part of the plant (stem and leaves), while for Cu, Pb and Zn, the highest values (with few exceptions) were recorded in the root. The metal transfer was highly effective from soil to RJ, such that all four of the HM studied exceeded the normal range of metals in a plant. Analysis of metal concentrations in plant tissues showed an efficient movement of Cd and Zn to the above-ground parts of the plant, a tendency particularly pronounced in the case of Cd (TF and BCF > 1), while Pb was the least bioaccumulated HM. It may be concluded that RJ is able to tolerate high concentrations of HM, being a good phytoextractor for Cd and Zn.

Semi-natural grasslands are particularly important in mountainous areas of Romania, being the only source of forage for many farmers. The aim of this study was to investigate the changes in forage quantity and quality as a result of Urea Ammonium nitrate (UAN) liquid fertilization. The experiment was carried out in the eastern part of Apuseni Mountains, Romania on a Festuca rubra L.-Agrostis capillaris L. grassland located at 1240 m altitude. Studies were made over three years of experimental trial (2014–2016) and covered four experimental plots in three replicates, as follows: V1–control plot, unfertilized; V2–plot fertilized with 50 kg UAN ha⁻¹ year⁻¹; V3–plot fertilized with 75 kg UAN ha⁻¹ year⁻¹, and V4–plot fertilized with 100 kg UAN ha⁻¹ year⁻¹. The experimental plots were harvested once per year and the botanical composition, dry matter yield and forage quality were assessed. Our results showed important changes in forage quantity, quality and diversity as a result of UAN fertilization. Starting from the second experimental year the dominance/co-dominance ratio changed favoring the species from Poaceae family. Dry matter increased as a result of UAN fertilization but forage quality was negatively affected by the higher percentage of participation of species from other botanical families which have higher crude fiber content and lower crude protein. Based on our results we recommend moderate fertilization with UAN up to 50 kg UAN ha⁻¹ year⁻¹ for semi-natural grasslands located in soil-climatic conditions similar to those in our experiment.