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.

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).

During the process of maize seed production, in order to ensure the genetic purity of parental forms of hybrid maize, an important work performed is the removal of male inflorescences from plants on mother rows. Hand detasseling has high precision but is labor-intensive. Mechanical detasseling offers the possibility to cover large acreages in a short period of time, but the number of leaves removed has a varying influence on plant performance and seed yield. The aim of this study was to simulate three types of damages on plants similar to those induced through mechanical detasseling and to assess the effects for five inbred lines during the course of three years. Results show that when tassels alone were removed, the average seed yield decreased an average of 4–21%. When two leaves were removed with the tassel, yield decreased an average of 22–31%, while when plants were cut above the main ear, seed yield decreased an average of 31–66%. Environmental conditions influenced seed yield, especially high temperatures during flowering. Yield response to tassel and leaves removal varied between the inbred lines. Genotype controls maize ear and kernel characters, while environmental factors exercise a strong influence on seed yield, due to the succession of years with contrasting weather conditions in a key phenophase. Within the trend of full mechanization in agriculture, identification of inbred lines that cope better with plant damage can assist in optimizing seed production.

There is a worldwide trend that supports the rational use of chemicals in agriculture. It has become common knowledge that irresponsible application of pesticides can cause food security issues, by endangering human and animal health while also having negative environmental consequences. The aim of this experiment was to assess the qualitative parameters of spraying treatments in vineyards. To achieve this, a vineyard and orchard sprayer machine was used for the application of treatments under a gradient of pressures (3, 5, 7, 9 bar). Water-sensitive collectors were placed at three heights (0.8 m, 1.5 m, 2.5 m). Following spraying was determined using DepositScan: the volume median diameter characterization of droplets (DV 1, DV 5, DV 9), and coverage degrees of sprayings. Results indicated that best coverage degree and larger droplets tend to be deposited 1.5 m from the ground, which corresponds with the highest proximity to the positioning of the nozzles of the machine during application, and lowest coverage is found at the top, where droplets deposited also tend to be smaller. For the anti-drift nozzle model used in the study, the best coverage was obtained at a pressure of 5 bar. For sustainability of agricultural practices and rational use of pesticides, more research is required for optimization of increased precision spraying that could ensure high coverage at lower doses of chemicals and coarse droplets. In this way the quantity of product sprayed is expected to be reduced, due to minimization of off-target losses and increased efficiency. This can ensure that negative environmental impacts are lowered. Improved treatment application at higher positioning of the canopy remains a challenge and shall receive more attention.

Maize is affected by drought and heat, abiotic stress factors that have been encountered more often in recent years in various parts of Europe. In the area of Turda, Romania, extreme temperatures and heat waves combined with an uneven distribution of precipitation have been recorded that had an unfavorable influence on the maize crop. In this study, the ASI (anthesis-to-silking interval), yield, and stability of 35 old and new maize hybrids created at the Agricultural Research and Development Station Turda were studied under drought and heat conditions. An increase in temperature was observed during vegetative growth and grain filling, and rainfall was deficient during and after flowering. These conditions had a negative influence on ASI, grain filling, and, indirectly, yield, which varied significantly during the seven experimental years. The five newest hybrids (Turda335, Turda2020, Turda380, Sur18/399, and HST148) stood out, with average yields of over 8400 kg ha⁻¹ in unfavorable years and over 15–16,000 kg ha⁻¹ under favorable conditions. They generally outperformed the mean by 29–33%. In contrast, the old hybrids achieved yields up to 22% lower than the experimental mean. Yield was 43.1% lower in 2022 and 31.8% lower in 2023 compared to the best year (2021).

High-Nature-Value (HNV) grasslands in the Apuseni Mountains represent traditional semi-natural ecosystems with high biodiversity and major ecological value, but are constantly exposed to pressures generated by both agricultural intensification and abandonment. This study asses the effects of long-term mineral fertilization on floristic composition and grassland diversity within a permanent experiment initiated in 2001 in Gârda de Sus (Romania). Four variants of mineral fertilization were tested: control (N0), low-input (N₅₀P₂₅K₂₅), medium-input (N₁₀₀P₅₀K₅₀) and high-input (N₁₅₀P₇₅K₇₅). Floristic analyses were performed using the modified Braun-Blanquet method, and the data were interpreted using multivariate analyses and diversity indices. The results revealed a clear trophic gradient. Both the control and low-input variants maintained high diversity and the stability of communities dominated by Festuca rubra and its associated oligotrophic species. In contrast, medium and high fertilization produced a pronounced reduction in community components, with the dominance of nitrophilous species, especially Agrostis capillaris, a species which is consumed by animals. Multivariate analyses confirmed that the dominant effect on plant communities was the fertilization level, outweighing the interannual climatic variations. Low fertilization maintained biodiversity with minimal changes after 17 years, while higher inputs led to significant species losses and reduced stability of community. The results provide a scientific benchmark for creating specific sustainable management scenarios and highlight the need for accepted organic alternatives. This study is one of the few long-term experiments in the Carpathians that documents the impact of fertilization on HNV grasslands and provides essential benchmarks for adapting management strategies in the context of the Common Agricultural Policy.