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.

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.

Nitrogen fertilization is indispensable in increasing wheat crop productivity but, in order to achieve maximum profitable production and minimum negative environmental impact, improving nitrogen use efficiency (NUE) should be considered. The aim of this study was to evaluate the nitrogen use efficiency (NUE) in a long-term wheat–maize–soybean rotation system with the final purpose of increasing the overall performance of the wheat cropping system. Research was undertaken at the Agricultural Research Development Station Turda (ARDS Turda), located in Western Transylvania Plain, Romania. The experimental field was carried out at a fixed place during seven wheat vegetation seasons. The plant material consisted of a wheat variety created by the ARDS Turda (Andrada), one variety of maize (Turda 332) and one variety of soybean (Felix). The experiment covered two planting patterns: wheat after maize and wheat after soybean and five levels of nitrogen fertilization (control-unfertilized, fertilization with 0—control plot, 30, 60, 90 and 120 kg N ha⁻¹ y⁻¹). The following indices were assessed: NUE (nitrogen use efficiency), N uptake and PFP (partial factor productivity). The results of the present study suggest that reduced N-fertilization doses could improve N uptake and utilization for both planting patterns.

Agriculture faces a dual challenge in the context of climate change, serving as both a significant contributor to greenhouse gas (GHG) emissions and a sector highly vulnerable to its impacts. Addressing this requires a transition toward climate-resilient agriculture (CRA). Emerging technologies, including geospatial tools (e.g., Geographic Information Systems (GISs) and remote sensing (RS)), as well as artificial intelligence (AI), offer promising methods to support this transition. However, their individual capabilities, limitations, and appropriate applications are not always well understood or clearly delineated in the literature. A common issue is the frequent overlap between GISs and RS, with many studies assessing GIS contributions while concurrently employing RS techniques, without explicitly distinguishing between the two (or vice versa). In this sense, the objective of this review is to conduct a critical analysis of the existing state of the art in terms of the distinct roles, limitations, and complementarities of GISs, RS, and AI in advancing CRA, guided by an original definition we propose for CRA (structured around three key dimensions and their corresponding targets). Furthermore, this review introduces a synthesis matrix that integrates both the individual contributions and the synergistic potential of these technologies. This synergy-focused matrix offers not just a summary, but a practical decision support matrix that could be used by researchers, practitioners, and policymakers in selecting the most appropriate technological configuration for their objectives in CRA-related work. Such support is increasingly needed, especially considering that RS and AI have experienced exponential growth in the past five years, while GISs, despite being the more established “big brother” among these technologies, remain underutilized and is often insufficiently understood in agricultural applications.

Potato, a component of global food security and economic stability, is cultivated extensively worldwide due to its adaptability to diverse climates and soil types. Ongoing research and technological advancements, including the use of unconventional products destined to fight the most harmful pathogens, are essential for enhancing productivity and resilience in potato farming. The current study aimed to identify the most appropriate fertilizers and phytosanitary treatments in order to attain optimal potato yields, dry matter, and starch contents, under climate-specific environments. The experiment was conducted in the northwest of Romania in 2023. The research was organized as a trifactorial experiment with the factors variety, fertilization, and phytosanitary treatment. XLSTAT (2022.2.1v.) was utilized for data processing. Mineral fertilization combined with conventional phytosanitary treatment led to the highest average yields in both potato varieties. Also, a combination of organic fertilization and treatment with 4% A. cepa extracts led to notable results, which suggests the possibility of successfully using these inputs in organic agriculture. The study shows the importance of selecting appropriate agricultural inputs to optimize potato yields, achieve specific levels of dry matter and starch content in a specific area, and promote sustainability.

The maize crop is an essential contributor to food security. At a global level, it is the cereal with the highest production, and the second imported commodity. This study evaluates the impact of precision agriculture on the morpho-productive traits and agronomic efficiency of the Turda 201 maize hybrid under distinct cultivation systems. A bifactorial field trial was conducted in Cojocna, Transylvania (Romania), using two factors: the farming system (organic vs. conventional) and the cultivation technology (standard vs. precision). The work hypothesis is that precision agriculture can enhance maize performance compared to standard methods. The results indicated that morphological traits such as plant height (197 cm), cob length (17.20 cm), and leaf number (10.60) were significantly higher in the conventional system, particularly under precision technology. In the organic system, while improvements were observed with precision input, overall growth and yield remained lower. The same trends are seen in production traits, which are lower in an organic system compared with conventional (6464.22 kg/ha vs. 9204 kg/ha, when precision technology was used). Agronomic efficiency has a spectacular increase in the conventional–precision experimental variant (4.92 kg/kg) compared with the organic–standard experimental variant (0.002 kg/kg). Crude protein, dry matter, nitrogen-free matter, and starch content are the main qualitative maize characteristics influenced by the cropping system and technology. The conventional–precision experimental variant led to the highest values of the above-mentioned parameters compared with the organic–standard experimental variant (86.90% vs. 83.60% dry matter; 10.75% vs. 8.65% crude protein; 72.60% vs. 64.40% nitrogen-free matter; 83.15% vs. 79.50% starch). Principal Component Analysis revealed that the crop system (PC1) was the dominant factor influencing morpho-productive traits, while environmental factors (PC2) contributed mainly to the variability of the characteristics. These findings support the use of precision agriculture as a tool for enhancing sustainable maize production, particularly in conventional systems.