Intensive conventional agriculture and climate change have induced severe ecological damages and threatened global food security, claiming a reorientation of agricultural management and public policies towards a more sustainable development model. In this context, nanomaterials promise to support this transition by promoting mitigation, enhancing productivity, and reducing contamination. This review gathers recent research innovations on smart nanoformulations and delivery systems improving crop protection and plant nutrition, nanoremediation strategies for contaminated soils, nanosensors for plant health and food quality and safety monitoring, and nanomaterials as smart food-packaging. It also highlights the impact of engineered nanomaterials on soil microbial communities, and potential environmental risks, along with future research directions. Although large-scale production and in-field testing of nano-agrochemicals are still ongoing, the collected information indicates improvements in uptake, use efficiency, targeted delivery of the active ingredients, and reduction of leaching and pollution. Nanoremediation seems to have a low negative impact on microbial communities while promoting biodiversity. Nanosensors enable high-resolution crop monitoring and sustainable management of the resources, while nano-packaging confers catalytic, antimicrobial, and barrier properties, preserving food safety and preventing food waste. Though, the application of nanomaterials to the agri-food sector requires a specific risk assessment supporting proper regulations and public acceptance.

A long-term experiment (38 years) was conducted to elucidate the effects of long-term N addition on the net N mineralization in both paddy and upland soils, based on their initial soil N status, with and in connection with soil microbial biomass and N cycling extracellular enzyme activities. Two treatments without N addition CK (No fertilizer) and K (inorganic potassium fertilizer) and two treatments with N addition (inorganic nitrogen fertilizer) and NK (inorganic nitrogen and potassium fertilizer) were placed in incubation for 90 days. Results showed that the total N and soil organic carbon (SOC) contents were higher in the treatments with N application compared to the treatments without N in both paddy and upland soils. The SOC content of paddy soil was increased relative to upland soil by 56.2%, 45.7%, 61.1% and 62.2% without N (CK, K) and with N (N and NK) treatments, respectively. Site-wise, total N concentration in paddy soil was higher by 0.06, 0.10, 0.57 and 0.60 times under the CK, K, N and NK treatments, respectively, compared with upland soil. In paddy soil, soil microbial biomass nitrogen (SMBN) was higher by 39.6%, 2.77%, 29.5% and 31.4%, and microbial biomass carbon (SMBC) was higher by 11.8%, 11.9%, 10.1% and 12.3%, respectively, in CK, K, N and NK treatment, compared with upland soil. Overall, compared to upland soil, the activities of leucine-aminopeptidase (LAP) were increased by 31%, 18%, 20% and 11%, and those of N-acetyl-b-D-glucosaminidase (NAG) were increased by 70%, 21%, 13% and 18% by CK, K, N and NK treatments, respectively, in paddy soil. A significantly linear increase was found in the NO₃⁻-N and NH₄⁺-N concentrations during the 90 days of the incubation period in both soils. NK treatment showed the highest N mineralization potential (N_o) along with mineralization rate constant, k (NMR) at the end of the incubation. SMBC, SMBN, enzyme activities, NO₃⁻-N and NH₄⁺-N concentrations and the N_o showed a highly significant (p ≤ 0.05) positive correlation. We concluded that long-term N addition accelerated the net mineralization by increasing soil microbial activities under both soils.

A long-term field experiment was carried out (since 2008) for evaluating the effects of different substitution rates of inorganic nitrogen (N) fertilizer by green manure (GM) on yield stability and N balance under double rice cropping system. Treatments included, (1) N₀ (no N fertilizer and no green manure); (2) N₁₀₀ (recommended rate of N fertilizer and no green manure); (3) N₁₀₀-M (recommended rate of N fertilizer and green manure); (4) N₈₀-M (80% of recommended N fertilizer and green manure); (5) N₆₀-M (60% of recommended N fertilizer and green manure); and (6) M (green manure without N fertilization). Results showed that, among all treatments, annual crop yield under N₈₀-M treatment was highest. Crop yield did not show significant differences between N₁₀₀-M and N₈₀-M treatments. Substitution of different N fertilizer rates by GM reduced the yield variability index. Compared to the N₀ treatment, yield variability index of early rice under N₁₀₀-M, N₈₀-M, and N₆₀-M treatments was decreased by 11%, 26%, and 36%, respectively. Compared to the N₀ treatment, yield variability index of late rice was decreased by 12%, 38%, 49%, 47%, and 24% under the N₁₀₀, N₁₀₀-M, N₈₀-M, N₆₀-M, and M treatments, respectively. During period of 2009–2013 and 2014–2018, nitrogen recovery efficiency (NRE) was highest under N₈₀-M treatment and N balance was highest under N₁₀₀ treatment. NRE of all treatments with GM was increased over the time from 2009–2013 to 2014–2018. All treatments with GM showed increasing trend of SOC over the years. Substitution of N fertilizer by GM also increased C inputs and soil C:N ratio compared to the N₁₀₀ and N₀ treatments. Boosted regression model indicated that C input, N uptake and AN were most influencing factors of crop yield. Thus, we concluded that N fertilization rates should be reduced by 20% under GM rotation to attain high yield stability of double rice cropping system through increasing NRE and C inputs.

Irrigation plays a crucial role in maize cultivation, as watering is essential for optimizing crop yield and quality, particularly given maize’s sensitivity to soil moisture variations. In the current study, a hybrid Long Short-Term Memory (LSTM) approach is presented aiming to predict irrigation scheduling in maize fields in Bursa, Turkey. A critical aspect of the study was the use of the Aquacrop 7.0 model to simulate soil moisture content (MC) data due to data limitations in the investigated fields. This simulation model, developed by the Food and Agriculture Organization (FAO), helped overcome gaps in soil sensor data, enhancing the LSTM model’s predictions. The LSTM model was trained and tuned using a combination of soil, weather, and satellite-based plant vegetation data in order to predict soil moisture content (MC) reductions. The study’s results indicated that the LSTM model, supported by Aquacrop 7.0 simulations, was effective in predicting MC reduction across various time phases of the maize growing season, attaining R² values ranging from 0.8163 to 0.9181 for Field 1 and from 0.7602 to 0.8417 for Field 2, demonstrating the potential of this approach for precise and efficient agricultural irrigation practices.

Cultivation of green manure (GM) crops in intensive cropping systems is important for enhancing crop productivity through soil quality improvement. We investigated yield sustainability, nutrient stocks, nutrient balances and enzyme activities affected by different long-term (1982–2016) green manure rotations in acidic paddy soil in a double-rice cropping system. We selected four treatments from a long-term experiment, including (1) rice-rice-winter fallow as a control treatment (R-R-F), (2) rice-rice-milkvetch (R-R-M), (3) rice-rice-rapeseed (R-R-R), and (4) rice-rice-ryegrass (R-R-G). The results showed that different GM rotations increased grain yield and the sustainable yield index compared with those of the R-R-F treatment. Compared with those of R-R-F, the average grain yield of early rice in R-R-M, R-R-R, and R-R-G increased by 45%, 29%, and 27%, respectively and that of late rice increased by 46%, 28%, and 26%, respectively. Over the years, grain yield increased in all treatments except R-R-F. Green manure also improved the soil chemical properties (SOM and total and available N and P), except soil pH, compared to those of the control treatment. During the 1983–1990 cultivation period, the soil pH of the R-R-M treatment was lower than that of the R-R-F treatment. The addition of green manure did not mitigate the soil acidification caused by the use of inorganic fertilizers. The soil organic matter (SOM), total nitrogen (TN) and total phosphorus (TP) contents and stocks of C, N and P increased over the years. Furthermore, GM significantly increased phosphatase and urease activities and decreased the apparent N and P balances compared with those in the winter fallow treatment. Variance partitioning analysis revealed that soil properties, cropping systems, and climatic factors significantly influenced annual grain yield. Aggregated boosted tree (ABT) analysis quantified the relative influences of the different soil properties on annual grain yield and showed that the relative influences of TN content, SOM, pH, and TP content on annual crop yield were 27.8%, 25.7%, 22.9%, and 20.7%, respectively. In conclusion, GM rotation is beneficial for sustaining high crop yields by improving soil biochemical properties and reducing N and P balances in acidic soil under double- rice cropping systems.