Nitrogen

Estimating indigenous rhizobial populations is crucial for understanding soil rhizobia abundance, determining the potential need for inoculation, and evaluating the performance of introduced inoculant strains. However, in southern Ethiopia, information on the population abundance of soybean-nodulating rhizobia is limited. To address this gap, the present study was conducted to evaluate the population abundance of indigenous soybean-nodulating rhizobia and to assess the influence of cropping history and soil properties on rhizobial abundance. The study was conducted across five sites suitable for soybean cultivation in southern Ethiopia: Arsi-Negelle, Boricha, Dore, Hawassa, and Wondo Genet. The study sites represented a range of cropping systems, including sole maize, sole tobacco, sole haricot bean, maize–potato intercropping, and crop rotation. Composite soil samples were collected from a depth of 0–20 cm, and rhizobial abundance was determined using the most probable number (MPN) technique. Indigenous rhizobial populations ranged from 0 to 1.7 × 10¹ cells g⁻¹ of dry soil. Overall, the population levels were low, suggesting that inoculation with effective rhizobial strains would likely improve nodulation and biological nitrogen fixation. Relatively higher rhizobial population densities were observed at Arsi-Negelle under haricot bean cropping history. Statistically significant positive correlations were found between rhizobial abundance and cation exchange capacity, organic carbon, and organic matter. In general, native rhizobial populations across all study locations were below levels considered sufficient to support effective soybean nodulation and nitrogen fixation, indicating the need for inoculation to enhance soybean productivity in the study areas.

The application of plasma-activated water and biostimulants offers a sustainable approach to supporting plant growth under reduced-nutrient conditions by supplying bioavailable nitrogen. This study investigated the growth and postharvest performance of hydroponically grown cos lettuce (Lactuca sativa L.) supplied with three Hoagland-based nutrient treatments: half-strength solution prepared with tap water (HS), half-strength solution with plasma-activated water (HS+PAW), and half-strength solution with plasma-activated water containing 1 mL L⁻¹ milk protein hydrolysate (HS+PAW+MPH). Plants treated with PAW, particularly those in the HS+PAW+MPH, exhibited increases in growth, biomass accumulation, and mineral composition, with reduced nitrate content compared to controls. At harvest, lettuce under HS+PAW+MPH exhibited nearly double fresh yield and enhanced dry matter, protein, lipid, phenolic, and flavonoid profiles as well as increased antioxidant capacity, indicating improved nitrogen utilization and nutritional quality under reduced nutrient input. Postharvest quality was evaluated by packing samples in polypropylene bags and storing them at 10 ± 1 °C and 95–98% relative humidity for 21 days. The HS+PAW+MPH treatment substantially suppressed respiration and production of ethylene, limited weight loss and color change, and better preserved pigments, bioactive compounds, and antioxidant stability compared to HS and HS+PAW, indicating HS+PAW+MPH as a sustainable nutrient management approach for hydroponic systems.

The Overseer model is widely used in New Zealand as a precision-agriculture-related tool for estimating nitrate (NO₃⁻) leaching losses in agricultural systems. This study evaluated the accuracy of the Overseer model in predicting nitrate (NO₃⁻) leaching through a two-year lysimeter experiment conducted at Woodhaven Gardens, New Zealand, under beetroot and pak choi cultivation. Seven distinct nitrogen (N) fertilizer treatments were applied to assess model performance. In year 1, Overseer overestimated NO₃⁻ leaching by an average of 45.2 kg N/ha (15.7%), and in year 2, the model overestimated by 35.2 kg N/ha (43.5%). A sensitivity analysis highlighted soil texture, impeded layer depth and crop residue incorporation as key drivers of leaching variability, underscoring the need for improved model calibration. Overseer performed reasonably well under lysimeter conditions, with a strong linear relationship (Pearson’s correlation coefficient r = 0.89, p < 0.0001) between measured and predicted values and explaining 77% of the variance (R² = 0.77) in the observed data. The model predicted a baseline leaching loss of 39.4 kg N/ha/year even when measured losses were zero. Overseer demonstrates moderate reliability in predicting NO₃⁻ leaching under vegetable cropping systems but exhibits notable limitations in handling crop-specific N dynamics, soil hydrology, and fertilizer timing.