Substituting leguminous crops for summer maize with optimal nitrogen fertilization strategies to improve soil ecosystem multifunctionality and crop production in semi-humid region

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 10, 2025

Legume crop rotation and moderate nitrogen application have been widely recognized in maintaining production improving soil quality. However, the mechanism of how soybean stubble combined with appropriate reduction regulates winter wheat growth, uptake, especially ecosystem multifunctionality (EMF), remain unclear. Therefore, a two-year field experiment was conducted using three different preceding crops (Fallow-F, Soybean-B Maize-M) rates (N0, N1 N2) to investigate effects legume pre-crops reduced input on root above-ground dry matter accumulation distribution, uptake utilization, as well impact yield EMF within cropping system. Compared F M stubbles, B significantly promoted aboveground underground growth wheat, increased by 27.48% 33.35%, respectively. With increase rate, absorption under each stubble, agronomic efficiency (NAE) higher than N2 at level. also improved yield, annual economic benefits EMF, best performance observed N1, where BN1 were average 70.87% higher, 4.17 times other treatments. Pearson correlation analysis revealed positive relationships between weight (RWD), biomass grain accumulation, yield. These findings highlight close relationship while revealing importance This study provides theoretical support for incorporating legumes into systems reduce chemical fertilizer use enhance multifunctionality.

Language: Английский

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The Effect of Long-Term Soil System Use and Diversified Fertilization on the Sustainability of the Soil Fertility—Organic Matter and Selected Trace Elements

Sustainability, Journal Year: 2025, Volume and Issue: 17(7), P. 2907 - 2907

Published: March 25, 2025

It has been assumed that the long-term impact of a diversified soil use system (SUS) and continuous application manure and/or mineral fertilizers (NPK) affects sustainability fertility components. This influence is manifested through content distribution nutrients, as well some bioavailable heavy metals in soil. hypothesis was verified 2022 field experiment started 1957. consisted seven-course crop rotation: potato–spring barley–winter triticale–alfalfa–alfalfa–winter wheat–winter rye monocultures these crops plus black fallow. The studies were carried out on three separate fields: fallow (BF), winter wheat grown monoculture (WW-MO), rotation (WW-CR). Each experimental objects consists five fertilizer variants (FVs) fertilized same way every year: absolute control (AC)—variant without for 75 years; farmyard manure—FM; fertilizers—NPK; mixed variant—NPK + FM; annually applied lime—NPK L. second factor layer: 0.0–0.3 m, 0.3–0.6 or 0.6–0.9 m. obtained results clearly indicate fertilization with NPK FM, especially legumes, strengthens eluviation/illuviation processes, decreasing fertility. Liming stabilizing silt clay particles key determining micronutrients organic carbon (Corg). Its decreased following order: WW-CR (13.2 ± 5.8) ≥ WW-MO (12.3 6.9) > BF (6.6 2.8 g·kg−1). large variability resulted from trend depth, which increased follows: MO CR BF. FVs FM had highest Corg content. NPK, regardless (SUS), lowest Among elements studied, one impacting both iron (Fe). Fe order BL (100%) (90.5%) (85%). opposite tendency found remaining elements, consistent Corg, CR. strongest Fe, modified by SUS, Zn, Pb, Cd. Despite differences observed between SUSs, variants, layers, Mn medium class, while Zn Cu high class availability. Ni WW-CR. Pb weakly affected SUS but showed strong accumulation topsoil layer. Cd BF, where it exceeded threshold 0.27 mg·kg−1. main fertility, makes possible to directions humus its turned be factor, cooperation determined

Language: Английский

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Predicting Sustainable Crop Yields: Deep Learning and Explainable AI Tools

Sustainability, Journal Year: 2024, Volume and Issue: 16(21), P. 9437 - 9437

Published: Oct. 30, 2024

Optimizing agricultural productivity and promoting sustainability necessitates accurate predictions of crop yields to ensure food security. Various climatic variables are included in the analysis, encompassing type, year, season, specific conditions Indian state during crop’s growing season. Features such as season were one-hot encoded. The primary objective was predict yield using a deep neural network (DNN), with hyperparameters optimized through genetic algorithms (GAs) maximize R2 score. best-performing model, achieved by fine-tuning its hyperparameters, an 0.92, meaning it explains 92% variation yields, indicating high predictive accuracy. DNN models further analyzed explainable AI (XAI) techniques, specifically local interpretable model-agnostic explanations (LIME), elucidate feature importance enhance model interpretability. analysis underscored significant role features crops, leading incorporation additional dataset classify most optimal crops based on more detailed soil climate data. This classification task also executed GA-optimized DNN, aiming results demonstrate effectiveness this approach predicting classifying crops.

Language: Английский

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Effects of different preceding crops on soil nutrients and foxtail millet productivity and quality

Frontiers in Plant Science, Journal Year: 2024, Volume and Issue: 15

Published: Nov. 25, 2024

Crop rotation can affect crop productivity and soil characteristics; however, the impact of preceding crops on yield quality foxtail millet relationship between these two factors have not been well characterised. To further investigate effects millet, this study cultivated maize, mung beans, soybeans, potatoes, proso as rotated them with Zhangzagu10 millet. A randomised complete block design was employed for study, samples were collected after harvest. The performance grown five different explored by measuring indicators comprehensively analysing various traits their interrelationships. physicochemical nutritional characteristics grains significantly influenced crop. bean higher (8277.47 kg/hm

Language: Английский

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