田间有机氮净矿化量化和模拟的原始实验设计

Nitrogen Pub Date : 2022-04-15 DOI:10.3390/nitrogen3020015
T. Morvan, Laure Beff, Yvon Lambert, B. Mary, P. Germain, B. Louis, N. Beaudoin
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引用次数: 3

摘要

改善土壤有机氮矿化的评估和预测是必要的,因为它对作物的氮营养有重要贡献,并且仍然是一个重大的经济和环境挑战。因此,在法国布列塔尼建立了一个由137个农田组成的网络,以代表该地区土壤和耕作方法的广泛多样性。为提高净氮矿化的测量精度,设计了连续3年测量净氮矿化的实验设计。利用矿质氮质量平衡估算了3 ~ 10月未施氮肥玉米作物的净氮矿化量。通过计算归一化时间(ndays)来考虑气候对矿化的影响,然后计算矿物N质量平衡与归一化时间之比的N矿化率(Vn)。使用农艺和统计标准对实验数据进行严格筛选,结果选择了67个领域的子集进行数据分析。在此期间,平均Vn相对较高(0.99 kg N ha−1 nday−1),变化较大,第10百分位和第90百分位分别为0.62 ~ 1.46 kg N ha−1 nday−1。在土壤表层(0 ~ 30 cm)取样,评估其物理和化学性质,颗粒有机质碳和氮组分(分别为POM-C和POM-N),土壤微生物生物量(SMB)和可提取有机氮(EON),在磷酸盐硼酸盐萃取剂中测定。Vn与这些变量的相关性最强的是EON (r = 0.47)、SMB (r = 0.45)、POM-N (r = 0.43),其次是土壤N储量(r = 0.31)。Vn与一种种植制度指标也有很强的相关性(r = 0.39)。采用广义加性模型的建模方法,对预测净氮矿化能力最强的变量进行了识别和排序。
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An Original Experimental Design to Quantify and Model Net Mineralization of Organic Nitrogen in the Field
Improving the assessment and prediction of soil organic nitrogen (N) mineralization is essential: it contributes significantly to the N nutrition of crops and remains a major economic and environmental challenge. Consequently, a network of 137 fields was established in Brittany, France, to represent the wide diversity of soils and cultivation practices in this region. The experimental design was developed to measure net N mineralization for three consecutive years, in order to improve the accuracy of measuring it. Net N mineralization was quantified by the mineral N mass balance, which was estimated from March to October for a maize crop with no N fertilization. The effect of climate on mineralization was considered by calculating normalized time (ndays) and, then, calculating the N mineralization rate (Vn) as the ratio of the mineral N mass balance to normalized time. Strict screening of the experimental data, using agronomic and statistical criteria, resulted in the selection of a subset of 67 fields for data analysis. Mean Vn was relatively high (0.99 kg N ha−1 nday−1) over the period and varied greatly, from 0.62 to 1.46 kg N ha−1 nday−1 for the 10th and 90th percentiles, respectively. The upper soil layer (0–30 cm) was sampled to estimate its physical and chemical properties, particulate organic matter carbon and N fractions (POM-C and POM-N, respectively), soil microbial biomass (SMB), and extractable organic N (EON) determined in a phosphate borate extractant. The strongest correlations between Vn and these variables were observed with EON (r = 0.47), SMB (r = 0.45), POM-N (r = 0.43), and, to a lesser extent, the soil N stock (r = 0.31). Vn was also strongly correlated with a cropping system indicator (r = 0.39). A modeling approach, using generalized additive models, was used to identify and rank the variables with the greatest ability to predict net N mineralization.
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