Determinants and Prediction of Carbon/Nitrogen Ratio in Five Diverse Crop Plants

• Published in: Communications in soil science and plant analysis Vol. 40; no. 17-18; pp. 2688 - 2711
• Main Authors: Jaradat, Abdullah A, Johnson, Jane M.F, Weyers, Sharon L, Barbour, Nancy W
• Format: Journal Article
• Language: English
• Published: Philadelphia, PA Taylor & Francis Group, LLC 01-01-2009; Taylor & Francis
• Subjects: Agronomy. Soil science and plant productions; Artificial neural networks; Biological and medical sciences; C/N ratio; carbon nitrogen ratio; chemical composition; chemical constituents of plants; Chemical, physicochemical, biochemical and biological properties; crop residues; Cuphea; discriminant analysis; estimation; Fundamental and applied biological sciences. Psychology; Glycine max; leaves; Medicago sativa; model validation; Organic matter; Panicum virgatum; Physics, chemistry, biochemistry and biology of agricultural and forest soils; plant tissues; prediction; predictive models; regression analysis; roots; Soil science; statistical models; stems; variance components; Zea mays; variance components; Carbon nitrogen ratio; Discriminant analysis; predictive models; Prediction; Artificial neural networks; Predictive value; C/N ratio; Neural network; Forecast model; Variance component; Artificial intelligence
• ISSN: 0010-3624; 1532-2416
• DOI: 10.1080/00103620903173756

Multivariate relationships in and statistical moments of eight biochemical constituents and their impact on estimating carbon/nitrogen (C/N) ratio in alfalfa, corn, soybean, cuphea, and switchgrass residues indicate that (1) equal portions of variation in C/N were explained by differences among crops and among organs; however, the largest variations in N and C were explained by differences among crops and among organs within crops, respectively; (2) variation in N, but not in C or N + C, content explained the greatest variance in C/N ratios; (3) biochemically, stems were closer to roots than to leaves; hence the large portion of variation in C/N ratio in roots explained by variation in biochemical constituents in stems and leaves (R2 = 61.0%) and in stems only (R2 = 58.0%); and (4) statistical moments, other than mean values of biochemical constituents, significantly impacted C/N ratio estimates and the reliability of these estimates, both of which were positively correlated (r = 0.64, p < 0.001).