Understanding legacy phosphorus (P) build-up and draw-down from long-term fertilization is essential for effective P management. Using replicated plots from Saskatchewan, Canada, with P fertilization from 1967 to 1995 followed by either P fertilization or P cessation (1995-2010), soil P was characterized in surface and subsurface layers using sequential fractionation, P K-edge X-ray absorption near-edge structure (XANES) and solution (31)P nuclear magnetic resonance (P NMR) spectroscopy. Legacy P from a 28-year build-up was sufficient for 15 years of wheat cultivation, resulting in no significant differences in crop yield in 2010. In surface soils, soil test (Olsen) P decreased significantly in unfertilized plots compared with 1995, which was reflected in declining aluminum (hydr)oxide-associated inorganic P by fractionation and XANES. Furthermore, XANES analysis revealed a decrease of calcium-associated P in 2010-unfertilized soils at both depths and an increase of Fe (hydr)oxides-associated P in the 2010-fertilized and -unfertilized surface soils relative to the 1995 soils. Increased total organic P and orthophosphate diesters by P NMR and accumulated inositol hexaphosphate by XANES were observed in surface soils with P fertilization cessation. In subsurface soils, few legacy P transformations were detected. These results provide important information about legacy P to improve agricultural sustainability while mitigating water quality deterioration.
Conservation tillage practices have become increasingly common in recent years to reduce soil erosion, improve water conservation, and increase soil organic matter. Research suggests that conservation tillage can stratify soil test phosphorus (P), but little is known about the effects on soil organic P. This study was conducted to assess the long-term effects of tillage practices (no-till [NT] and mouldboard plowing) and P fertilization (0 and 35 kg P ha) on the distribution of P species in the soil profile. Soil samples from a long-term corn-soybean rotation experiment in Québec, Canada, were collected from three depths (0-5, 5-10, and 10-20 cm). These samples were analyzed for total P (TP), total C (TC), total N (TN), pH, and Mehlich-3 P (PM3); P forms were characterized with solution phosphorus-31 nuclear magnetic resonance spectroscopy (P-NMR). Results showed a stratification of TP, TC, TN, pH, PM3, and Mehlich-3-extractable aluminum and magnesium under NT management. The PM3 and orthophosphate concentrations were greater at the soil surface (0-5 cm) of the NT-P (soil treatment with 35 kg P ha) treatment. Organic P forms (orthophosphate monoesters, especially -IP, and nucleotides) had accumulated in the deep layer of NT treatment possibly due to preferential movement. We found evidence that the NT system and P fertilization changed the distribution of P forms along the soil profile, potentially increasing soluble inorganic P loss in surface runoff and organic P in drainage and decreasing bioavailability of inorganic and organic P in deeper soil layers.
Near-infrared reflectance spectroscopy (NIRS) is a rapid, inexpensive, and accurate analysis technique for a wide variety of materials, and it is increasingly used in soil science. The objectives of our study were to examine the potential of NIRS :o predict (i) soil P extracted by two methods [Mehlich 3 (M3P) and water (Cp)], soil total P (TP), annual crop P-uptake, and annual P-budget, and (ii) other soil chemical properties [total C (TC), total N (TN), pH, and K, Al, Fe, Ca, Mg, Mn, Cu, and Zn extracted by Mehlich 3]. Soil samples (« = 448) were taken over a 7-yr period from an experimental site in Lévis (Québec, Canada) where timothy (Phleum pratense L.) was grown under four combinations of P and N fertilizer. The NIRS equations were developed using 80% of the samples for calibration and 20% for validation. The predictive ability of NIRS was evaluated using the coefficient of determination of validation {R^) and the ratio of standard error of prediction to standard deviation (RPD). Results show that M3P, Cp, crop annual P-uptake, and annual P-budget were not accurately predicted by NIRS [R^ < 0.70 and RPD < 1.75). Similar results were found for K and Cu. However, NIRS predictions were moderately useful for TP, TN, Fe, and Zn (0.70 < R^^ < 0.80 and 1.75 :< RPD < 2.25), moderately successful for TC and Al (0.80 < R^^ < 0.90 and 2.25 < RPD < 3.00), successful for pH and Mg (0.90 < R^^ < 0.95 and 3.00 < RPD < 4.00), and excellent for Ca and Mn (A/ > 0.95 and RPD > 4.00). The NIRS predictive ability of several soil properties appears to be related to their relationship with soil organic C. Although NIRS can predict several soil properties, prediction of total P was the only soil P-related property, correlated to soil C, that was moderately useful.Abbreviations: b, slope of linear regression; Cp, P extracted in water; CV, coefficient of variation; DM, dry matter; ICP, inductively coupled plasma; M3, Mehlich 3; M3P_Col, soil P content extracted using the Mehlich 3 method and analyzed by colorimetry; M3P_ICP, soil P content extracted using the Mehlich 3 method and analyzed by ICP; N, total number of samples; NIRS, near-infrared reflectance spectroscopy; PLSR, partial least squares regression method; R^^, coefficient of determination of calibration; R^^, coefficient of determination of validation; Rep File, repeatability file; RPD, ratio of standard error of prediction to standard deviation; SD, standard deviation; SEC, standard error of calibration; SECV, standard error of cross-validation; SEP, standard error of prediction; SNVD, standard normal variate and detrending; TC, total carbon; TN, total nitrogen; TP, total phosphorus; 1 -VR, coefficient of determination of cross-validation. P hosphorus is an essential nutrient and one of the most limiting for crop production. Mineral and organic P fertilizers are often applied to agricultural soils to achieve optimal crop yield, but amounts exceeding crop requirements can have a negative environmental effect. Several methods and/or techniques of soil analysis, including che...
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.