Considering inorganic P binding in bio-based products improves prediction of their P fertiliser value
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Considering inorganic P binding in bio-based products improves prediction of their P fertiliser value. / Brod, Eva; Øgaard, Anne Falk; Müller-Stöver, Dorette Sophie; Rubæk, Gitte Holton.
In: Science of the Total Environment, Vol. 836, 155590, 2022.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Considering inorganic P binding in bio-based products improves prediction of their P fertiliser value
AU - Brod, Eva
AU - Øgaard, Anne Falk
AU - Müller-Stöver, Dorette Sophie
AU - Rubæk, Gitte Holton
N1 - Publisher Copyright: © 2022 The Authors
PY - 2022
Y1 - 2022
N2 - Prediction of the relative phosphorus (P) fertiliser value of bio-based fertiliser products is agronomically important, but previous attempts to develop prediction models have often failed due to the high chemical complexity of bio-based fertilisers and the limited number of products included in analyses. In this study, regression models for prediction were developed using independently produced data from 10 different studies on crop growth responses to P applied with bio-based fertiliser products, resulting in a dataset with 69 products. The 69 fertiliser products were organised into four sub-groups, based on the inorganic P compounds most likely to be present in each product. Within each product group, multiple regression was conducted using mineral fertiliser equivalents (MFE) as response variable and three potential explanatory variables derived from chemical analysis, all reflecting inorganic P binding in the fertiliser products: i) NaHCO3-soluble P, ii) molar ratio of calcium (Ca):P and iii) molar ratio of aluminium + iron (Al + Fe):P. The best regression model fit was achieved for sewage sludges with Al-/Fe-bound P (n = 20; R2 = 79.2%), followed by sewage sludges with Ca-bound P (n = 11; R2 = 71.1%); fertiliser products with Ca-bound P (n = 29; R2 = 58.2%); and thermally treated sewage sludge products (n = 9; R2 = 44.9%). Even though external factors influencing P fertiliser values (e.g. fertiliser shape, application form, soil characteristics) differed between the underlying studies and were not considered, the suggested prediction models provide potential for more efficient P recycling in practice.
AB - Prediction of the relative phosphorus (P) fertiliser value of bio-based fertiliser products is agronomically important, but previous attempts to develop prediction models have often failed due to the high chemical complexity of bio-based fertilisers and the limited number of products included in analyses. In this study, regression models for prediction were developed using independently produced data from 10 different studies on crop growth responses to P applied with bio-based fertiliser products, resulting in a dataset with 69 products. The 69 fertiliser products were organised into four sub-groups, based on the inorganic P compounds most likely to be present in each product. Within each product group, multiple regression was conducted using mineral fertiliser equivalents (MFE) as response variable and three potential explanatory variables derived from chemical analysis, all reflecting inorganic P binding in the fertiliser products: i) NaHCO3-soluble P, ii) molar ratio of calcium (Ca):P and iii) molar ratio of aluminium + iron (Al + Fe):P. The best regression model fit was achieved for sewage sludges with Al-/Fe-bound P (n = 20; R2 = 79.2%), followed by sewage sludges with Ca-bound P (n = 11; R2 = 71.1%); fertiliser products with Ca-bound P (n = 29; R2 = 58.2%); and thermally treated sewage sludge products (n = 9; R2 = 44.9%). Even though external factors influencing P fertiliser values (e.g. fertiliser shape, application form, soil characteristics) differed between the underlying studies and were not considered, the suggested prediction models provide potential for more efficient P recycling in practice.
KW - Chemical extraction
KW - Phosphorus recycling
KW - Plant availability
KW - Relative agronomic efficiency
KW - Solubility
KW - Waste resources
U2 - 10.1016/j.scitotenv.2022.155590
DO - 10.1016/j.scitotenv.2022.155590
M3 - Journal article
C2 - 35490815
AN - SCOPUS:85129598173
VL - 836
JO - Science of the Total Environment
JF - Science of the Total Environment
SN - 0048-9697
M1 - 155590
ER -
ID: 318446753