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Humic substances are increasingly used as biostimulants in agriculture because of their supposed effects on nutrient uptake and crop yield. The objective of this study was to assess the effect of fulvic acid (FA) and humic acid (HA) addition with and without fertilization (N, P, K, S, and Ca) on (i) grass yield (Poa trivialis) and nutrient uptake and (ii) composition of soil porewater and 0.01 M CaCl2 soil extracts. Therefore, a pot experiment was performed using a loamy soil and a non-calcareous sandy soil. Fertilization increased N and P uptake and grass yield but there was no effect of FA or HA application (200 mg C kg���1 soil) regardless of whether N or P was the growth limiting nutrient. Nutrient availability was assessed in soil pore water samples extracted by centrifugating moist soil and by 0.01 M CaCl2 extracts of oven-dried soil. HA and FA had no effect on the availability of NO3 or ortho-P, neither in soil porewater nor in 0.01 M CaCl2 soil extracts. Fertilization led to an increase in 0.01 M CaCl2-extractable ortho-P but, remarkably, to a decrease in ortho-P and Dissolved Organic Carbon (DOC) concentrations in soil pore water samples. This discrepancy was explained by the higher ionic strength of pore water in the fertilized soils, which caused the pH to drop by 0.2 to 0.4 units and thereby stimulated adsorption of ortho-P and DOC to reactive soil minerals. Such salt-induced effects do not occur in 0.01 M CaCl2 soil extracts where the ionic strength is nearly constant.

Amino acids can interfere with NH4+ in spectrophotometric NH4+ determination hampering accurate quantification of the fate of NH4+ and dissolved organic N in soils. Serious interference has been reported for soils rich in organic matter, and for soils that have been fumigated, oven-dried or fertilized where between 5 and 60% of the NH4+ detected could be attributed to amino acid interference. We investigated whether a combination of gas diffusion and the classical Berthelot method can eliminate this interference, increasing the selectivity of the NH4+ analysis. We tested this approach using synthetic amino acid solutions and a large set of terrestrial samples (n = 353), including pore water samples, (fumigated or dried) soil extracts, and extracts of manures, composts and crop residues. The evaluated method produced accurate (recovery > 99.7%) and reproducible (standard error = 2.2%) NH4+ concentrations, eliminating any interference between amino acids and NH4+ (interference

11 páginas, 7 figuras, 7 tablas., Many empirical equations have been developed to predict the properties of saturation extracts, primarily electrical conductivity, from the properties of soil water extracts of 1 to 5 ratio. Soil water 1:5 extracts are more rapidly and reproducibly prepared than saturation extracts. However, the electrical conductivity of saturation extracts (ECse) is the benchmark to assess soil salinity. Analysis of the information provided by the electrical conductivity of soil 1:5 extracts (EC1:5) is a prerequisite to guide equation development and to use EC1:5 for soil salinity assessment. A total of 135 soil samples were taken from 39 sites at up to four different depths per site, down to a maximum depth of 95 cm in an irrigated agricultural area in SE Spain. Soil 1:5 extracts obtained from each sample were analysed for twelve chemical properties: concentration of sodium, ammonium, potassium, magnesium, calcium, chloride, nitrite, nitrate, sulphate, alkalinity and electrical conductivity. A principal component analysis (PCA) was applied to the correlation matrix of the log-transformed data set. The equilibrium status of 1:5 extracts with regard to gypsum was assessed with the chemical speciation programme SALSOLCHEMIS. The soil gypsum content was determined by using an adaptation of the classical method of total dissolution of soil gypsum, adequate to determine low gypsum contents, i.e. lower than 2%. Three principal components, accounting for 82% of the variance in the correlation matrix, were retained after eigenvector extraction. The first component accounted for 53% of the variance and was interpreted as representing the extract salinity due to gypsum dissolution. The second component accounted for 16% of the variance and was interpreted as representing the component of the extract salinity due to salts more soluble than gypsum, such as sodium and chloride salts. The information about soil salinity is split in two components in the 1:5 extracts, which are not easily resolved, whereas only one salinity component was obtained in the saturation extracts. The EC1:5 is a reliable property to estimate ECse, with a 95% confidence interval of ±1.2 dS m−1, only when it is lower than 1 dS m−1. When EC1:5 is higher than 2.4 dS m−1 it could also be reliably used to estimate soil salinity only if the 1:5 extract is gypsum-saturated, which is highly probable when the soil gypsum content is higher than 1.5%, or when the saturation extract is not gypsumsaturated, situation which happens when soil gypsum content is lower than 0.2%. When the EC1:5 is between 1 and 2.4 dS m−1, it provides poor information about the ECse, which could be between 4 and 14 dS m−1 unless the soil gypsum content is negligible, i.e. lower than 0.2%. The usefulness of the EC1:5 to estimate soil salinity can be extended when it is used in conjunction with an estimate of soil gypsum content. The development of more than one equation to estimate ECse from EC1:5 depending on soil gypsum content is recommended., We thank the Conselleria de Medi Ambient from the Generalitat Valenciana for funding this research through project GV 0461/2006. We would also like to thank the two anonymous reviewers, and editor-in-chief for their fruitful comments and indications, which improved the article.