Soil K extraction with ammonium‐acetate (NH4OAc) from oven‐dried samples is the most widely used K test method, but drying often increases extracted K compared with field‐moist soil. This study assessed sample drying effects on soil K extracted by NH4OAc and used field response data to correlate K tests based on dried (35–40°C) (DK) and field‐moist (MK) samples for corn (Zea mays L.) and soybean [Glycine max (L.) Merr.] based on 162 single‐ and multi‐year response trials conducted during 6 yr (200 site‐years for corn and 162 for soybean). Potassium (15‐cm depth) extracted by DK was higher than for MK (on average 1.92 times higher). The ratio DK/MK decreased exponentially with increasing K (R2 0.77); increased linearly with soil clay, organic matter (OM), estimated cation exchange capacity (ECEC), and (Ca+Mg)/K ratio (r2 0.15–0.32); and increased with sample moisture but the relationship was poor (r2 0.03). The MK test correlated better than DK with grain yield response. The R2 values for Cate–Nelson (CN), linear‐plateau (LP), and quadratic‐plateau (QP) models across crops were 0.24 to 0.27 for DK and 0.39 to 0.58 for MK. Critical concentration (CC) ranges for corn defined by these models were 144 to 301 mg K kg−1 for DK and 51 to 82 mg K kg−1 for MK; whereas for soybean were 136 to 283 for DK and 49 to 84 for MK. Potassium testing of field‐moist samples predicts crop response to K fertilization better than the common test based on oven‐dried samples.

Soil carbon sequestration is a viable shortterm option to mitigate increased atmospheric CO 2 . In agriculture, strategies to increase the soil carbon (C) sink include no-tillage, cover crops, and improved crop rotation. The objective of this study was to determine the influence of tillage systems on SOC and total N, soil aggregation and aggregate associated C and N in three soil types: Oxisol (Brazil), Vertisol (Argentina), and Mollisol (USA). Long-term tillage experiments included tilled (T) and no-till (NT) systems. A native grassland was included for comparison in each site. Soil samples were taken at 0-5, 0-15, and 15-30 cm depths.Water-stable aggregates (WSA) were separated using a wet-sieving method. Total C and total N were determined by dry combustion. A shift from native grassland to an agroecosystem decreased microbial biomass, but this decrease was less pronounced under NT. Cultivation reduced the mass of macroaggregates and the concentration associated C and N; however among agroecosystems, NT, regardless soil type, tended to be more similar to the native grassland sites. Agroecosystems reduced TOC and total N stocks, regardless of soil type, compared to the native grassland. This effect followed: Mollisol [ Oxisol [ Vertisol, and was more pronounced at the 0-5 cm soil depth than at deeper depths. This loss of C and N was associated with the decrease in the mass of macroaggregates and lower C and N concentrations of the aggregates. Macroaggregation was related to TOC and microbial biomass in the Mollisol, suggesting that the biological process of aggregate formation is the principal mechanism of C protection in these soils. The relationship between TOC and large macroaggregates showed lower values for the Oxisol and Vertisol, indicating that in these soils TOC has a complementary role in macroaggregation.

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Core Ideas The contribution of P indices that include organic P to predict soybean P fertilization response was evaluated. Bioavailable P and MA‐P indices correlated with soybean relative yield. MA‐P index correlated with labile organic P fractions. MA‐P index improved the accuracy to predict soybean yield response to applied P. The use of organic P fraction in soil test P for soybean [Glycine max (L.) Merr.] under no‐till could improve the accuracy to predict crops response to P fertilization. The research objectives were to assess the contribution and accuracy of P indices that include organic‐P fractions to predict soybean yield response to P fertilization in comparison with Bray soil test P (BP). The study included P fertilization experiments conducted in the Pampas Region of Argentina during three growing seasons. We selected sites considering Cate and Nelson quadrants (I, II, III), established by a critical BP concentration of 9 mg P kg−1 and a relative soybean yield (RY) of 85%. Bray P, bioavailable (BioP), particulate (POM‐P), and mineral‐associated (MA‐P) soil P fractions were determined in soil samples from the 0‐ to 5‐cm and 0‐ to 20‐cm depths. Bray P varied from 4.8 to 31 mg P kg−1 and BioP from 8 to 29 mg P kg−1 at the 0‐ to 20‐cm depth. Phosphorus content in POM ranged from 19 to 171 mg P kg−1, and MA‐P ranged from 208 to 446 mg P kg−1. Bioavailable P and MA‐P correlated with RY, whereas POM‐P did not. Bioavailable P performed similarly to BP test to predict soybean yield response to P fertilization. Phosphorus content in MA fraction reduced Cate–Nelson classification errors, improving the accuracy to predict soybean yield response to applied P in comparison with BP test. Sampling at the 0‐ to 5‐cm depth did not improve soil test P performance compared with the 0‐ to 20‐cm depth.

Core Ideas DTPA‐extractable Zn is often used to predict corn response to Zn application. Can DTPA–Zn‐based diagnosis be improved by considering other soil properties? Soil properties did not contribute to explain corn grain yield response. DTPA–Zn allowed to discriminate sites based on their response to Zn fertilization. We determined a Zn‐critical range from 0.86 to 1.30 mg kg−1 (n = 64). Current zinc (Zn) diagnostic methods for corn (Zea mays L.) are often based on soil DTPA (diethylenetriamine‐pentaacetic acid) extractable Zn (DTPA‐Zn). However, calibration of the DTPA‐Zn test may be influenced by other soil properties such as pH, organic matter (SOM) and available Bray‐P (PBray‐1). Our objective was to assess the contribution of soil properties to a DTPA‐Zn model used to predict corn response to Zn fertilization. We conducted 64 field trials with two Zn‐fertilization treatments: with and without Zn fertilization. In all sites, we measured SOM, PBray‐1, pH, and DTPA‐Zn at 0‐ to 20‐cm depth before sowing. Yield difference between Zn‐fertilized and unfertilized treatments (Ydifference) was significant in 33% of the experimental site‐years. In responsive site‐years, the average Ydifference was 0.98 Mg ha‐1 (11.4%). Soil organic matter was the only property that was a significant addition to the DTPA‐Zn model for predicting the corn relative yield (Model R2 including SOM = 0.27). However, the improvement was nominal (Partial R2 of SOM = 0.06). Use of DTPA‐Zn alone was suitable to discriminate Zn responsiveness among site‐years based on the Ydifference by correctly diagnosing 81% of the outcomes. We determined three soil DPTA‐Zn ranges with different probability of resulting in a Ydifference greater than zero when fertilized with Zn: high (<0.9 mg kg‐1), medium (0.9–1.3 mg kg‐1), and low (>1.3 mg kg‐1). These soil‐test‐based Zn recommendations improve the identification of Zn‐deficient soils allowing prevention of yield loss from Zn deficiency and more rational use of Zn fertilizers.

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