Empower Innovations in Routine Soil Testing

Conventional soil tests are commonly used to assess single soil characteristics. Thus, many different tests are needed for a full soil fertility/soil quality assessment, which is laborious and expensive. New broad-spectrum soil tests offer the potential to assess many soil characteristics quickly, but often face challenges with calibration, validation, and acceptance in practice. Here, we describe the results of a 20 year research program aimed at overcoming the aforementioned challenges. A three-step approach was applied: (1) selecting and establishing two contrasting rapid broad-spectrum soil tests, (2) relating the results of these new tests to the results of conventional soil tests for a wide variety of soils, and (3) validating the results of the new soil tests through field trials and communicating the results. We selected Near Infrared Spectroscopy (NIRS) and multi-nutrient 0.01 M CaCl2 extraction (1:10 soil to solution ratio; w/v) as broad-spectrum techniques. NIRS was extensively calibrated and validated for the physical, chemical, and biological characteristics of soil. The CaCl2 extraction technique was extensively calibrated and validated for ‘plant available’ nutrients, often in combination with the results of NIRS. The results indicate that the accuracy of NIRS determinations is high for SOM, clay, SOC, ECEC, Ca-CEC, N-total, sand, and inorganic-C (R2 ≥ 0.95) and good for pH, Mg-CEC, and S-total (R2 ≥ 0.90). The combination of the CaCl2 extraction technique and NIRS gave results that related well (R2 > 0.80) to the results of conventional soil tests for P, K, Mg, Na, Mn, Cu, Co, and pH. In conclusion, the three-step approach has revolutionized soil testing in The Netherlands. These two broad-spectrum soil tests have improved soil testing; have contributed to increased insights into the physical, chemical, and biological characteristics of soil; and have thereby led to more sustainable soil management and cropping systems.

Temporal variability of soil fertility indicators and sampling periods in Québec

An inadequate soil sampling time leads to difficulties in interpreting soil tests, to incorrect recommendations for soil amendments and fertilizers, and to inappropriate environmental protection restrictions. Soil samples may be collected from agricultural fields before, during or after the crop growth period. Since the time of soil sample collection can affect soil tests results, the objective of this study was to evaluate the effect of sampling time on measurements representativity of 15 fertility indicators in two fields located in La Pocatière (Québec, Canada). The soils were of fine (G1) and medium (G2) textural groups and were sampled weekly for 33 weeks per year during four years. Data analyses included: descriptive statistics, time series decomposition, and time autocorrelation function (ACF). Since results of these analyses showed a clear seasonal effect only for Mehlich-3 extracted phosphorus (PM3), soil phosphorus saturation index (SPS) for both G1 and G2 soils, and for pHwater for G1 only, we recommend that the sampling calendar should be restricted to the first five weeks of spring (until the end of May) and to the entire fall period (starting in early September). Also, the temporal autocorrelation was four weeks on average. This implies that, for an initial year, whichever date is chosen for the sampling, the following annual sampling should be done within a four-week time window (i.e., two weeks before until two weeks after the initial sampling date). Time series are an important element to consider in selecting a representative sampling period for soil fertility indicators.

UF/IFAS Standardized Fertilization Recommendations for Agronomic Crops

This publication presents in abbreviated form the fertilization recommendations for agronomic crops based on soil tests performed by the UF/IFAS Extension Soil Testing Laboratory (ESTL). It contains the basic information from which ESTL soil-test reports and fertilization recommendations are generated.

Experimental Study on Soil Stabilization Using Fibres

For pavement constructions such as runway and highway construction, fine-grained soils are not suitable because of their undesirable properties such as grading of particle size, low bearing capacity, and more plasticity, and its ability to swell. To improve these soil properties various soil stabilization methods are needed. The stabilization is done by adding various stabilizing materials with the fine-grained soil. Fibres are one of the materials used in soil stabilization. This experimental study has been carried over to improve the bearing capacity of soft soil (from Sholinganallur, Chennai) by using Natural and Artificial fibres. During this study, the soil samples which has been stabilized with various fibres was prepared i.e., soil with Natural fibres (jute fibre) and soil with artificial fibres. In this experimental study, index properties and engineering properties of soft soil or unreinforced samples and stabilized soil samples with fibres are determined. Samples are subjected to various soil tests which have been used to determine the engineering properties of soil. The soil tests such as the standard proctor compaction test, unsoaked California Bearing Ratio (CBR) test, and Unconfined Compression (UCC) test had been done to determine the characteristics of the samples. To determine the properties of the reinforced materials, the fibres also have undergone various geosynthetic laboratory tests. The results of the study show that the bearing capacity of Shollinganallur fine-grained soil can be improved subsequently and water absorption by soil has been reduced significantly by using fibres.

Analytical stress-strain relation for soils

A new stress-strain relation capable of reproducing the entire stress-strain range of typical soil tests is presented. The new relation involves a total of five parameters, four of which can be inferred directly from typical test data. The fifth parameter is a fitting parameter with a relatively narrow range. The capabilities of the new relation is demonstrated by the application to various clay and sand data sets.