Assessment of soil properties by organic matter and EM-microorganism incorporation

Properties of a claim loam soil, collected in Aranjuez (Madrid) and enriched with organic matter and microorganisms, were evaluated under controlled temperature and moisture conditions, over a period of three months. The following treatments were carried out: soil (control); soil + 50 t ha-1 of animal manure (E50); soil + 50 t ha-1 of animal manure + 30 L ha-1 of effective microorganisms (E50EM); soil + 30 t ha-1 of the combination of various green crop residues and weeds (RC30) and soil + 30 t ha-1 of the combination of various green crop residues and weeds + 30 L ha-1 of effective microorganisms (RC30EM). Soil samples were taken before and after incubation and their physical, chemical, and microbiological parameters analyzed. Significant increase was observed in the production of exopolysaccharides and basic phosphatase and esterase enzyme activities in the treatments E50EM and RC30EM, in correlation with the humification of organic matter, water retention at field capacity, and the cationic exchange capacity (CEC) of the same treatments. The conclusion was drawn that the incorporation of a mixture of effective microorganisms (EM) intensified the biological soil activity and improved physical and chemical soil properties, contributing to a quick humification of fresh organic matter. These findings were illustrated by the microbiological activities of exopolysaccharides and by alkaline phosphatase and esterase enzymes, which can be used as early and integrated soil health indicators.

Carbon dioxide efflux in a rhodic hapludox as affected by tillage systems in southern Brazil

Agricultural soils can act as a source or sink of atmospheric C, according to the soil management. This long-term experiment (22 years) was evaluated during 30 days in autumn, to quantify the effect of tillage systems (conventional tillage-CT and no-till-NT) on the soil CO2-C flux in a Rhodic Hapludox in Rio Grande do Sul State, Southern Brazil. A closed-dynamic system (Flux Chamber 6400-09, Licor) and a static system (alkali absorption) were used to measure soil CO2-C flux immediately after soybean harvest. Soil temperature and soil moisture were measured simultaneously with CO2-C flux, by Licor-6400 soil temperature probe and manual TDR, respectively. During the entire month, a CO2-C emission of less than 30 % of the C input through soybean crop residues was estimated. In the mean of a 30 day period, the CO2-C flux in NT soil was similar to CT, independent of the chamber type used for measurements. Differences in tillage systems with dynamic chamber were verified only in short term (daily evaluation), where NT had higher CO2-C flux than CT at the beginning of the evaluation period and lower flux at the end. The dynamic chamber was more efficient than the static chamber in capturing variations in CO2-C flux as a function of abiotic factors. In this chamber, the soil temperature and the water-filled pore space (WFPS), in the NT soil, explained 83 and 62 % of CO2-C flux, respectively. The Q10 factor, which evaluates CO2-C flux dependence on soil temperature, was estimated as 3.93, suggesting a high sensitivity of the biological activity to changes in soil temperature during fall season. The CO2-C flux measured in a closed dynamic chamber was correlated with the static alkali adsorption chamber only in the NT system, although the values were underestimated in comparison to the other, particularly in the case of high flux values. At low soil temperature and WFPS conditions, soil tillage caused a limited increase in soil CO2-C flux.

Dielectric constant obtained from TDR and volumetric moisture of soils in southern Brazil

Soil moisture is the property which most greatly influences the soil dielectric constant, which is also influenced by soil mineralogy. The aim of this study was to determine mathematical models for soil moisture and the dielectric constant (Ka) for a Hapludalf, two clayey Hapludox and a very clayey Hapludox and test the reliability of universal models, such as those proposed by Topp and Ledieu and their co-workers in the 80's, and specific models to estimate soil moisture with a TDR. Soil samples were collected from the 0 to 0.30 m layer, sieved through a mesh of 0.002 m diameter and packed in PVC cylinders with a 0.1 m diameter and 0.3 m height. Seven samples of each soil class were saturated by capillarity and a probe composed of two rods was inserted in each one of them. Moisture readings began with the saturated soil and concluded when the soil was near permanent wilting point. In each step, the samples were weighed on a precision scale to calculate volumetric moisture. Linear and polynomial models were adjusted for each soil class and for all soils together between soil moisture and the dielectric constant. Accuracy of the models was evaluated by the coefficient of determination, the standard error of estimate and the 1:1 line. The models proposed by Topp and Ledieu and their co-workers were not adequate for estimating the moisture in the soil classes studied. The adjusted linear and polynomial models for the entire set of data of the four soil classes did not have sufficient accuracy for estimating soil moisture. The greater the soil clay and Fe oxide content, the greater the dielectric constant of the medium for a given volumetric moisture. The specific models, θ = 0.40283 - 0.04231 Ka + 0.00194 Ka² - 0.000022 Ka³ (Hapludox) θ = 0.01971 + 0.02902 Ka - 0.00086 Ka² + 0.000012 Ka³ (Hapludox -PF), θ = 0.01692 - 0.00507 Ka (Hapludalf) and θ = 0.08471 + 0.01145 Ka (Hapludox-CA), show greater accuracy and reliability for estimating soil moisture in the soil classes studied.

Monitoring nitrogen nutrition in cotton

Both N excess and deficiency may affect cotton yield and quality. It would therefore be useful to base the N management fertilization on the monitoring of the nutritional status. This study investigated the correlations among the following determination methods of the N nutritional status of cotton (Gossypium hirsutum L., var. Latifolia): chlorophyll readings (SPAD-502®, Minolta), specific-ion nitrate meter (Nitrate Meter C-141, Horiba-Cardy®), and laboratory analysis (conventional foliar diagnosis). Samples were taken weekly from two weeks before flowering to the fifth week after the first flower. The experiment was conducted on the Fazenda Santa Tereza, Itapeva, State of São Paulo, Brazil. The crop was fertilized with 40 kg ha-1 N at planting and 0, 30, 60, 90, and 120 kg ha-1 of side-dressed N. The range of leaf N contents reported as adequate for samples taken 80-90 days after plant emergence (traditional foliar diagnosis) may be used as reference from the beginning of flowering when the plant is not stressed. Specific-ion nitrate meter readings can be used as a nutritional indicator of cotton nutrition from one week after pinhead until the third week of flowering. In this case, plants are well-nourished when readings exceed 8,000 mg L-1 NO3-. The chlorophyll meter can also be used to estimate the nutritional status of cotton from the third week of flowering. In this case the readings should be above 48 in well-nourished plants.

Long-term C-CO2 emissions and carbon crop residue mineralization in an oxisol under different tillage and crop rotation systems

Soil C-CO2 emissions are sensitive indicators of management system impacts on soil organic matter (SOM). The main soil C-CO2 sources at the soil-plant interface are the decomposition of crop residues, SOM turnover, and respiration of roots and soil biota. The objectives of this study were to evaluate the impacts of tillage and cropping systems on long-term soil C-CO2 emissions and their relationship with carbon (C) mineralization of crop residues. A long-term experiment was conducted in a Red Oxisol in Cruz Alta, RS, Brazil, with subtropical climate Cfa (Köppen classification), mean annual precipitation of 1,774 mm and mean annual temperature of 19.2 ºC. Treatments consisted of two tillage systems: (a) conventional tillage (CT) and (b) no tillage (NT) in combination with three cropping systems: (a) R0- monoculture system (soybean/wheat), (b) R1- winter crop rotation (soybean/wheat/soybean/black oat), and (c) R2- intensive crop rotation (soybean/ black oat/soybean/black oat + common vetch/maize/oilseed radish/wheat). The soil C-CO2 efflux was measured every 14 days for two years (48 measurements), by trapping the CO2 in an alkaline solution. The soil gravimetric moisture in the 0-0.05 m layer was determined concomitantly with the C-CO2 efflux measurements. The crop residue C mineralization was evaluated with the mesh-bag method, with sampling 14, 28, 56, 84, 112, and 140 days after the beginning of the evaluation period for C measurements. Four C conservation indexes were used to assess the relation between C-CO2 efflux and soil C stock and its compartments. The crop residue C mineralization fit an exponential model in time. For black oat, wheat and maize residues, C mineralization was higher in CT than NT, while for soybean it was similar. Soil moisture was higher in NT than CT, mainly in the second year of evaluation. There was no difference in tillage systems for annual average C-CO2 emissions, but in some individual evaluations, differences between tillage systems were noticed for C-CO2 evolution. Soil C-CO2 effluxes followed a bi-modal pattern, with peaks in October/November and February/March. The highest emission was recorded in the summer and the lowest in the winter. The C-CO2 effluxes were weakly correlated to air temperature and not correlated to soil moisture. Based on the soil C conservation indexes investigated, NT associated to intensive crop rotation was more C conserving than CT with monoculture.

Spatial patterns of preconsolidation pressure and soil moisture along transects in two directions under coffee

Information on the spatial structure of soil physical and structural properties is needed to evaluate the soil quality. The purpose of this study was to investigate the spatial behavior of preconsolidation pressure and soil moisture in six transects, three selected along and three across coffee rows, at three different sites under different tillage management systems. The study was carried out on a farm, in Patrocinio, state of Minas Gerais, in the Southeast of Brazil (18 º 59 ' 15 '' S; 46 º 56 ' 47 '' W; 934 m asl). The soil type is a typic dystrophic Red Latosol (Acrustox) and consists of 780 g kg-1 clay; 110 g kg-1 silt and 110 g kg-1 sand, with an average slope of 3 %. Undisturbed soil cores were sampled at a depth of 0.10-0.13 m, at three different points within the coffee plantation: (a) from under the wheel track, where equipment used in farm operations passes; (b) in - between tracks and (c) under the coffee canopy. Six linear transects were established in the experimental area: three transects along and three across the coffee rows. This way, 161 samples were collected in the transect across the coffee rows, from the three locations, while 117 samples were collected in the direction along the row. The shortest sampling distance in the transect across the row was 4 m, and 0.5 m for the transect along the row. No clear patterns of the preconsolidation pressure values were observed in the 200 m transect. The results of the semivariograms for both variables indicated a high nugget value and short range for the studied parameters of all transects. A cyclic pattern of the parameters was observed for the across-rows transect. An inverse relationship between preconsolidation pressure and soil moisture was clearly observed in the samples from under the track, in both directions.

Beaufils ranges to assess the cotton nutrient status in the southern region of Mato Grosso

The relationships between nutrient contents and indices of the Diagnosis and Recommendation Integrated System (DRIS) are a useful basis to determine appropriate ranges for the interpretation of leaf nutrient contents. The purpose of this study was to establish Beaufils ranges from statistical models of the relationship between foliar concentrations and DRIS indices, generated by two systems of DRIS norms - the F value and natural logarithm transformation - and assess the nutritional status of cotton plants, based on these Beaufils ranges. Yield data from plots (average acreage 100 ha) and foliar concentrations of macro and micronutrients of cotton (Gossypium hirsutum r. latifolium) plants, in the growing season 2004/2005, were stored in a database. The criterion to define the reference population consisted of plots with above-average yields + 0.5 standard deviation (over 4,575 kg ha-1 seed cotton yield). The best-fitting statistical model of the relationship between foliar nutrient concentrations and DRIS indices was linear, with R² > 0.8090, p < 0.01, except for N, with R² = 0.5987, p < 0.01. The two criteria were effective to diagnose the plant nutritional status. The diagnoses were not random, but based on the effectiveness of the chi-square-tested method. The agreement between the methods to assess the nutritional status was 92.59-100 %, except for S, with 74.07 % agreement.

Compared boron uptake and translocation in cotton cultivars

The mobility of boron (B), a commonly deficient micronutrient in cotton, has been shown to be low in the plant phloem. Nevertheless, studies have indicated that cotton cultivars can respond differently to B application. A greenhouse experiment was conducted to compare B absorption and mobility in cotton cultivars grown in nutrient solution. Treatments consisted of three cotton cultivars (FMT 701, DP 604BG and FMX 993), and five B rates (0.0, 2.5, 5.0, 10.0, and 20.0 µmol L-1). Plant growth and development were monitored for four weeks from the appearance of the first square. The time of onset and severity of B deficiency symptoms varied among cotton cultivars. Initial B uptake of cv. DP 604BG was lower than of the other cultivars, but a greater amount of available B in the nutrient solution was required to prevent deficiency symptoms in this cultivar. Boron deficiency impairs cotton growth, with no differences among cultivars, regardless of the time of appearance and intensity of B deficiency symptoms.

N2O emissions from a cultivated mollisol: optimal time of day for sampling and the role of soil temperature

The correct use of closed field chambers to determine N2O emissions requires defining the time of day that best represents the daily mean N2O flux. A short-term field experiment was carried out on a Mollisol soil, on which annual crops were grown under no-till management in the Pampa Ondulada of Argentina. The N2O emission rates were measured every 3 h for three consecutive days. Fluxes ranged from 62.58 to 145.99 ∝g N-N2O m-2 h-1 (average of five field chambers) and were negatively related (R² = 0.34, p < 0.01) to topsoil temperature (14 - 20 ºC). N2O emission rates measured between 9:00 and 12:00 am presented a high relationship to daily mean N2O flux (R² = 0.87, p < 0.01), showing that, in the study region, sampling in the mornings is preferable for GHG.

Soil thermal diffusivity estimated from data of soil temperature and single soil component properties

Under field conditions, thermal diffusivity can be estimated from soil temperature data but also from the properties of soil components together with their spatial organization. We aimed to determine soil thermal diffusivity from half-hourly temperature measurements in a Rhodic Kanhapludalf, using three calculation procedures (the amplitude ratio, phase lag and Seemann procedures), as well as from soil component properties, for a comparison of procedures and methods. To determine thermal conductivity for short wave periods (one day), the phase lag method was more reliable than the amplitude ratio or the Seemann method, especially in deeper layers, where temperature variations are small. The phase lag method resulted in coherent values of thermal diffusivity. The method using properties of single soil components with the values of thermal conductivity for sandstone and kaolinite resulted in thermal diffusivity values of the same order. In the observed water content range (0.26-0.34 m³ m-3), the average thermal diffusivity was 0.034 m² d-1 in the top layer (0.05-0.15 m) and 0.027 m² d-1 in the subsurface layer (0.15-0.30 m).

Methane fluxes from waterlogged and drained Histosols of highland areas

Soil can be either source or sink of methane (CH4), depending on the balance between methanogenesis and methanotrophy, which are determined by pedological, climatic and management factors. The objective of this study was to assess the impact of drainage of a highland Haplic Histosol on CH4 fluxes. Field research was carried out in Ponta Grossa (Paraná, Brazil) based on the measurement of CH4 fluxes by the static chamber method in natural and drained Histosol, over one year (17 sampling events). The natural Histosol showed net CH4 eflux, with rates varying from 238 µg m-2 h-1 CH4, in cool/cold periods, to 2,850 µg m-2 h-1 CH4, in warm/hot periods, resulting a cumulative emission of 116 kg ha-1 yr-1 CH4. In the opposite, the drained Histosol showed net influx of CH4 (-39 to -146 µg m-2 h-1), which resulted in a net consumption of 9 kg ha-1 yr-1 CH4. The main driving factors of CH4 consumption in the drained soil were the lowering of the water-table (on average -57 cm, vs -7 cm in natural soil) and the lower water content in the 0-10 cm layer (average of 5.5 kg kg-1, vs 9.9 kg kg-1 in natural soil). Although waterlogged Histosols of highland areas are regarded as CH4 sources, they fulfill fundamental functions in the ecosystem, such as the accumulation of organic carbon (581 Mg ha-1 C to a depth of 1 m) and water (8.6 million L ha-1 = 860 mm to a depth of 1 m). For this reason, these soils must not be drained as an alternative to mitigate CH4 emission, but effectively preserved.

Aggregate stability by the "high energy moisture characteristic" method in an oxisol under differentiated management

Studies testing the High Energy Moisture Characteristic (HEMC) technique in tropical soils are still incipient. By this method, the effects of different management systems can be evaluated. This study investigated the aggregation state of an Oxisol under coffee with Brachiaria between crop rows and surface-applied gypsum rates using HEMC. Soil in an experimental area in the Upper São Francisco region, Minas Gerais, was studied at depths of 0.05 and 0.20 m in coffee rows. The treatments consisted of 0, 7, and 28 Mg ha-1 of agricultural gypsum rates distributed on the soil surface of the coffee rows, between which Brachiaria was grown and periodically cut, and compared with a treatment without Brachiaria between coffee rows and no gypsum application. To determine the aggregation state using the HEMC method, soil aggregates were placed in a Büchner funnel (500 mL) and wetted using a peristaltic pump with a volumetric syringe. The wetting was applied increasingly at two pre-set speeds: slow (2 mm h-1) and fast (100 mm h-1). Once saturated, the aggregates were exposed to a gradually increasing tension by the displacement of a water column (varying from 0 to 30 cm) to obtain the moisture retention curve [M = f (Ψ) ], underlying the calculation of the stability parameters: modal suction, volume of drainable pores (VDP), stability index (slow and fast), VDP ratio, and stability ratio. The HEMC method conferred sensitivity in quantifying the aggregate stability parameters, and independent of whether gypsum was used, the soil managed with Brachiaria between the coffee rows, with regular cuts discharged in the crop row direction, exhibited a decreased susceptibility to disaggregation.

Comparing the artificial neural network with parcial least squares for prediction of soil organic carbon and pH at different moisture content levels using visible and near-infrared spectroscopy

Visible and near infrared (vis-NIR) spectroscopy is widely used to detect soil properties. The objective of this study is to evaluate the combined effect of moisture content (MC) and the modeling algorithm on prediction of soil organic carbon (SOC) and pH. Partial least squares (PLS) and the Artificial neural network (ANN) for modeling of SOC and pH at different MC levels were compared in terms of efficiency in prediction of regression. A total of 270 soil samples were used. Before spectral measurement, dry soil samples were weighed to determine the amount of water to be added by weight to achieve the specified gravimetric MC levels of 5, 10, 15, 20, and 25 %. A fiber-optic vis-NIR spectrophotometer (350-2500 nm) was used to measure spectra of soil samples in the diffuse reflectance mode. Spectra preprocessing and PLS regression were carried using Unscrambler® software. Statistica® software was used for ANN modeling. The best prediction result for SOC was obtained using the ANN (RMSEP = 0.82 % and RPD = 4.23) for soil samples with 25 % MC. The best prediction results for pH were obtained with PLS for dry soil samples (RMSEP = 0.65 % and RPD = 1.68) and soil samples with 10 % MC (RMSEP = 0.61 % and RPD = 1.71). Whereas the ANN showed better performance for SOC prediction at all MC levels, PLS showed better predictive accuracy of pH at all MC levels except for 25 % MC. Therefore, based on the data set used in the current study, the ANN is recommended for the analyses of SOC at all MC levels, whereas PLS is recommended for the analysis of pH at MC levels below 20 %.

APPRAISAL OF THE SNAP MODEL FOR PREDICTING NITROGEN MINERALIZATION IN TROPICAL SOILS UNDER EUCALYPTUS

The Soil Nitrogen Availability Predictor (SNAP) model predicts daily and annual rates of net N mineralization (NNM) based on daily weather measurements, daily predictions of soil water and soil temperature, and on temperature and moisture modifiers obtained during aerobic incubation (basal rate). The model was based on in situ measurements of NNM in Australian soils under temperate climate. The purpose of this study was to assess this model for use in tropical soils under eucalyptus plantations in São Paulo State, Brazil. Based on field incubations for one month in three, NNM rates were measured at 11 sites (0-20 cm layer) for 21 months. The basal rate was determined in in situ incubations during moist and warm periods (January to March). Annual rates of 150-350 kg ha-1 yr-1 NNM predicted by the SNAP model were reasonably accurate (R2 = 0.84). In other periods, at lower moisture and temperature, NNM rates were overestimated. Therefore, if used carefully, the model can provide adequate predictions of annual NNM and may be useful in practical applications. For NNM predictions for shorter periods than a year or under suboptimal incubation conditions, the temperature and moisture modifiers need to be recalibrated for tropical conditions.

Nitrogen and Potassium in Narrow-Row Cotton

ABSTRACT Information on fertilizer management for cotton in narrow-row cropping system is scarce; therefore, studies are needed to improve nutrient stewardship for such systems. The aim of this study was to evaluate the effects of nitrogen and potassium application on yield and fiber quality of cotton under a narrow-row system. A field trial was carried out for three years, where the treatments were set up in an incomplete factorial arrangement [(4 × 4) + 1] under a randomized block design, with four N rates (20, 40, 60, and 80 kg ha-1), four K2O rates (0, 40, 80, and 120 kg ha-1), and one control (no N or K2O), for a total of 17 treatments, with four replicates. Urea and potassium chloride were applied on the soil surface 20 days after crop emergence. Varieties used were FMT 701 (2009/2010 and 2010/2011) and FMT 709 (2011/2012). Cotton yield and fiber quality parameters were measured. In the narrow-row cropping system, cotton lint yield was positively affected by N and K application. Cotton yield in relation to K applications was not dependent on N rates. Potassium application increased the micronaire index and fiber resistance, whereas high N rates reduced fiber resistance.