Spatial relationships between soil attributes and corn yield in no-tillage system

Soil properties play an important role in spatial variability of crop yield. However, a low spatial correlation has generally been observed between maps of crop yield and of soil properties. The objectives of the present investigation were to assess the spatial pattern variability of soil properties and of corn yield at the same sampling intensity, and evaluate its cause-and-effect relationships. The experimental site was structured in a grid of 100 referenced points, spaced at 10 m intervals along four parallel 250 m long rows spaced 4.5 m apart. Thus, points formed a rectangle containing four columns and 25 rows. Therefore, each sampling cell encompassed an area of 45 m² and consisted of five 10 m long crop rows, in which the referenced points represented the center. Samples were taken from the layers 0-0.1 m and 0.1-0.2 m. Soil physical and chemical properties were evaluated. Statistical analyses consisted of data description and geostatistics. The spatial dependence of corn yield and soil properties was confirmed. The hypothesis of this study was confirmed, i.e., when sampling the soil to determine the values of soil characteristics at similar to sampling intensity as for crop yield assessments, correlations between the spatial distribution of soil characteristics and crop yield were observed. The spatial distribution pattern of soil properties explained 65 % of the spatial distribution pattern of corn yield. The spatial distribution pattern of clay content and percentage of soil base saturation explained most of the spatial distribution pattern of corn yield.

Characterization of soil chemical properties of strawberry fields using principal component analysis

One of the largest strawberry-producing municipalities of Rio Grande do Sul (RS) is Turuçu, in the South of the State. The strawberry production system adopted by farmers is similar to that used in other regions in Brazil and in the world. The main difference is related to the soil management, which can change the soil chemical properties during the strawberry cycle. This study had the objective of assessing the spatial and temporal distribution of soil fertility parameters using principal component analysis (PCA). Soil sampling was based on topography, dividing the field in three thirds: upper, middle and lower. From each of these thirds, five soil samples were randomly collected in the 0-0.20 m layer, to form a composite sample for each third. Four samples were taken during the strawberry cycle and the following properties were determined: soil organic matter (OM), soil total nitrogen (N), available phosphorus (P) and potassium (K), exchangeable calcium (Ca) and magnesium (Mg), soil pH (pH), cation exchange capacity (CEC) at pH 7.0, soil base (V%) and soil aluminum saturation(m%). No spatial variation was observed for any of the studied soil fertility parameters in the strawberry fields and temporal variation was only detected for available K. Phosphorus and K contents were always high or very high from the beginning of the strawberry cycle, while pH values ranged from very low to very high. Principal component analysis allowed the clustering of all strawberry fields based on variables related to soil acidity and organic matter content.

Optimization of the sampling scheme for maps of physical and chemical properties estimated by kriging

The sampling scheme is essential in the investigation of the spatial variability of soil properties in Soil Science studies. The high costs of sampling schemes optimized with additional sampling points for each physical and chemical soil property, prevent their use in precision agriculture. The purpose of this study was to obtain an optimal sampling scheme for physical and chemical property sets and investigate its effect on the quality of soil sampling. Soil was sampled on a 42-ha area, with 206 geo-referenced points arranged in a regular grid spaced 50 m from each other, in a depth range of 0.00-0.20 m. In order to obtain an optimal sampling scheme for every physical and chemical property, a sample grid, a medium-scale variogram and the extended Spatial Simulated Annealing (SSA) method were used to minimize kriging variance. The optimization procedure was validated by constructing maps of relative improvement comparing the sample configuration before and after the process. A greater concentration of recommended points in specific areas (NW-SE direction) was observed, which also reflects a greater estimate variance at these locations. The addition of optimal samples, for specific regions, increased the accuracy up to 2 % for chemical and 1 % for physical properties. The use of a sample grid and medium-scale variogram, as previous information for the conception of additional sampling schemes, was very promising to determine the locations of these additional points for all physical and chemical soil properties, enhancing the accuracy of kriging estimates of the physical-chemical properties.

Variability of soil fertility properties in areas planted to sugarcane in the State of Goias, Brazil

Soil sampling should provide an accurate representation of a given area so that recommendations for amendments of soil acidity, fertilization and soil conservation may be drafted to increase yield and improve the use of inputs. The aim of this study was to evaluate the variability of soil fertility properties of Oxisols in areas planted to sugarcane in the State of Goias, Brazil. Two areas of approximately 8,100 m² each were selected, representing two fields of the Goiasa sugarcane mill in Goiatuba. The sugarcane crop had a row spacing of 1.5 m and subsamples were taken from 49 points in the row and 49 between the row with a Dutch auger at depths of 0.0-0.2 and 0.2-0.4 m, for a total of 196 subsamples for each area. The samples were individually subjected to chemical analyses of soil fertility (pH in CaCl2, potential acidity, organic matter, P, K, Ca and Mg) and particle size analysis. The number of subsamples required to compose a sample within the acceptable ranges of error of 5, 10, 20 and 40 % of each property were computed from the coefficients of variation and the Student t-value for 95 % confidence. The soil properties under analysis exhibited different variabilities: high (P and K), medium (potential acidity, Ca and Mg) and low (pH, organic matter and clay content). Most of the properties analyzed showed an error of less than 20 % for a group of 20 subsamples, except for P and K, which were capable of showing an error greater than 40 % around the mean. The extreme variability in phosphorus, particularly at the depth of 0.2-0.4 m, attributed to banded application of high rates of P fertilizers at planting, places limitations on assessment of its availability due to the high number of subsamples required for a composite sample.

ORGANIC PHOSPHORUS FRACTIONS IN SOIL FERTILIZED WITH CATTLE MANURE

Inorganic phosphorus (Pi) usually controls the P availability in tropical soils, but the contribution of organic P (Po) should not be neglected, mainly in systems with low P input or management systems that promote organic matter accumulation. The aims of this study were to evaluate the changes in the Po fractions over time in soil fertilized and not fertilized with cattle manure and to correlate Po forms with available P extracted by anion exchange resin. The experiment was carried out under field conditions, in a sandy-clay loam Haplustox. The experimental design was a 2 × 9 randomized complete block factorial design, in which the first factor was manure application (20 t ha-1) or absence, and the second the soil sampling times (3, 7, 14, 21, 28, 49, 70, 91, and 112 days) after manure incorporation. Labile, moderately labile and non-labile Po fractions were determined in the soil material of each sampling. Manure fertilization increased the Po levels in the moderately labile and non-labile fractions and the total organic P, but did not affect the Po fraction proportions in relation to total organic P. On average, 5.1 % of total Po was in the labile, 44.4 % in the moderately labile and 50.5 % in the non-labile fractions. Available P (resin P) was more affected by the manure soluble Pi rather than by the labile Po forms. The labile and non-labile Po fractions varied randomly with no defined trend in relation to the samplings; for this reason, the data did not fit any mathematical model.

Changes in Soil Organic Carbon Fractions in Response to Cover Crops in an Orange Orchard

ABSTRACT The cultivation of cover crops intercropped with fruit trees is an alternative to maintain mulch cover between plant rows and increase soil organic carbon (C) stocks. The objective of this study was to evaluate changes in soil total organic C content and labile organic matter fractions in response to cover crop cultivation in an orange orchard. The experiment was performed in the state of Bahia, in a citrus orchard with cultivar ‘Pera’ orange (Citrus sinensis) at a spacing of 6 × 4 m. A randomized complete block design with three replications was used. The following species were used as cover crops: Brachiaria (Brachiaria decumbes) – BRAQ, pearl millet (Pennisetum glaucum) – MIL, jack bean (Canavalia ensiformis) – JB, blend (50 % each) of jack bean + millet (JB/MIL), and spontaneous vegetation (SPV). The cover crops were broadcast-seeded between the rows of orange trees and mechanically mowed after flowering. Soil sampling at depths of 0.00-0.10, 0.10-0.20, and 0.20-0.40 m was performed in small soil trenches. The total soil organic C (SOC) content, light fraction (LF), and the particulate organic C (POC), and oxidizable organic C fractions were estimated. Total soil organic C content was not significantly changed by the cover crops, indicating low sensitivity in reacting to recent changes in soil organic matter due to management practices. Grasses enabled a greater accumulation of SOC stocks in 0.00-0.40 m compared to all other treatments. Jack bean cultivation increased LF and the most labile oxidizable organic C fraction (F1) in the soil surface and the deepest layer tested. Cover crop cultivation increased labile C in the 0.00-0.10 m layer, which can enhance soil microbial activity and nutrient absorption by the citrus trees. The fractions LF and F1 may be suitable indicators for monitoring changes in soil organic matter content due to changes in soil management practices.

Soil Physical Quality and Soybean Yield as Affected by Chiseling and Subsoiling of a No-Till Soil

ABSTRACT The concept of soil physical quality (SPQ) is currently under discussion, and an agreement about which soil physical properties should be included in the SPQ characterization has not been reached. The objectives of this study were to evaluate the ability of SPQ indicators based on static and dynamic soil properties to assess the effects of two loosening treatments (chisel plowing to 0.20 m [ChT] and subsoiling to 0.35 m [DL]) on a soil under NT and to compare the performance of static- and dynamic-based SPQ indicators to define soil proper soil conditions for soybean yield. Soil sampling and field determinations were carried out after crop harvest. Soil water retention curve was determined using a tension table, and field infiltration was measured using a tension disc infiltrometer. Most dynamic SPQ indicators (field saturated hydraulic conductivity, K0, effective macroporosity, εma, total connectivity and macroporosity indexes [CwTP and Cwmac]) were affected by the studied treatments, and were greater for DL compared to NT and ChT (K0 values were 2.17, 2.55, and 4.37 cm h-1 for NT, ChT, and DL, respectively). However, static SPQ indicators (calculated from the water retention curve) were not capable of distinguishing effects among treatments. Crop yield was significantly lower for the DL treatment (NT: 2,400 kg ha-1; ChT: 2,358 kg ha-1; and DL: 2,105 kg ha1), in agreement with significantly higher values of the dynamic SPQ indicators, K0, εma, CwTP, and Cwmac, in this treatment. The results support the idea that SPQ indicators based on static properties are not capable of distinguishing tillage effects and predicting crop yield, whereas dynamic SPQ indicators are useful for distinguishing tillage effects and can explain differences in crop yield when used together with information on weather conditions. However, future studies, monitoring years with different weather conditions, would be useful for increasing knowledge on this topic.

Tomato yield and potassium concentrations in soil and in plant petioles as affected by potassium fertirrigation

Tomato (Lycopersicon esculentum Mill.) cv. Santa Clara was grown on a silt clay soil with 46 mg dm-3 Mehlich 1 extractable K, to evaluate the effects of trickle-applied K rates on fruit yield and to establish K critical concentrations in soil and in plant petioles. Six potassium rates (0, 48, 119, 189, 259 and 400 kg ha-1 K) were applied in a randomized complete block design with four replications. Soil and plant K critical levels were determined at two plant growth stages (at the beginning of the second and fourth cluster flowering). Total, marketable and weighted yields increased with K rates, reaching their maximum of 86.4, 73.4, and 54.9 ton ha-1 at 198, 194, and 125 kg ha-1 K , respectively. At the first soil sampling date K critical concentrations in the soil associated with K rates for maximum marketable and weighted yields were 92 and 68 mg dm-3, respectively. Potassium critical concentrations in the dry matter of the petioles sampled by the beginning of the second and fourth cluster flowering time, associated with maximum weighted yield, were 10.30 and 7.30 dag kg-1, respectively.

Soil compaction due to forest harvest operations

The objective of this work was to determine, through the use of the bearing capacity model, the traffic effects of the forest harvest operations on the preconsolidation pressure (sigmap), during one cycle of the eucalyptus plantation. The work was conducted using undisturbed soil samples, collected at the surface of the A horizon and in the top of the B horizon of an Udult (PA), Aquox (FX) and Udox (LA) soils. The undisturbed soil samples were used in the uniaxial compression tests. The soil sampling was done before and after the harvest operations. The operations performed with the Forwarder caused greater soil compaction than the ones done with the Feller Büncher and Harvester. The percentage of soil samples, in the region with additional soil compaction, indicated that the Udult was the soil class more susceptible to soil compaction, followed by the Aquox and Udox. Despite Udult is the more susceptible to soil compaction, the regeneration of the soil structure in this soil class was more efficient than in Aquox. The percentage of soil samples with sigmap values in the region with additional soil compaction in 1996, 1998 and 2004, after harvest operations, indicated a sustainable forest exploration in this period.

Correlation of physical and chemical attributes of soil with sugarcane yield

The objective of this work was to evaluate the correlation between sugarcane yield and some physical and chemical attributes of soil. For this, a 42‑ha test area in Araras, SP, Brazil, was used. Soil properties were determined from samples collected at the beginning of the 2003/2004 harvest season, using a regular 100x100 m grid. Yield assessment was done with a yield monitor (Simprocana). Correlation analyses were performed between sugarcane yield and the following soil properties: pH, pH CaCl2, N, C, cone index, clay content, soil organic matter, P, K, Ca, Mg, H+AL, cation exchange capacity, and base saturation. Correlation coefficients were respectively ‑0.05, ‑0.29, 0.33, 0.41, ‑0.27, 0.22, 0.44, ‑0.24, trace, ‑0.06, 0.01, 0.32, 0.14, and 0.04. Correlations of chemical and physical attributes of soil with sugarcane yield are weak, and, per se, they are not able to explain sugarcane yield variation, which suggests that other variables, besides soil attributes, should be analysed.

Effect of period of sugarcane cultivation on the abundance and distribution of weed seeds in the soil profile

An experiment was laid down in a screen house to determine the distribution of weed seeds at different soil depths and periods of cultivation of sugarcane in Ilorin, Nigeria. Soil samples from different depth levels (0-10 cm, 11-20 cm and 21-30 cm) were collected after harvesting of canes from three different land use fields (continuous sugarcane cultivation for > 20 years, continuous sugarcane cultivation for < 10 years after long fallow period and continuous sugarcane cultivation for < 5 years after long fallow period) in November, 2012. One kilogram of the sieved composite soil samples was arranged in the screen house and watered at alternate days. Germinating weed seedlings were identified, counted and then pulled out for the period of 8 months. Land use and soil depth had a highly significant (p £ 0.05) effect on the total number of weeds that emerged from the soil samples. The 010 cm of the soil depth had the highest weed seedlings that emerged. There was an equal weed seed distribution at the 11-20 cm and 21-30 cm depths of the soil. Sugarcane fields which have been continuously cultivated for a long period of time with highly disturbing soil tillage practices tend to have larger seed banks in deeper soil layers (11-20 cm and 21-30 cm) while recently opened fields had significantly larger seed banks at the 0-10 cm soil sampling depth.

Evolution of Ryegrass Seed Banks Depending on Soil Tillage and Crops

The seed bank is characterized by the amount of seeds and other viable reproductive structures in the soil and it is changed by the input and output of seeds, being classified by its permanence in the soil as transient or permanent. The tillage and crops used decisively influence this dynamic and more disturbed areas tend to have richer seed banks. The purpose of this study was to test different soil tillage and crop systems, aiming to reduce or eliminate the ryegrass in the area. The experiment was conducted from 2010 to 2012. In the first year, the effect of chemical tillage was assessed, compared to the area without tillage. From the second year on, in the area that received chemical tillage, the second experiment was installed, where it was assessed the effect of soil tillage and crop rotation in the ryegrass seed yield. The soil tillage treatment was chisel plow and non-chisel plow. The crop rotation was: fallow/soybean; wheat/soybean; black oat/maize. The samples of soil were taken three times a year and split in 0-5, 5-10, 10-15 and 15-20 cm. After sampling, the seeds were separated from the soil and sterilized. Afterwards, germination and tetrazolium test were conducted. In the same plots used for soil sampling, the emergence flow of ryegrass was assessed in the winter 2011 and 2012. In the first year it was observed that chemical tillage had considerably reduced the amount of ryegrass in the soil. The crop rotations used were more effective than soil tillage in reducing the seed banks in the soil. The rotation oat/maize and wheat/soybean, in only two years, practically zeroed the ryegrass seed banks in the area.

Incorporating Legacy Soil pH Databases into Digital Soil Maps

Soil data and reliable soil maps are imperative for environmental management. conservation and policy. Data from historical point surveys, e.g. experiment site data and farmers fields can serve this purpose. However, legacy soil information is not necessarily collected for spatial analysis and mapping such that the data may not have immediately useful geo-references. Methods are required to utilise these historical soil databases so that we can produce quantitative maps of soil propel-ties to assess spatial and temporal trends but also to assess where future sampling is required. This paper discusses two such databases: the Representative Soil Sampling Scheme which has monitored the agricultural soil in England and Wales from 1969 to 2003 (between 400 and 900 bulked soil samples were taken annually from different agricultural fields); and the former State Chemistry Laboratory, Victoria, Australia where between 1973 and 1994 approximately 80,000 soil samples were submitted for analysis by farmers. Previous statistical analyses have been performed using administrative regions (with sharp boundaries) for both databases, which are largely unrelated to natural features. For a more detailed spatial analysis that call be linked to climate and terrain attributes, gradual variation of these soil properties should be described. Geostatistical techniques such as ordinary kriging are suited to this. This paper describes the format of the databases and initial approaches as to how they can be used for digital soil mapping. For this paper we have selected soil pH to illustrate the analyses for both databases.

The spatial prediction of soil mineral N and potentially available N using elevation

The precision farmer wants to manage the variation in soil nutrient status continuously, which requires reliable predictions at places between sampling sites. Ordinary kriging can be used for prediction if the data are spatially dependent and there is a suitable variogram model. However, even if data are spatially correlated, there are often few soil sampling sites in relation to the area to be managed. If intensive ancillary data are available and these are coregionalized with the sparse soil data, they could be used to increase the accuracy of predictions of the soil properties by methods such as cokriging, kriging with external drift and regression kriging. This paper compares the accuracy of predictions of the plant available N properties (mineral N and potentially available N) for two arable fields in Bedfordshire, United Kingdom, from ordinary kriging, cokriging, kriging with external drift and regression kriging. For the last three, intensive elevation data were used with the soil data. The mean squared errors of prediction from these methods of kriging were determined at validation sites where the values were known. Kriging with external drift resulted in the smallest mean squared error for two of the three properties examined, and cokriging for the other. The results suggest that the use of intensive ancillary data can increase the accuracy of predictions of soil properties in arable fields provided that the variables are related spatially. (c) 2005 Elsevier B.V. All rights reserved.

Co-kriging when the soil and ancillary data are not co-located

Data such as digitized aerial photographs, electrical conductivity and yield are intensive and relatively inexpensive to obtain compared with collecting soil data by sampling. If such ancillary data are co-regionalized with the soil data they should be suitable for co-kriging. The latter requires that information for both variables is co-located at several locations; this is rarely so for soil and ancillary data. To solve this problem, we have derived values for the ancillary variable at the soil sampling locations by averaging the values within a radius of 15 m, taking the nearest-neighbour value, kriging over 5 m blocks, and punctual kriging. The cross-variograms from these data with clay content and also the pseudo cross-variogram were used to co-krige to validation points and the root mean squared errors (RMSEs) were calculated. In general, the data averaged within 15m and the punctually kriged values resulted in more accurate predictions.