Ground-Sensor Soil Reflectance as Related to Soil Properties and Crop Response in a Cotton Field

2005 ◽  
Vol 6 (4) ◽  
pp. 399-411 ◽  
Author(s):  
S. Stamatiadis ◽  
C. Christofides ◽  
C. Tsadilas ◽  
V. Samaras ◽  
J. S. Schepers ◽  
...  
Keyword(s):  
Soil Properties ◽  
Cotton Field ◽  
Crop Response ◽  
Soil Reflectance

Consequential rice crop response to resultant soil properties in a toposequence in eastern coastal plain of Odisha, India

2021 ◽  
Author(s):  
Ramasamy Srinivasan ◽  
Dulal Chandra Nayak ◽  
Rajendran Gobinath ◽  
Subbanna Naveen Kumar ◽  
D. V. K. Nageswara Rao ◽  
...  
Keyword(s):  
Soil Properties ◽  
Coastal Plain ◽  
Rice Crop ◽  
Crop Response

scholarly journals Separation of soil and canopy reflectance signatures of Mid German agricultural soils

2011 ◽  
Vol 51 (No, 7) ◽  
pp. 296-303 ◽  
Author(s):  
T. Behrens ◽  
K. Gregor ◽  
W. Diepenbrock
Keyword(s):  
Remote Sensing ◽  
Soil Properties ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Vegetation Index ◽  
Near Infrared ◽  
Field Experiments ◽  
Agricultural Soils ◽  
Soil Reflectance

Remote sensing can provide visual indications of crop growth during production season. In past, spectral optical estimations were well performed in the ability to be correlated with crop and soil properties but were not consistent within the whole production season. To better quantify vegetation properties gathered via remote sensing, models of soil reflectance under changing moisture conditions are needed. Signatures of reflected radiation were acquired for several Mid German agricultural soils in laboratory and field experiments. Results were evaluated at near-infrared spectral region at the wavelength of 850 nm. The selected soils represented different soil colors and brightness values reflecting a broad range of soil properties. At the wavelength of 850 nm soil reflectance ranged between 10% (black peat) and 74% (white quartz sand). The reflectance of topsoils varied from 21% to 32%. An interrelation was found between soil brightness rating values and spectral optical reflectance values in form of a linear regression. Increases of soil water content from 0% to 25% decreased signatures of soil reflectance at 850 nm of two different soil types about 40%. The interrelation of soil reflectance and soil moisture revealed a non-linear exponential function. Using knowledge of the individual signature of soil reflectance as well as the soil water content at the measurement, soil reflectance could be predicted. As a result, a clear separation is established between soil reflectance and reflectance of the vegetation cover if the vegetation index is known.

Influence of tillage and liquid swine manure on productivity of a soybean-barley rotation and some properties of a fine sandy loam in Prince Edward Island

2006 ◽  
Vol 86 (4) ◽  
pp. 741-748 ◽  
Author(s):  
M R Carter ◽  
A J Campbell
Keyword(s):  
Soil Properties ◽  
Prince Edward Island ◽  
Sandy Loam ◽  
Soil Depth ◽  
Swine Manure ◽  
Residual Effect ◽  
Crop Response ◽  
Fine Sandy Loam ◽  
Liquid Swine Manure ◽  
Second Year

Interactions between tillage management for manure incorporation and rate of manure application may influence crop productivity and soil properties. This study was conducted to evaluate the effect of liquid swine (Sus scrofa L.) manure (LSM) applied at three N rates (40, 80, 160 kg ha-1), compared with mineral N fertilizer, in a 2-yr barley (Hordeum vulgare L.)-soybean (Glycine max L. Merr.) rotation, incorporated by two tillage methods (chisel plough and disc), on crop yield and quality and some soil properties, especially C parameters. The LSM was applied every second year in the spring, prior to barley seeding. The study was conducted over a 5-yr period on a Charlottetown fine sandy loam (Orthic Humo-Ferric Podzol) in Prince Edward Island. The experimental design was a split-plot with four replicates. Soil samples (0–60 cm) were obtained at the termination of the study to determine residual effects of the LSM on soil properties. The two methods of LSM incorporation had no differential effect on crop response. Generally, increasing the application rate of LSM increased the barley yield, but had no effect on grain N concentration. A residual effect on crop grain yield for the high rate of LSM was evident in the soybean year. Crop response to LSM was similar to that of mineral fertilizer. Application operations for LSM had no adverse effect on soil strength or soil bulk density. Soil properties (microbial biomass C, carbohydrates, water-stable aggregates) were not greatly influenced by LSM application, however, increases in particulate C (POM-C) were evident for the high LSM rate at the 10- to 30-cm soil depth. The study showed that for fine sandy loams in Prince Edward Island low to medium rates of LSM applied every second year could serve as a source of N for barley in barley-soybean rotations. Key words: Barley, soybean, liquid swine manure, fine sandy loam, soil properties, tillage incorporation, eastern Canada

Effects of time of urea application on combine-sown Calrose rice in south-east Australia. I. Crop response and N uptake

1987 ◽  
Vol 38 (1) ◽  
pp. 101 ◽  
Author(s):  
E Humphreys ◽  
WA Muirhead ◽  
FM Melhuish ◽  
RJG White
Keyword(s):  
Grain Yield ◽  
Soil Properties ◽  
Dry Matter ◽  
Clay Soil ◽  
N Uptake ◽  
First Flush ◽  
Crop Response ◽  
Plant N Uptake ◽  
Matter Production ◽  
Highly Correlated

Urea (50 kg N ha-1) was applied at one of four times (before the first flush, before permanent flood, after permanent flood and at panicle initiation) to Calrose rice growing on an alkaline grey clay soil. Plant N uptake was highly correlated with dry matter production (r2=0.90) and with grain yield (r2 = 0.95). Efficiency of fertilisation and grain yield were highest when urea was applied either before permanent flood (56 kg grain (kg N) -1, 6.4 t ha-1) or at panicle initiation (47 kg grain (kg N)-1, 6.0 t ha-1), and these efficiencies are among the highest that have been recorded in rice. Significantly lower yields were obtained when the fertiliser was applied at sowing or after permanent flood, largely due to lower panicle densities. Fertilisation at sowing did not produce significantly more grain than the control, despite an early vegetative response. This is in contrast with previous findings on a more fertile acid red-brown earth, and suggests that soil properties may be an important consideration in predicting optimum fertilisation strategies.

scholarly journals Effect of cotton residues incorporation on soil properties, organic nitrogen fractions, and nitrogen-mineralizing enzyme activity under long-term continuous cotton cropping

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11053
Author(s):  
Fangxia Ma ◽  
Yiyun Wang ◽  
Peng Yan ◽  
Fei Wei ◽  
Zhiping Duan ◽  
...  
Keyword(s):  
Enzyme Activity ◽  
Soil Properties ◽  
Organic Nitrogen ◽  
Organic N ◽  
Cotton Field ◽  
Continuous Cropping ◽  
Soil Organic C ◽  
Organic C ◽  
C And N

The objective of this experiment was to study the effect of cotton residues incorporation on soil properties, soil organic nitrogen (N) fractions, and N-mineralizing enzyme (protease, and urease) activity in the 0–40 cm soil layer in the long-term continuous cotton field. In this experiment, seven treatments, including cotton residues incorporation for 5, 10, 15 and 20 years (marked as 5a, 10a, 15a, and 20a) and continuous cropping for 5, 10 and 20 years (marked as CK5, CK10 and CK20) were conducted. The results showed that the soil organic carbon (C) and N increased gradually with the increase in the duration of continuous cropping with cotton residues incorporation. Compared with CK20, the 20a treatments reduced the content of amino acid N (AAN), ammonium N (AN), amino sugar N (ASN), hydrolysable unidentified N (HUN), and acid insoluble N (AIN) significantly by 48.6, 32.2, 96.9, 48.3, and 38.7%, respectively (p < 0.05). The activity of protease and urease in 20a treatments significantly increased by 53.4 and 53.1% respectively as compared to CK20 (p < 0.05). Soil organic C and N-mineralizing enzyme activity decreased with the increase in cropping duration in the absence of cotton residues incorporation, while the organic N increased slightly. In conclusion, cotton residues returning can increase the storage of soil organic C and N in long-term continuous cropping cotton field, and improve the soil quality and soil fertility of continuous cropping cotton field.

scholarly journals Effect of Open Soil Surface Patterns on Soil Detectability Based on Optical Remote Sensing Data

Proceedings ◽  
2018 ◽  
Vol 2 (7) ◽  
pp. 357 ◽  
Author(s):  
Elena Prudnikova ◽  
Igor Savin
Keyword(s):  
Remote Sensing ◽  
Soil Properties ◽  
Remote Sensing Data ◽  
Optical Remote Sensing ◽  
Spectral Variation ◽  
Least Squares Regression ◽  
Arable Soils ◽  
Sensing Data ◽  
Surface Patterns ◽  
Soil Reflectance

Arable soils are subjected to the altering influence of agricultural and natural processes determining surface feedback patterns therefore affecting their ability to reflect light. However, remote soil mapping and monitoring usually ignore information on surface state at the time of data acquisition. Conducted research demonstrates the contribution of surface feedback dynamics to soil reflectance and its relationship with soil properties. Analysis of variance showed that the destruction surface patterns accounts for 71% of spectral variation. The effect of surface smoothing on the relationships between soil reflectance and its properties varies. In the case of organic matter and medium and coarse sand particles, correlation decreases with the removement of surface structure. For particles of fine sand and coarse silt, grinding changes spectral areas of high correlation. Partial least squares regression models also demonstrated variations in complexity, R2cv and RMSEPcv. Field dynamics of surface feedback patterns of arable soils causes 22–46% of soil spectral variations depending on the growing season and soil type. The directions and areas of spectral changes seem to be soil-specific. Therefore, surface feedback patterns should be considered when modelling soil properties on the basis of optical remote sensing data to ensure reliable and reproducible results.

scholarly journals Dynamics of agricultural use differentially affect soil properties and crop response in East African wetlands

2013 ◽  
Vol 21 (6) ◽  
pp. 417-431 ◽  
Author(s):  
Hellen Kamiri ◽  
Christine Kreye ◽  
Mathias Becker
Keyword(s):  
Soil Properties ◽  
Crop Response ◽  
East African ◽  
Agricultural Use

SOIL REFLECTANCE SENSING FOR DETERMINING SOIL PROPERTIES IN PRECISION AGRICULTURE

2001 ◽  
Vol 44 (6) ◽  
Author(s):  
J. A. Thomasson ◽  
R. Sui ◽  
M. S. Cox ◽  
A. Al–Rajehy
Keyword(s):  
Soil Properties ◽  
Precision Agriculture ◽  
Soil Reflectance

Field-scale N fertilizer recommendations: The spatial covariance problem

2002 ◽  
Vol 82 (1) ◽  
pp. 59-64 ◽  
Author(s):  
Bing Cheng Si ◽  
R. Gary Kachanoski
Keyword(s):  
Analytical Solution ◽  
Spatial Variability ◽  
Soil Properties ◽  
N Fertilizer ◽  
Yield Response ◽  
Soil Test ◽  
Soil N ◽  
Crop Response ◽  
Field Scale ◽  
Available Water

Theory is needed to estimate field-scale crop response and calibration relationships (soil test versus recommended fertilize r rate) from local scale measurements, in fields with spatially variable soil properties. The objective of this study is to present a theoretical stochastic framework for examining the influence of the spatial variability of soil properties, and covariance between soil properties, on field-scale crop response to fertilizer. An analytical solution of the general stochastic scaling equation is given for the specific case of wheat grain yield response to applied N fertilizer with variable soil-N test and available water in Saskatchewan, Canada. The analytical solution indicates spatial variance of soil properties within fields influences field average yield response to applied fertilizer. The field-scale maximum economic rate of fertilizer N (MERN), depends not only on the average soil properties, but also on (1) the amount of variability of soil properties in the field, and (2) the correlation between the spatial patterns of soil properties (e.g., soil test and available water). For the specific soil examined, positive spatial correlation between soil-N test and available water significantly increases MERN, for the same average soil test and available water. Negative correlation decreases MERN. Key Words: Fertilizer recommendation, soil test, spatial variability, crop response, soil water

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