scholarly journals Soil Fertility Appraisal for Pea Growing Regions of Himachal Pradesh using GPS and GIS Techniques

2020 ◽  
Author(s):  
Nishant Thakur ◽  
Rakesh Sharma ◽  
Anil Kumar ◽  
Kunal Sood
Keyword(s):  
Electrical Conductivity ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Fertility ◽  
Soil Properties ◽  
Soil Samples ◽  
Available N ◽  
Available Nutrients ◽  
Fertility Status ◽  
Cu And Zn

Background: Overexploitation of productive lands creates serious problem of lowering the fertility status of soil and it leads to deterioration of soil. The deficiency of nutrients directly affects on the growth of crops and crop response become poor. Pea crop, like other plants, need different nutrients in varying quantities to achieve optimum growth and productivity. Soil fertility and its productivity are mainly affected by soil properties and nutrient status. Hence, it is necessary to assess the fertility status of soil with the consideration of available nutrients in soils and to recommend the specific nutrients for the proper management of soil. Methods: In this field-laboratory investigation during 2017-2019, about 135 geo-referenced soil samples were collected from 49 pea growing locations/ villages of Gohar and Sundernagar blocks of Mandi district. The collected (0-15 cm) soil samples were analyzed for different soil properties such as pH, electrical conductivity, soil organic carbon and available N, P, K, Ca, Mg, S, Fe, Mn, Cu and Zn content. Different thematic maps were prepared using Arc-GIS software version 10.2.1.Result: The investigations revealed that the soils were acidic to neutral in soil reaction and are in safe limits of electrical conductivity as the values were less than 0.8 dS m-1. Soil organic carbon status was found to be medium to high in surface layer. About 94.8 and 22.2% soil samples were recorded deficient in available N and Zn, whereas K, Cu and Zn were moderate in 53.3, 28.1 and 55.6% samples, respectively. On the basis of coefficient of variation, the soil pH and exchangeable Ca are least variable, whereas, available nutrients like N, Ca, Mg, Fe and Mn are moderately variable. However, electrical conductivity, OC, available P, K, S, Cu and Zn are highly variable in the samples under investigation. This information will also help to adopt effective strategy on fertilizer use and cropping pattern.

scholarly journals Spatial variability assessment in Central Farm Soils of Horticultural College and Research Institute, Periyakulam, Tamil Nadu using GIS techniques

2021 ◽  
Vol 108 (september) ◽  
Author(s):  
Sellamuthu K M ◽  
◽  
Kumaraperumal R ◽  
Malathi P ◽  
◽  
...  
Keyword(s):  
Organic Carbon ◽  
Spatial Variability ◽  
Soil Fertility ◽  
Tamil Nadu ◽  
Soil Samples ◽  
High Status ◽  
Available N ◽  
Fertility Status ◽  
Nutrient Index ◽  
Research Institute

A total number of 201 surface soil samples were collected encompassing the fields of Central Farm of Horticultural College and Research Institute, Periyakulam, Tamil Nadu. The GPS data (Latitude ºN and Longitude ºE) were recorded for each sampling site by using GPS-Garmin eTrex Vista HCX model. Field maps were collected and field number wise digitization was done. Soil samples were processed and anlaysed for soil physic-chemical and fertility parameters. Results indicated that soil samples were neutral to alkaline in reaction, non saline, and slightly calcareous to non calcareous in nature. Soil fertility groupings under percent category indicated that the soils were medium in soil organic carbon, low in available nitrogen, medium to high in available phosphorus, medium to high in available potassium, and low in available sulphur. With respect to DTPA extractable micronutrients, Fe, Zn, Mn and Cu were found to dominate by low to medium, low, high, medium to high categories, respectively. HWS-Boron was also recorded under the high category. The nutrient index values of the samples indicated a high status for organic carbon, available P and K, while medium for available N and adequate for available sulphur. With respect to micro nutrients, nutrient index values indicated that adequate for DTPA-Zn and very high for DTPA-Fe, Mn, Cu, and HWS-B. Thematic maps generated on the individual parameters depicted the spatial variability of parameters in the Central Farm of Horticultural College and Research Institute, Periyakulam. In the identified areas of poor fertility status, nutrient deficiency has to be eliminated by the application of organic and /or inorganic sources to maintain sustainable soil fertility status. Soil test-based fertilizer recommendations and micronutrients are to be followed to mitigate nutrient deficiencies and achieve sustained crop production and soil fertility.

scholarly journals Effect of Integrated Nutrient Management on Performance of Chickpea (Cicer arietinum L.) and Soil Properties

2021 ◽  
pp. 156-162
Author(s):  
Sumit Mukati ◽  
Y. M. Kool ◽  
Deepak Thakur ◽  
Deepak Singune
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Properties ◽  
Management Practices ◽  
Nutrient Management ◽  
Management Practice ◽  
Block Design ◽  
Integrated Nutrient Management ◽  
Available Nutrients ◽  
Randomized Block Design

Present field experiment was conducted at farmer’s field in Ringondiya village, Madhya Pradesh during rabi season 2018-19 to study the effect of integrated nutrient management practices on performance of chickpea, basic soil properties and nutrient availability. The performance of chickpea (cv. JG-322) was evaluated under seven treatments viz., T1-Control, T2-100% N:P:K (20:50:20), T3-50% N:P:K + FYM @5 t ha-1, T4-50% N:P:K + vermicomposting @2 t ha-1, T5-50% N:P:K + PSB @4 kg ha-1, T6-50% N:P:K + FYM @5 t ha-1 + PSB @4 kg ha-1 and T7-50% N:P:K + vermicomposting @2 t ha-1 +PSB @4 kg ha-1 replicated thrice in a randomized block design. The grain yield, straw yield and harvest index of chickpea were determined at harvest. Similarly, the soil pH, electrical conductivity, soil organic carbon and soil available nutrients (N, P and K) were also determined in post harvest soil samples. The results revealed that the integrated nutrient management practice significantly improved the performance of chickpea. The soil organic carbon and available nutrients were also found increased under INM practices.

scholarly journals Soil fertility evaluation of rice soils of Lumbajong block of Karbi Anglong district under hill zone of Assam through nutrient indexing

2020 ◽  
Vol 15 (2) ◽  
pp. 81-85
Author(s):  
Nilim Kalita ◽  
Subal Maibangsa
Keyword(s):  
Organic Carbon ◽  
Soil Fertility ◽  
Available P ◽  
Chemical Fertilizers ◽  
Available Nitrogen ◽  
Rice Soils ◽  
Available N ◽  
Fertility Status ◽  
Nutrient Index ◽  
Soil Fertility Status

The Lumbajong block of Karbi Anglong district of Assam is characterized by undulating topography comprising of hillocks and lowland paddy fields. Cultivation of rice in traditional ways for years without adequate and balanced use of chemical fertilizers and with little or no use of organic manure have caused severe fertility deterioration resulting in stagnating or even declining productivity of the paddy field soils. Spatial distributions for organic carbon, available N, available P and available K were examined in the soil samples of selected rice fields in 102 different locations covering six villages in the block to evaluate the fertility status of the block. The study revealed that there is much variation in soil fertility status of soils developed on various land forms in the area as the soils were having low to high in organic carbon (0.42 to1.12 %), low to medium in available nitrogen (175.62 to 376 kg/ha) content; low in available P (3.86 to 28.29 kg/ha) and low to high in available K (71.68 – 439.04 kg/ha) contents. The soils of Lumbajong block were characterized as medium-medium-low-medium (MMLM) category based on the nutrient index calculated with respect to organic carbon, available N, available P and available K.

scholarly journals Assessment of Soil Fertility Status of Kanwara Minor Lift Canal Command Area in Banda District of Bundelkhand using Nutrient Index Values

2021 ◽  
pp. 98-104
Author(s):  
Chandrakant Chaubey ◽  
A. K. Chaubey ◽  
Amit Mishra ◽  
Narendra Singh ◽  
Gaurav Shukla ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Fertility ◽  
Available P ◽  
Soil Parameters ◽  
Command Area ◽  
Available N ◽  
Fertility Status ◽  
Nutrient Index ◽  
Canal Command ◽  
Canal Command Area

A study was conducted to assess the fertility status of Kanwara minor lift canal command area using Nutrient Index values of different soil parameters under study in 2019-20. A systematic set of two hundred and eleven georeferenced soil samples were collected and analysed following the standard sampling and analytical procedure. The analysed values of different parameters were categorized in low, medium and high and further used in determination of the nutrient index. NI value of soil organic carbon was 1.16, 1.00 for available N, 1.47 for available P and 2.55 for available K respectively. Regarding the fertility class based on Nutrient Index values it was deficient in organic carbon, available N and available P while, sufficient in soil available K. This requires immediate attention towards the management of nutrients to restore the soil fertility and sustain crop productivity.

scholarly journals VIS-NIR REFLECTANCE SPECTROSCOPY FOR ASSESSMENT OF SOIL ORGANIC CARBON IN A RICE-WHEAT FIELD OF LUDHIANA DISTRICT OF PUNJAB

2019 ◽  
Vol XLII-3/W6 ◽  
pp. 417-422
Author(s):  
B. P. Mondal ◽  
B. S. Sekhon ◽  
R. N. Sahoo ◽  
P. Paul
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Fertility ◽  
Soil Properties ◽  
Soil Health ◽  
Reflectance Spectroscopy ◽  
Spectral Model ◽  
Validation Dataset ◽  
Wheat Field ◽  
Nir Reflectance Spectroscopy

<p><strong>Abstract.</strong> Soil organic carbon (SOC) is a crucial indicator of soil fertility, maintaining soil health and sustaining the productivity of agro-ecosystem. Rapid, reliable and cost effective assessment of soil properties specially for SOC is important for monitoring soil fertility status along with soil health. Conventional chemical analysis of any soil property is hazardous, tedious and time consuming. So, the visible near infrared (VIS-NIR) reflectance spectroscopy can provide an effective alternative technique for rapid and ecofriendly measurement of soil properties. In view of this, a key soil fertility parameter SOC was examined through diffuse reflectance spectroscopy. Georeferenced surface soil samples (0&amp;ndash;15&amp;thinsp;cm) were collected from a rice-wheat field of the study area for both chemical and spectral analysis. A viable statistical technique namely partial least square regression (PLSR) technique were used to correlate the measured properties with soil reflectance spectra and for developing spectral model. The predictive performance of newly developed spectral model was evaluated through different reliable indices like root mean square of error of prediction (RMSEP), coefficient of determination (R<sup>2</sup>) and ratio of performance deviation (RPD). The result showed that the R<sup>2</sup> value for SOC is 0.44, RMSEP is 0.07 and the RPD value is 1.57 in the validation dataset. The RPD value indicating that SOC can be reliably predicted using the hyperspectral model or reflectance analysis. So, this hyperspectral modeling technique can be successfully employed for monitoring soil health as well as for sustainable agriculture.</p>

scholarly journals GIS-based Fertility Assessment and Mapping for Agricultural Research Station, Tandur, Telangana, India

2021 ◽  
pp. 289-296
Author(s):  
Kasthuri Rajamani ◽  
C. Sudhakar ◽  
N. Hari ◽  
M. Venkata Ramana
Keyword(s):  
Organic Carbon ◽  
Soil Fertility ◽  
Carbon Content ◽  
Agricultural Research ◽  
Soil Samples ◽  
Research Station ◽  
Organic Carbon Content ◽  
Fertility Status ◽  
Agricultural Research Station ◽  
Soil Fertility Status

This study was conducted to determine the soil fertility status of the Agricultural Research Station, Tandur of Professor Jayashankar Telangana State Agricultural University (PJTSAU), Vikarabad District, Telangana. To identify the soil sampling points, GPS device was used and collected total of 60 soil samples on grid-based method at a depth of 0–15 cm. The collected samples were analyzed for pH, EC, OC, N, P2O5, K2O, Zn, Cu, Fe and Mn status by following standard methods in the laboratory of Regional Agricultural Research Station, Palem, PJTSAU, Nagarkurnool District of Telangana, and Arc-GIS software was used further to prepare soil fertility maps. Around 37.5% of samples fall in neutral pH, whereas 62.5% samples were found as moderately alkaline reactions and entire farm soils were non-saline. Among the analyzed soil samples, 37.29% samples were in low organic carbon content, and rest of the samples i.e.,62.71% have medium organic carbon content and total samples were low in available N content (< 280 kg ha-1). The analyzed farm samples were medium to high in available phosphorus and potassium (28.67 & 71.33 % of P2O5 and 16.96 & 83.04 % of K2O respectively) content. In contrast, the micronutrients (Zn, Cu, Fe & Mn) exceeded their sufficiency level and suggested for amelioration measures to enhance research efficacy in the farm and to build future research strategies based on the determined soil fertility status.

Mapping soil organic carbon based on simulated EnMAP images and the LUCAS soil spectral library

2020 ◽  
Author(s):  
Kathrin J. Ward ◽  
Maximilian Brell ◽  
Daniel Spengler ◽  
Fabio Castaldi ◽  
Carsten Neumann ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Properties ◽  
Image Data ◽  
Soil Samples ◽  
Test Area ◽  
Model Accuracy ◽  
Wet Chemistry ◽  
Spectral Libraries

&lt;p&gt;The degradation of European soils is a cause for concern. Examples are the reduction of carbon content and soil fertility. The European Commission therefore recommends further research on how to better monitor soils and their changes over time and space. Digital soil mapping (DSM) is already an established method for the use of hyperspectral information from soil samples for quantifying soil properties under laboratory conditions based on soil spectral libraries. At the remote sensing level, imaging spectroscopy has already achieved good results for the prediction of soil properties on a local scale. Major advantages of this method are that topsoil maps can be updated more frequently, spatially more accurately and with less costs.&lt;/p&gt;&lt;p&gt;In this study we bring together pedometric and remote sensing approaches to achieve the development of soil spectral models applicable to upcoming global hyperspectral imagery, combining DSM methods and data with Earth Observation expertise. In a first step at laboratory level, we used the EU-wide topsoil database LUCAS. We investigated whether using solely spectral data (without any covariates) and selected classification algorithms combined with PLSR could allow and improve the quantification of soil organic carbon (SOC) content. The best results were obtained for the local PLSR approach with RMSE=5.16 g kg-1, RPD=1.74 and R&amp;#178;=0.67. In addition, the local PLSR approach was tested with LUCAS spectral data resampled to EnMAP satellite spectral resolution, resulting in a very similar SOC prediction model accuracy.&lt;/p&gt;&lt;p&gt;In the next step, the local PLSR approach was applied to airborne HySpex image data and simulated satellite EnMAP data from a test area in north-eastern Germany where local soil data are available for model validation. This area is associated with one LUCAS point. A direct application of the laboratory-based SOC model to the spectra of the airborne image was not possible due to higher variability in the image data caused by different environmental conditions (solar illumination, mixed soil-vegetation pixels, surface state -roughness, wetness-) and sensor performances different from the laboratory data resulting in an overall lower signal-to-noise ratio in the airborne image. Therefore, after reducing the effect of soil moisture, green vegetation cover, residues coverage, we used a two-step approach where (i) wet chemistry SOC analyses for a set of soil samples from the test area were replaced by the local PLSR approach using the LUCAS database. Then (ii) an airborne model was calibrated using the SOC content from (i) and the corresponding image spectra to calibrate an airborne PLSR. Preliminary results show a good airborne model accuracy for HySpex imagery with RMSE=3.33 g kg-1, RPD=1.59, R&amp;#178;=0.63 and slightly lower but still good accuracy for simulated EnMAP imagery with RMSE=3.72 g kg-1, RPD=1.45, R&amp;#178;=0.55. Both models were then applied to the images to produce SOC maps for bare soils and validated with existing data and previous SOC mapping works in the area based on local datasets. This approach demonstrates the possibility to replace wet chemistry by the local PLSR approach based on large scale soil spectral libraries for SOC mapping.&lt;/p&gt;

scholarly journals From the Ground Up: Prairies on Reclaimed Mine Land—Impacts on Soil and Vegetation

Land ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 455
Author(s):  
Rebecca M. Swab ◽  
Nicola Lorenz ◽  
Nathan R. Lee ◽  
Steven W. Culman ◽  
Richard P. Dick
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Properties ◽  
Plant Community ◽  
Prairie Restoration ◽  
Native Plant ◽  
Soil Microbial ◽  
Prairie Restorations ◽  
Mine Lands ◽  
The Impact

After strip mining, soils typically suffer from compaction, low nutrient availability, loss of soil organic carbon, and a compromised soil microbial community. Prairie restorations can improve ecosystem services on former agricultural lands, but prairie restorations on mine lands are relatively under-studied. This study investigated the impact of prairie restoration on mine lands, focusing on the plant community and soil properties. In southeast Ohio, 305 ha within a ~2000 ha area of former mine land was converted to native prairie through herbicide and planting between 1999–2016. Soil and vegetation sampling occurred from 2016–2018. Plant community composition shifted with prairie age, with highest native cover in the oldest prairie areas. Prairie plants were more abundant in older prairies. The oldest prairies had significantly more soil fungal biomass and higher soil microbial biomass. However, many soil properties (e.g., soil nutrients, β-glucosoidase activity, and soil organic carbon), as well as plant species diversity and richness trended higher in prairies, but were not significantly different from baseline cool-season grasslands. Overall, restoration with prairie plant communities slowly shifted soil properties, but mining disturbance was still the most significant driver in controlling soil properties. Prairie restoration on reclaimed mine land was effective in establishing a native plant community, with the associated ecosystem benefits.

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