Soil Fertility Maps Research Articles

Site suitability for Aromatic Rice cultivation by integrating Geo-spatial and Machine learning algorithms in Kaliyaganj C.D. block, India

The purpose of this work is to assess the soil fertility for Tulaipanji rice cultivation in Kaliyaganj C.D. Block using the Analytic Hierarchy Process (AHP) and Machine learning algorithms along with the field survey data and GIS. A total of 40 soil samples from Tulaipanji rice fields (from 0 to 40 ​cm depth) have been randomly collected for the analysis of the soil health condition. For the purpose of assigning ratings to the parameters, ten experts' opinions were taken into account. The final soil fertility map indicates that 18.01% of the land is in excellent health condition to support Tulaipanji cultivation. The artificial neural networks (ANN), support vector machine (SVM), and Bagging models-based suitability analysis was also done using geo-spatial and soil data for Tulaipanji cultivation. Nevertheless, the ANN is the more appropriate model for locational analysis of Tulaipanji cultivation. The ANN-based findings show that areas of 25.8% (77.89 sq. km) are excellent for growing Tulaipanji rice, about 22.01% (66.45 sq. km) are highly suitable, 19.84% (59.90 sq. km) are moderately suitable, 21.19% (63.97 sq. km) are low suitable and 11.16% (33.69 sq. km) are not suitable for Tulaipanji rice cultivation. The receiver operating characteristic (ROC) curve depicts that the applied models have a high degree of accuracy. This endeavour will aid much in the soil fertility and site suitability assessment that will aid local government officials, academics, and the framers, to utilize the lands in a scientific way.

Digital soil assessment of soil fertility for Thai jasmine rice in the Thung Kula Ronghai region, Thailand

Digital soil assessment (DSA) is an application for the interpretation of digital soil mapping (DSM) outputs for evaluating soil and related environmental factors. However, DSA has not been widely applied to assess soil fertility in the humid tropics due to the complexity of integrating numerous soil chemical properties into one map. In this study, principal component analysis was applied to extract the most appropriate soil indicator for crop production. A digital map of soil fertility for jasmine rice was created using a multiple linear regression (MLR) model. Finally, the digital map was confirmed by comparing it with actual rice yield in the Thung Kula Ronghai (TKR) region of Thailand. The calculated soil fertility was significantly expressed by soil pH, electrical conductivity, organic matter, and contents of macronutrients (P, K, Ca, and Mg). The obtained MLR model for this region’s soil fertility consisted of spectral indices (brightness, coloration, normalized difference water, and moisture stress) and topographic indices (slope and topographic wetness). The digital map indicated that more than half of the TKR region contained “very low” to “low” soil fertility. The soil fertility map fits well to actual rice production in the TKR region.

Evaluation of Soil Fertility Map for Beans cultivation in Eghlid Plain by Using Hybrid Fuzzy -AHP and GIS Techniques

The increase in the performance of cultivated plants is under the influence of various features including the soil properties. The nutrient elements of the soil are among the important soil features. The soil fertility should be studied to determine the proper level of fertilizer application. the determination of soil fertility and providing a soil fertility map sounds necessary. In this study, the soil fertility of Shadkam plain in Eghlid county of Fars province, was determined to prepare the soil fertility map for the cultivation of beans. The soil fertility map was obtained by a fuzzy system using a hierarchical analysis in a GIS environment. To this end, soil sampling was conducted from 210 locations and the input data (organic matter, potassium, phosphorous, iron, manganese, zinc, and copper concentrations) were measured. The interpolation of each soil element was achieved by the inverse distance weight (IDW) model in the GIS environment. Then, a membership function was prepared for each factor to obtain the fuzzy map considering their corresponding critical values. Finally, each layer was allocated with weight using the analytic hierarchy process. Based on the relative weight of each criterion, the highest significance and weight was for organic carbon (0.345) while iron showed the lowest weight (0.031). The results also indicated that 0.3, 80.3, and 19.4% of the studied region can be categorized as very poor, poor, and moderate groups in terms of fertility for bean cultivation.

Spatial variability in soil nutrients and fertility mapping using geospatial techniques in Kurnool division of Andhra Pradesh

A revision was undertaken to draw correlation between nutrients available in soil and special indices in chickpea and cotton in the cram area of Kurnool revenue division in Kurnool district of Andhra Pradesh by means of remote sensing plus GIS techniques. A significant and positive correlation was observed between NDVI and available nitrogen during 2017-18 whereas both OC and nitrogen available had considerable positive correlation with NDVI during 2016-17 in chickpea. A significant and positive correspondence was recorded between the NDVI and organic carbon and nitrogen available in cotton during 2016-17. However, insignificant correlation was observed among NDVI and organic carbon or available nitrogen during 2017-18 under cotton cropping.

Evaluation of Balanced Fertilizer Types and Validation of Soil Fertility Map Based on Fertilizer Recommendation in South East Arsi, Ethiopia

A field experiment to evaluate blended fertilizer types and validation of soil fertility map based on fertilizer recommendation was conducted at 10 sites on-farmers’ fields in Lemu Bilbilo and Asasa districts during 2014 and 2015 cropping seasons. The experiment was conducted to compare the effects of multi-nutrient blends that included macro- and micro-nutrients (N, P, K, S, B, and Zn) among each other and against the conventional N and P rate recommendation from Urea and DAP fertilizers. The experiment consisted of six treatments viz. recommended NP and five different types of blended fertilizers laid out in randomized complete block design (RCBD) with three replications. The P and S containing fertilizers were drilled along seed line at planting while N was split applied in such a way that half was applied at planting and the remaining half was applied at tillering stage. All management practices in respect of sowing, seed rate, weed control, pest and disease control were done according to agronomic best practices. Combined analysis over locations and years indicated that wheat grain yield, test weight and hectoliter weight were not significantly increased by blended fertilizer application at both Lemu Bilbilo and Asasa areas. The highest wheat grain yield of 4694 kg/ha and 4286 kg/ha were recorded from application of recommended rate of fertilizer at Lemu Bilbilo and Asasa, respectively.

Identification of soil fertility constraints in boranakunte-1 micro-watershed, Tumkur district, Karnataka

Land resource inventory of Boranakunte-1 micro-watershed (939 ha) representing central dry zone (Zone-4) of Tumkur district, Karnataka was carried out using geospatial techniques. Totally 140 surface soil samples at 250 m2 grid were collected, characterized for chemical and fertility properties and soil fertility maps were prepared using geographic information system (GIS). The results revealed that the soils were moderately alkaline (pH 8.29±0.47) with low total salt content (EC 0.15±0.10 dS m−1) and low to medium in organic carbon (OC) (0.50±0.20%) status. The available nitrogen (N), phosphorus (P) and potassium (K) contents were 238.9±48.8, 31.6±13.3 and 330.8±109.2 kg ha−1, respectively and the available sulphur (S) was 17.36±9.74 mg kg−1. The exchangeable calcium (Ca) and magnesium (Mg) were 21.62±6.32 and 10.82±3.35 cmol(p+)kg−1, respectively. The DTPA extractable iron (Fe), copper (Cu), manganese (Mn) and zinc (Zn) contents were 2.91±0.80, 0.90±0.32, 2.95±1.86 and 0.46±0.20 mg kg−1, respectively. The hot water extractable boron (B) content was 0.60±0.25 mg kg−1. Soil pH, OC, available N, P, Zn and B were found important soil fertility constraints for crop production in the micro-watershed. Thus, proper nutrient management along with correction of soil reaction and soil conservation measures needs to be done in order to enhance productivity.

Mapping of nutrients status in tatrakallu village of anantapuramu district of andhra pradesh using geographic information system

The present investigation was carried out to assess and map the fertility status of chronically drought affected Tatrakallu village in Anantapuramu district of Andhra Pradesh using GIS and GPS. Two hundred fifty geo-referenced surface soil samples (0-15 cm) from Tatrakallu village located in Scarce Rainfall Zone of Andhra Pradesh were collected at 250 m grid interval and analyzed for their fertility parameters. Analytical data was interpreted and statistical parameters like range, mean, standard deviation and coefficient of variation were calculated. Soil fertility maps were prepared for each parameter under GIS environment using Arc GIS v 10.3. Soils were neutral to strongly alkaline (6.49-8.90) in reaction, non-saline (0.01-0.84 dS m-1) and low to medium (0.3-7.0 g kg-1) in organic carbon. The soils were low to medium in available nitrogen (13-266 kg ha-1) and low to high in available phosphorus (2.0-91.0 kg P2O5 ha-1) and available potassium (0.4-628 kg K2O ha-1) and deficient to sufficient in available sulphur (0.1-50.1 mg kg-1). The wide variation from deficient to sufficient was observed in the status of DTPA extractable zinc (0.1-5.6 mg kg-1), iron (0.8-30.7 mg kg-1) and manganese (1.4-39.0 mg kg-1), whereas DTPA extractable copper (0.2-2.7 mg kg-1) was almost sufficient. The fertility status in Tatakallu village revealed that available N, S, Zn and Fe are important soil fertility constraints.

Generating cadastral level digital map of soil macro nutrients of Perambalur block

The study was conducted in Perambalur block to determine the soil nutrient status and to generate cadastral level soil fertility maps. The total geographical area of the respective block is 32076.48 ha and it lies between 11° 31' 53

Mapping of macronutrient status in soils of Gaganbawda tehsil of Kolhapur district using GPS-GIS technique

The present study entitiled “GPS-GIS based soil fertility maps of Gaganbawda tehsil of Kolhapur district (M.S.)” was conducted during year 2016-2017, by using Global Positioning System (GPS) and Geographical Information System (GIS). Soil samples were analysed for pH, EC,OC, Per cent CaCO3 equivalent, available macronutrients N,P,K,S, Exchangeable Calcium, magnesium and sodium. The availability of macronutrient and their relationship with soil properties were studied. The soil pH varied from 4.86 to 6.94 with a mean value 5.77 and indicated that strongly acidic to slightly acidic in reaction. The EC of soil varied from 0.10 to 0.32 dSm-1 (mean value 0.15) and indicated that 100 per cent soils were noraml in nature. The per cen CaCO3 equivalent content and organic carbon content ranged from0.37 to 2.25 and 0.58 to 1.80 per cent with a mean value 1.37 per cent and 1.20 per cent respectively. The soils of Gaganbawda tehsil were baerely calcareous to moderatly calcerous and moderate to very high in organic carbon content. The available macronutrients N, P, K and S ranged from 161.50 to 385.72 kg ha-1, 4.48 to 14.33 kg ha-1, 100.80 to 380.80 kg ha-1 and 10.82 to 24.15 mg kg-1 respectively. Soils were low to moderate in available nitrogen, very low to moderate in available in phosphrous, moderate to very high in available potassium and moderate to high in available sulphur. The exchangeble calcium, magnesium and sodium ranged from 2.20 to 10.40 [Cmol(p+) kg-1], 0.30 to 7.10 [cmol(p+)kg-1] and 0.10 to 0.52 [cmol(p+)kg-1]. Exchangeable calcium and magnesium were 100% deficient. Organic carbon showed positive significant correlation with available K and negative significant corrleation with sulphur. CaCO3 showed positive significant correlation with potassium, calcium and magnesium.

Soil Fertility Assessment of Sainamaina Municipality, Rupandehi, Nepal

Soil fertility assessment is a very fundamental task for farmers and agricultural planners to adopt appropriate fertility management practices, to recommend applying lacking fertilizers, to make fertility-based agricultural plans,s and to produce a large number of crops in their land. This study assesses the soil fertility status of Sainamaina Municipality, ward no. 5-9, Rupandehi district based on soil sample data collected from the field. Soil test based fertility assessment, calculation of overall fertility of area using fertility index, and preparation of soil fertility map is carried out. As soil fertility, the status of total nitrogen (TN), phosphorus (P2 O5), potassium (K), organic matter (OM), and soil pH are measured. As a result, the status of TN, (K2 O), and OM is found low, the status of (P2 O5 ) is found high and soil pH is found in range of very strongly acidic to slightly alkaline.

Use of GIS in soil fertility mapping of Rapti Municipality, Chitwan, Nepal

Mapping the spatial distribution of soil fertility in a particular area gives an idea about the nutrient content in the soil which plays an im-portant role in fertilizer recommendation, sustainable soil manage-ment, integrated plant nutrient management, landuse planning, and site-specific nutrient management (SSNM). A study was carried out to assess the soil fertility status of the Rapti Municipality, Chitwan, Ne-pal. A total of 120 soil samples was collected based on land use, slope, and aspects with the useof Google Earth Pro (GEP) and ArcGIS. Based on the soil test report spatial variation of soil texture, soil pH, total nitrogen, available phosphorous, and potassium of the study area was prepared. The majority of the study area (57.11%) has sandy clay soils. The soil pH was very strongly acidic to slightly alkaline with pH values ranging from 4.8 to 8.0. Soil organic matter (1.94-3.75%), total nitrogen (0.097-0.187%), available phosphorous(51.03-270.10 kgha-1), and available potassium (169.87-358.68 kgha-1) in the soil are within the range of medium to high in the study area. To maintain this nutrient status, the use of organic manure, reduced use of chemical fertilizers, and different soil management practices should be adopted in this area.

Pedogenic and Contemporary Issues of Fluvisol Characterization and Utilisation in the Wetlands of Bamenda Municipality, Cameroon

Fluvisols in urban wetlands in Bamenda Municipality Cameroon play a vital role in vegetable production but they are under immense pressure. Seven representative soil profiles and 21 surface soil samples were morphologically and/or physico-chemically characterized to classify the soils, evaluate their agro-utilization constraints, and to provide adequate data for planning sustainable land management. The soil samples were analyzed using standard procedures. Critical levels established for tropical crops and vegetables were used to declare deficiency of soil nutrients. The coefficient of variation were used as an index of soil variability, while sources of soil variation and subsequent grouping into management units were identified using principal component analysis. The soils, classified as Humi-umbric fluvisols are developed from young alluvio-colluvial material of granitic origin. Like other physico-chemical properties, organic matter varied irregularly down the profile. Except of pH which was slightly (CV<15%) variable, most soil properties were moderately (CV=15-35%) to highly (CV>35%) variable. Some correlation coefficients between the soil parameters were highly significant (p<0.01) ranging - 0.95 to 0.99, but most of them have correlation values less than 0.5. Six principal components (PCs) grouping soils in management units explained 96.2% of the variations observed in the soil properties. The PCs were: base status, organic matter, weathering and moisture retention, acidity, dispersal and N-mineralization, and mineral neo-synthesis factors. We recommend that a detailed mapping of soil properties be carried out for the establishment of a soil fertility map; and individual soil management practices defined for identified units instead of a common management for all units in the municipality.

Soil Fertility Mapping Using Soil Health Card data and Geospatial Technology in Ri Bhoi District of Meghalaya

Soil Fertility Mapping Using Soil Health Card data and Geospatial Technology in Ri Bhoi District of Meghalaya

Quantifying and Mapping of Major, Secondary and Micronutrient Status of Tomato Growing Soils in Kolar District, Karnataka Using GIS and GPS Approach

Assessment of land use-induced changes in soil properties is essential for addressing issues of spatial variability in soil fertility and sustainable land productivity. In view of this, a study was conducted to assess the impact of spatial variability on physicochemical properties, macro and micro nutrient status of 75 farmers fields of tomato growing areas of Kolar district, Karnataka. Arc Map with spatial analyst function of Arc GIS software was used to prepare soil fertility maps, which would act as an important tool for soil as well as nutrient management for sustainable crop production by using Global Positioning System coordinates. The results revealed that the soils under investigation were acidic to alkaline in reaction (pH 4.41 to 8.13), mostly non saline and low to high in organic carbon status (0.53 to 1.95%). Available nitrogen, phosphorus, potassium and sulphur content varied from 150.53-348.10, 6.4 - 111.44, 147.18 - 916.61 and 12.29 - 103.8 kg ha-1. Exchangeable Ca, Mg are in the range of 2.5 – 14.2 and 1.2 – 6.6 C mol (p+) kg. The GIS-aided thematic maps with respect to available zinc, 6.67 (low), 21.33 (medium) and 72 (high) per cent samples were categorized, based on the existing critical limits. All the studied samples i.e., 100 per cent were high in copper content, 65.33, 30.67 and 4 per cent samples of Mn, 25.33, 32 and 42.67 per cent samples of Fe, were categorized as low, medium and high in nutrient status respectively. With respect to available boron 16.67 per cent was under low, 38.09 per cent was under medium and 45.24 per cent was under high nutrient status. The nutrient index (NI) of tomato growing areas of Kolar district revealed that N (1.19), manganese (1.39) and iron (1.29) were categorized as low, available boron (2.17) as medium and P (2.65), K (2.71), S (2.65) zinc (2.75), copper (3.0) as high nutrient index category.

Rapid soil fertility prediction using X-ray fluorescence data and machine learning algorithms

Conventional soil fertility analyses are laborious, costly, time-consuming, and produce hazardous waste. The high demand of these laboratory-based analyses prompted us to investigate an environment-friendly, rapid, and inexpensive methodology for soil fertility assessment. Portable X-ray fluorescence (pXRF) spectrometry allows the determination of total elemental concentration in soils quickly, simply and without hazardous waste production. However, incipient usage of this technology for the prediction of soil fertility properties has been reported for tropical conditions. Soil samples were collected from seven Brazilian states (n = 1975) aiming to use pXRF data to predict contents of available or exchangeable Ca2+, Mg2+, Al3+, K+ and P by testing different algorithms using 70% of the samples for model training, and the remaining 30% for model validation. In addition to point data predictions, the best performing models were applied to data obtained from a farm within the studied regions with a known cropping history to create soil fertility maps and illustrate another applicability of this approach. The attested use of pXRF data and machine learning algorithms stepwise Generalized Linear Model (GLM) and Random Forest (RF) to predict the contents of relevant soil fertility properties exhibited great potential. Validation of the models corroborated that RF resulted in more accurate predictions than GLM. Validation R2 values ranged from 0.59 to 0.82. Maps created were coherent with expected distributions of soil fertility attributes. This environment-friendly methodology may be used for the assessment of soil fertility properties in a wide range of tropical and subtropical soils with minimum waste generation and reduced costs.

Geostatistical based soil fertility mapping of Horticultural Research Station, Rajikot, Jumla, Nepal

Geostatistical soil mapping is important for determining spatial distribution of soil parameters. This study was conducted to assess soil spatial distribution of the Horticultural Research Station, Rajikot, Jumla, Nepal. The total 27 samples were collected randomly at a depth of 0-20 cm by using soil sampling auger. A GPS device was used for determination of geographical position of soil sampling points. The collected samples were analyzed following standard analytical methods in the laboratory of National Soil Science Research Centre, Khumaltar. The Arc-GIS 10.1 software was used for the mapping spatial distribution of various soil parameters. The observed data revealed the structure was sub-angular blocky and granular, whereas colour were dark brown to dark grayish brown and dark yellowish brown. The sand, silt and clay content were ranged 24.40-72.10%, 19.40-63.10% and 6.20-14.50%, respectively and categorized loam, sandy loam and silt loam in texture. The soil pH was slightly acidic to moderately alkaline (5.01-8.06), and very low available sulphur (0.59-2.41 mg/kg) and very low to low available boron (0.04-0.87 mg/kg). Moreover, very low to medium available manganese (2.18-13.46 mg/kg), very low to very high available iron (4.50-138.58 mg/kg), and low to medium available magnesium (7.20-177.60.53 mg/kg) and zinc (0.26-1.66 mg/kg). Similarly, medium total nitrogen (0.09-0.22%), medium to high organic matter (1.71-6.26%) and available calcium (1200-3144 mg/kg), medium to very high available phosphorus (3.71-82.4 mg/kg) and potassium (59.37-173.05 mg/kg). Correspondingly, high to very high available copper (0.78-4.20 mg/kg). The determined soil test data can be used for sustainable soil management as well as developing future research strategy in the farm.

Evaluation of balanced fertilizer types on yield and yield components of sorghum and validation of soil fertility map based fertilizer recommendation

Sorghum has tremendous uses for the Ethiopian farmer and no part of this plant is ignored. However, the productivity of sorghum is low. In Harari region, the average productivity of 22.22 Quintal ha-1 which is even below the national average yield of 27.26 Quintal ha-1 mainly constrained by soil nutrient deficiencies.

Producing the digital soil fertility map of Karelia

Recent advancements in soil digital mapping have opened new opportunities for handling the scientific and applied problems of ecological soil monitoring, inventory of land and soil resources, and are generally helpful in optimizing the management of natural resources. For Karelia the development of forest soil assessment techniques is essential, considering that 95% of the republic’s land is forest soils. This paper tells about the process of creating an updated digital map of forest soils fertility in Karelia, scale 1 : 500 000. To this end, the archival soil productivity map of the republic, produced in paper version by R.M. Morozova in 2000, was scanned and converted into a vector layer with the use of the MapInfo Professional 8.5 software package. The resultant layer was aligned with the existing digitalized soil map of Karelia, which served as the basis for constructing the thematic layer according to the data on the fertility of each soil type. As a result of this study, the soil fertility assessment scale was specified and the percentage ratio of soils of different productivity in Karelia was calculated. The digital soil fertility map is an important information source of archival and modern data, and also is a part of the GIS for soils of Karelia.

Assessment of soil fertility through GIS techniques and thematic mapping in micro-watershed of Hassan, Karnataka

The study was conducted to assess the soil fertility status and to prepare the fertility mapping at Honnvalli micro-watershed of Hassan district during 2019 by using GIS and GPS techniques. The 105 grid soil samples were drawn from an area of 420 ha each at 400 m intervals and analysed for surface soil physicochemical and biological properties. The results revealed that overall Honnavalli micro-watershed found acidic pH area (93%), low organic carbon (55% area) and normal EC (100% area), further the watershed area was low in available N (51% area), P2O5 (77% area) and medium in K2O (48% area). The exchangeable Ca and Mg were sufficient in 95 and 72 per cent of the watershed area, respectively. The 95 per cent of the watershed area has sufficient available Sulphur. The surface soil fertility maps of pH, EC, OC, available nitrogen, phosphorus and potassium, exchangeable calcium and magnesium and available Sulphur were prepared through ArcGIS and thematic maps.

Evaluation of the soil fertility for corn production (Zea Mays) using the multiple-criteria decision analysis (MCDA)

The ongoing water deficiencies in arid and semi-arid regions in conjunction with certain nutritional requirements highlight the importance of pinpointing the most optimal locations for cultivating agricultural products with the highest yield. Given the importance of this issue, this study proceeds to prepare soil fertility maps for corn production (Zea Mays L.) in Fars province, Iran. Initially, fuzzy membership functions (FMs) are employed to prepare fuzzy maps for each layer in the geographic information system (GIS), after which feature selection algorithms are deployed to designate the most relevant layers. The layers are then assigned specific weights obtained using a combination of analytic network process (ANP) and analytic hierarchy process (AHP) methods to prepare soil fertility maps. The input data consist of organic content (OC), phosphorus (P), potassium (K), iron (Fe), zinc (Zn), manganese (Mn), and copper (Cu). Inverse distance weighting (IDW) is utilized to procure interpolation maps for each layer. Thereafter, zoning maps are obtained using FMs. Ultimately, ANP and AHP models are once again deployed to generate the final overlayered fertility maps for corn production. The results show that combining the ANP method with feature selection (OC, K, Fe, and P) results in higher accuracy than solely applying the AHP method. Thus, incorporating feature selection and ANP methods with both inter and intra-group pair-wise comparison would result in more accurate fertility maps for corn production with lower costs and time complexity.