Soil Fertility Evaluation Research Articles

Critical levels and fertility classes of soils with high-activity clay in the Brazilian semi-arid region

ABSTRACT Soil fertility evaluation is important for adopting conservation management and adequate nutrient supply. The objective of this study was to identify critical levels and soil fertility classes using the boundary line method for rainfed crops (corn, cowpea and sabiá [Mimosa caesalpiniifolia]) in the Brazilian semi-arid region. A database of 226 soil fertility analyses of samples from the 0.00-0.20 m soil layer, and corn, cowpea and sabiá yields from Ceará State was used to generate interpretation classes (at 80 and 95 % of maximum yield). In a scatter plot, soil nutrient concentrations (x-axis) and relative crop yields (y-axis) were correlated, and the border points fitted to a quadratic model. Proposed interpretation classes were classified as very low, low, adequate, high and very high, except for Na + , whose adequate class was considered tolerable. Generated models showed coefficients of determination (R 2 ) for the chemical properties ranging from 0.54 to 0.92. Based on the interpretation classes, the critical level was determined as 6.3 for pH, 10.8 g dm -3 for OM, 20.9 mg dm -3 for P, 81 mg dm -3 for K, 55 mmol c dm -3 for Ca 2+ , 24 mmol c dm -3 for Mg 2+ and 8 mg dm -3 for S-SO 4 2- . Interpretation classes for soils with high-activity clay in the Brazilian semi-arid region were superior to those in the reference literature. Boundary line method established fertility classes and critical levels for soil chemical properties in more than one crop, using the concept of relative yield.

Integration of indigenous and formal knowledge in the assessment of soil quality performance assessment using multiple factor analysis in Alborz central mountains

Despite the data gap between researchers and farmers in soil fertility assessment, there are similarities and coincidences between the achievements of scientific versus local assessments. Farmers’ land management practices are a function of perceived soil fertility assessment in day-to-day management decisions. Despite the efforts made, studies have yielded different results when comparing soil fertility assessments in terms of indigenous and scientific knowledge, thus calling for closer assessments using extensive creative and systematic approaches. The current study uses Multiple Factor Analysis (MFA) to propose efficiency indicators based on the weighting of familiar, organizational, or productive variables in groups evaluating indigenous, scientific, and data variability. The end goal is to help identify the decision-makers’ training needs and decide on future institutional endeavors for developing productive skills and adopting better measures to evaluate soil fertility. By combining indigenous knowledge with innovations and improving the relationship between scientists and indigenous peoples and also promoting collaboration, thinking, and knowledge acquisition of farmers on how to maintain soil fertility and health, we hope to move towards sustainable agriculture as an institutional reform.

Enhancing crop productivity and its economic farm profitabilty of smallholder farmer through the use of green manures from Alnus acuminata

Decline in soil fertility is a major threat to land productivity and food security in the East African highlands. This calls for the application of nutrient inputs to improve crop productivity. A study was conducted in Nyabihu District of Rwanda from 2013 to 2016 to assess the effect of Alnus acuminata green manure (AGM)─applied in situ, through biomass alone, or combined with inorganic fertilizer─on the productivity and profitability of maize (Zea mays), beans (Phaseolus vulgaris), and potato (Solanum tuberosum). The treatments included application of AGM, inorganic fertilizer, combination of AGM and inorganic fertilizer, and unfertilized plot as a control (except for potato). These treatments were compared in two seasons and on two local soil fertility levels (medium and high) as defined by the farmer’s knowledge and experience. There was a convergence between farmers’ criteria and soil analysis in the soil fertility evaluation. Crops yields were analyzed using a linear mixed model while for other parameters, descriptive statistics were applied. The combination of AGM and inorganic fertilizer recorded the highest increment in maize (44%) and bean (46%) yields compared with inorganic fertilizer while it increased up to 87% compared with the unfertilized control. The financial analysis showed that AGM + inorganic fertilizer recorded the highest value-to-cost ratio (VCR) of 24.6 for potato and a significantly lower VCR (2.9) for maize and beans. The high VCR highlights a significant potential contribution of AGM + inorganic fertilizer to increase incomes of resource-constrained potato farmers in the Rwandan highlands. However, low crop prices possibly make this practice less attractive for those cultivating maize and beans.

Rapid Determination of Soil Organic Carbon and Permanganate Oxidizable Carbon: Comparison of Individual and Data Fusion Performance Using Fourier Transform Mid-Infrared Photoacoustic Spectroscopy (FTIR-PAS) and Laser-Induced Breakdown Spectroscopy (LIBS)

Rapid and accurate prediction of soil organic carbon (SOC) and the carbon fractions that are sensitive to management are vital for evaluating soil fertility and SOC turnover from both long-term and short-term perspectives. This study used 396 soil samples to investigate the individual and combined use of FTIR-PAS and LIBS for both SOC and permanganate oxidizable carbon (POXC) prediction coupled with partial least squares regression (PLSR). The results showed that LIBS from 205 to 899 nm (LIBS-H) was suitable for predicting SOC and POXC, with a coefficient of determination in prediction ( R P 2 ) of 0.68 and 0.73, and a root mean square error in prediction (RMSEP) of 0.57% and 169 mg kg−1, respectively. FTIR-PAS also exhibited good potential for the prediction of SOC and POXC with a slightly poorer performance ( R P 2 of 0.66 and RMSEP of 0.59% for SOC; R P 2 of 0.72 and RMSEP of 171 mg kg−1 for POXC). The prediction ability of SOC was improved by low-level data fusion based on direct concatenation of FTIR-PAS spectra and LIBS spectra at the range of 184–205 nm (LIBS-L), resulting in an R P 2 of 0.72 and an RMSEP of 0.53%. In general, there is good potential for combining FTIR-PAS and LIBS-L to improve the SOC prediction. Both FTIR-PAS and LIBS-H can be applied for individual prediction of SOC and POXC. In addition, FTIR-PAS offers the advantages of reduced complexity in the modeling and easier sample preparation.

Mapping nutrient and soil fertility indexes for Durum Wheat in the La Mina region of Algeria

The growing population coupled with a reduction in available agricultural land per capita necessitates smart management practices to boost production per unit area and enhance overall land productivity, ultimately ensuring food security. Thus, evaluating soil fertility and productivity is crucial for sustainable agriculture. This study aims to assess the chemical fertility status of the soils within the irrigated perimeter of la Mina, a region in Algeria known for Durum Wheat production. Thirty-two soil samples were collected from the study area and subjected to analysis for total N, available P and K, and organic matter (OM) concentration. All the soils were basic (pH 7.63–8.95), had low concentrations of total N (0.04 and 0.19 %), low concentrations of available P (7.36 – 30 mg kg−1), low concentrations of available K (<0.4 Cmol kg−1) and low concentrations of OM (0.67–2.37 % by weight). Using a Nutrient Index classification, the overall classification of the soils of the irrigated perimeter of la Mina were low for N, P, K and OM. In addition, the Soil Fertility Index revealed three levels of fertility with a dominance of fertility level 5 (low). Application of the FertiliCalc software for the evaluation of nutrient requirements of Durum Wheat showed average requirements of 183 kg ha−1 for N, 65.8 kg ha−1 for P and 579 kg ha−1 for K. In light of these findings, appropriate agricultural practices, including the addition of fertilizers, are required to build and maintain the needs of Durum Wheat in the study area.

Evaluating Soil Fertility as a Basis for Fertiliser Needs for Agricultural Crops

Evaluating Soil Fertility as a Basis for Fertiliser Needs for Agricultural Crops

KAJIAN KESUBURAN DAN KESESUAIAN LAHAN BERBASIS KOMODITAS DI KECAMATAN TUGU DAN KARANGAN KABUPATEN TRENGGALEK

Drought is a major challenge in developing the integrated farming system (IFS) in Trenggalek Regency, making it one of the factors contributing to the construction of the Tugu Dam. Additionally, in developing the IFS area, it is necessary to assess soil fertility and land suitability evaluation for food and livestock feed commodities. The research was conducted in Tugu and Karangan Sub-Districts, Trenggalek Regency by conducting spatial analysis and soil survey at locations potentially affected by dam construction and soil samples analysis at the laboratory. The results of this study found that the level of soil fertility at the research site was included in the low to very low class with characteristics of acidic pH, very low C-organic, very low total N and low base saturation. While the results of the actual land suitability evaluation of rice, maize, and elephant grass showed the land suitability class S3 with limiting factors of C-organic, pH, total N, P2O5, and base saturation.

Mapping Key Soil Properties of Cropland in a Mountainous Region of Southwestern China

Soil organic carbon (SOC), total nitrogen (TN), total phosphorus (TP), and total potassium (TK) are important indicators for evaluating soil fertility. Exploring the content and spatial distribution of these indicators is of great significance for optimizing cropland management measures and developing sustainable agriculture. Yunnan Province is one of the most important agricultural regions in southwestern China, characterized by large variations in the topography and an uneven distribution of soil fertility. In this study, the data of 8571 topsoil (0–20 cm) samples selected from Yunnan Province and a portion of related spatial data were used to carry out electronic mapping of the spatial distribution of soil sand content, clay content, silt content, SOC, TN, TP, TK content, and C:N ratio at 1 km resolution using the Random Forest (RF) model. The results indicated that the average measured contents of SOC, TN, TP, TK, and C:N ratio in the topsoil of Yunnan Province were 18.78 ± 0.09 g/kg, 1.78 ± 0.01 g/kg, 0.98 ± 0.01 g/kg, 13.89 ± 0.08 g/kg, and 10.56 ± 0.02, respectively. The spatial analysis showed that higher SOC was mainly distributed in northern and eastern Yunnan, and the spatial distribution pattern of TN and TP was similar to that of SOC. While higher TK was mainly distributed in southwestern Yunnan Province. There was a significant positive correlation between SOC and TN and TP contents with correlation coefficients of 0.889 and 0.463, however, there was a significant negative correlation between SOC and TK content with correlation coefficients of −0.060. It was also indicated that elevation, temperature, precipitation, clay content, sand content, and silt content were the most important factors affecting SOC, TN, TP, and TK content. The present study provided an understanding of soil nutrients characteristics and their affecting factors, which is helpful to optimize agricultural management practices and develop sustainable agriculture according to soil fertility.

Self-driven dual reinforcement model with meta heuristic framework to conquer the iot based clustering to enhance agriculture production

In agriculture, irrigation is essential for providing water to crops based on the type of soil they are grown in. To achieve success in farming, it is important to evaluate soil fertility, temperature, rainfall and set irrigation schedules. In this work, to enhance agricultural production, an IoT-based hydration system that utilizes soil moisture and humidity sensors to keep an eye on soil conditions and water crops precisely is developed. This system effectively manages water usage in farming, resulting in an efficient conservation of water resources. The proposed model is categorized into four main phases: (a) Pre-processing; (b) Clustering; (c) Feature extraction; (d) Classification. Initially, the collected raw data is pre-processed via a data-cleaning approach. From the pre-processed data, DB scan is used to cluster the data. From the clustered data, the important feature is extracted by using statistical features like mean, standard deviation, kurtosis, and skewness. Subsequently, from the extracted features, the most optimal features are selected via a new hybrid meta-heuristic optimization model referred to as Cuckoo search-based Levy adolescent identity search algorithm (CLAIS). The projected CLAIS model is the conceptual amalgamation of the standard Cuckoo search optimization (CSO) and adolescent identity search algorithm (AISA), respectively. CLAIS-based deep Q network (CLAIS-DQN) classifier is used to classify the optimal features. DQN is an efficient solution to offload the request optimally which improves the overall performance of the network. The proposed model is implemented using the PYTHON platform. The proposed model has recorded the highest detection accuracy as 96%.

Evaluation of Soil Fertility Status on Oil Palm Cultivation Land (Elaeis guineensis Jacq.) In Pulo Padang Village

Declinen soil fertility on crop cultivation land has become a problem that must be considered. As an effort to rehabilitate these lands, it is very necessary to carry out appropriate actions. One way is to evaluate soil fertility by looking at the soil chemical characteristics of land that has been managed intensively. The aim of this research is to determine the chemical characteristics of the soil and the status of soil fertility on agricultural land in Pulo Padang Village, Rantau Utara District, Labuhanbatu Regency. The method used in this research was a survey method and soil sampling which was carried out by purposive sampling on oil palm plants which were composited, air-dried and chemical analysis of the soil was carried out in the laboratory. The results of research on soil chemical characteristics show a soil pH value of 5.0-5.2 with acid status, C-organic 1.42-1.67% (Low), Total Nitrogen 0.13-0.15% (low), P2O5 with a value of 283-400 mg/100g (Very High ), P available 36.2-126.6 ppm (Very High), Base cations can be exchanged Ca2+, Mg2+, K+, Na+ namely 7.19-8.13 cmol/kg (Medium), 3.22-3.93 cmol/kg (High), 0.17-0.30 cmol/ kg (Low), 0.08-0.22 cmol/kg (Very low), CEC 14.66cmol/kg (Very Low) and 21.98 cmol/kg (Medium), KB 57-73 % (Very High). The soil fertility status of agricultural land in Pulo Pandang Village, Rantau Utara District, Labuhanbatu Regency has a low fertility status, so management measures are needed to increase soil fertility

Soil Fertility Evaluation of Wheat /Alfalfa Intercropping

Perfect evaluation of soil fertility is the basis of constructing crop fertilization scheme. In this paper, principal component analysis, systematic cluster analysis and diagnosis of soil nutrient abundance-deficiency were used to evaluate the soil fertility of wheat/alfalfa intercropping system. The results of soil fertility evaluation showed that the soil fertility of wheat/alfalfa intercropping was higher than that of exclusive alfalfa, but lower than single wheat's. Diagnosis of soil nutrient abundance-deficiency indicate that the soil total nitrogen and available nitrogen were deficient, the soil total potassium and available phosphorus were moderate, but the soil total phosphorus and available potassium were abundant. The study results means that the system should focus on nitrogen fertilizer inputting and the controlling of the distribution amount of potassium fertilizer.

Evaluasi kesesuaian lahan padi pasang surut di Distrik Kamundan Kabupaten Teluk Bintuni

Agricultural activities on tidal marshland are strongly influenced by the tide (rise) and ebb (fall) of sea or river water. This study aims to (1) Determine soil physical and chemical property criteria; (2) Evaluate soil fertility; and (3) Evaluate tidal paddy suitability. The research site is in the tidal lands of Kamundan District of Teluk Bintuni Regency. The method used is a descriptive method with a survey technique. The results of the study were obtained (1) Criteria of physical and chemical properties of the soil has the physical properties of dusty clay. Soil chemical properties are average slightly acidic pH, low C-organic, medium, high, low to moderate N-total, very low to low P-available, very low to low Potassium, very low KTK, and high KB. (2) Soil fertility status is classified as low which is influenced by low values of P-available and Potassium soil. Low p-available soils are present on (river embankments, switchbacks and back bogs) and Low classified soil Potassium is present on river embankments, and (3) The results of land suitability analysis obtained on river embankments have an actual land suitability class of S3Na with limiting factor P-available, Very low Potassium can be upgraded into potential land suitability by performing Phosphate and Potassium fertilization with proper dosages and schedules, addition of organic matter through the use of manure. In the Intermediate and Back Swamp areas obtained the actual land suitability of S3na with a very low Potassium limiting factor can be increased to potential land suitability by performing Potassium fertilization with proper dosage and schedule, addition of organic matter through the use of manure.

Evaluation of soil fertility using combination of Landsat 8 and Sentinel‑2 data in agricultural lands.

Today, remote sensing is widely used to estimate soil properties. Because it is an easy and accessible way to estimate soil properties that are difficult to estimate in the field. Based on this, to evaluate the soil fertility (SF), soil sampling was performed irregularly from the surface depth of 0-30cm in 216 points, 11 soil properties were measured, and the soil fertility index (SFI) was calculated by soil properties. Simultaneously, we combined satellite images of Landsat 8 and Sentinel-2 using the Gram-Schmidt algorithm. Finally, multiple linear regression SFI was calculated using satellite data, as well as the spatial distribution of SFI was obtained in very low, low, moderate, high, and very high classes. Our findings showed that the combination of Landsat 8 and Sentinel-2 data using the Gram-Schmidt algorithm has a higher correlation with SFI than when these data are individually. Therefore, combined Landsat 8 and Sentinel 2 data were used for SFI modeling. Using model selection procedure indices (including Cp, AIC, and ρc criteria), the visible range bands, notably blue (r = 0.65), green (r = 0.63), and red (r = 0.61), provide the best model for estimating SFI (R2 = 0.43, Cp = 3.34, AIC = -277.4, and ρc = 0.44). Therefore, these bands were used to estimate the SFI index. Also, the spatial distribution of the SIF index showed that the most significant area was related to the low class, and the lowest area belonged to the high and very high fertility classes. According to these results, it can be concluded that using the combination of Landsat 8 and Sentinel 2 bands to estimate soil fertility index in agricultural lands can increase the accuracy of soil fertility estimation.

Soil Fertility Evaluation in Long-term Paddy Field on Small Island: A Preliminary Research in Savana Jaya Village, Buru Island, Maluku Province, Indonesia

Efforts to increase rice production continue to face severe challenges, primarily attributed to the declining quality of paddy field soil resources. This study aims to investigate the management of fertilizer utilization and chemical properties of six rice paddy soils in Savana Jaya Village, Waeapo District, Buru Regency. Additionally, it seeks to assess the soil fertility status after 10 to 40 years of continuous rice planting and recommend an approach for fertilizer application. These fields were selected using a purposive sampling method. The soil samples were analyzed total nitrogen (N), potential phosphorus (P), and potential potassium (K) content, as well as cation exchange capacity (CEC). Rice production data was collected by interviewing farmers. The results showed that the soil organic C content and the total N were very low to low, the potential P status was moderate to very high, the potential K status was low to moderate, and the CEC-s of all fields were very low. The soil fertility status of all fields was very low. Organic matter is essential for maintaining the health and fertility of paddy soil, particularly in small islands where the soil is often subjected to intensive use of inorganic fertilizers, posing potential environmental contamination concerns.

Soil fertility evaluation and mapping

Soil fertility evaluation and mapping

STATUS KESUBURAN TANAH PADA LAHAN SAWAH DILINDUNGI YANG BERALIH FUNGSI DI KAPANEWON SEYEGAN, KABUPATEN SLEMAN, DAERAH ISTIMEWA YOGYAKARTA

The conversion of rice fields in Seyegan is suspected to occur due to low soil fertility. This study was conducted to analyze the extent and distribution of conversion of rice fields associated with soil fertility status. This study used a survey method, purposive determination of sample points on rice fields representing the converted rice fields, and soil samples were taken compositely. Data analysis used spatial analysis, graphs, and laboratory tests. The parameters tested were cation exchange capacity (CEC), Base Saturation, potential P2O5, potential K2O, and organic C. Determination of soil fertility status was based on The Technical Guidelines For Soil Fertility Evaluation of Soil Research Center. The results showed that the area of rice fields in Seyegan District in 2015-2022 decreased by 55.26 ha (3.76%), with an average annual decrease of 7.89 ha. The soil fertility status in rice fields converted into settlements was very low to medium, rice fields into dryland and poultry farming were medium, and rice fields into shrubs and factories were low. The limiting factors of soil fertility were CEC and organic C.

An Investigation into Ensemble Learning Techniques for Evaluating Soil Fertility through Analytical Approaches

At the heart of India’s livelihood lies agriculture, a foundational and ever-evolving sector. The realm of agriculture faces modern challenges, encompassing unpredictable climate fluctuations, insufficient irrigation infrastructure, and erratic weather conditions. Amidst these challenges, machine learning has emerged as a valuable tool for evaluating soil fertility and Crop assessment in agriculture. Ensemble machine learning methodologies have garnered attention for their potential to enhance predictive capabilities. These techniques involve constructing meta-classifiers that collectively contribute to improved predictive accuracy. This paper centers on the analysis of soil data acquired from testing laboratories, to predict fertility based on a comprehensive dataset. The study employs prominent ensemble machine learning algorithms, specifically focusing on boosting techniques, to elevate predictive accuracy and ensure heightened consistency.The assessment of soil fertility categories involved the examination of 12 carefully chosen attributes. Diverse soil parameters were measured to facilitate the prediction of soil fertility levels. The outcomes of the experimentation revealed that the application of the boosting technique using the Xgboost algorithm yielded superior accuracy compared to alternative ensemble classifiers, achieving a remarkable 96% accuracy rate.

Farinha de ossos e hidrogel aumentam a fertilidade do solo com cultivo de cajueiro em áreas semiáridas

ABSTRACT Cashew trees are often cultivated in semi-arid regions with poor soil and limited rainfall, presenting significant challenges for soil management. This study aimed to evaluate soil fertility based on varying doses of bone meal (0, 250, 500, 750 and 1,000 g pit−1), mixed into the planting pit with or without moisture-retaining hydrogel (0 and 5 g pit−1), in dwarf cashew ‘BRS 226’ cultivation. The soil chemical attributes were monitored over two growing seasons. The bone meal application increased the soil pH by 221 % along the two years and boosted the organic matter by 13 % in the first year and 28 % in the second one. The use of 5 g of hydrogel per pit, combined with 1,000 g of bone meal per pit, is recommended to improve the soil fertility in semi-arid cashew-growing areas over a two-year period. The bone meal fertilization in cashew planting promotes beneficial changes in the soil, and the hydrogel has a great potential in cashew farming, offering an alternative for expanding the fruit production in regions with low rainfall and sandy soils.

Bioremediation of chlorpyrifos-contaminated soil with biduri plant (Calotropis gigantea), bacteria, and biochar: Soil fertility impact

During the Industrial Revolution, agriculture was linked to environmental issues. One issue is pesticide pollution. Bioremediation is needed because plant diseases and pests cause farmers to use pesticides excessively, polluting and decreasing soil production. This study evaluated soil fertility from bioremediation with biduri plants, bacteria, and biochar on chlorpyrifos-polluted shallot-growing soil in Brebes Regency. This type of research was an experiment in a greenhouse, using a factorial experimental design with a completely randomized design, consisting of two factors, namely bioremediation agent (A0: without bioremediation agent, A1: Atlantibacter hermannii, A2: bacterial consortium) and coconut shell biochar (B0: without biochar, B1: with biochar). There were six treatment combinations, then replicated three times for each treatment, so there were 18 treatment units. The data were statistically analyzed using ANOVA, Duncan Multiple Range Test, and Pearson correlation. The results showed that the best treatments that were able to improve soil fertility after bioremediation were treatments A1B0 (Atlantibacter hermannii + without biochar), A2B0 (bacterial consortium + without biochar), and A2B1 (bacterial consortium + with biochar). The A1B0 treatment (Atlantibacter hermannii + without biochar) increased the pH by 4.97%, and the soil available P was 12 times higher than the initial soil. The A2B0 (bacterial consortium + without biochar) treatment increased soil cation exchange capacity by 99.81% and soil organic C by 116% higher than the initial soil. The A2B1 (bacterial consortium + with biochar) treatment increased soil total N by 37.50% and available K by 38.47%, higher than the initial soil.

Evaluation of Soil Fertility for Crop Production in Beel Chiroil, Pabna, Bangladesh

The study area is at Beel, Chiroil, Chatmohar, Pabna, Bangladesh. Ten soil sampling locations were selected from this area. Based on soil type and existing cropping patterns, soil samples were collected after harvesting the crops from each selected location of the study area. All soil samples (ten) were collected as per Soil Samples Collection Method of Soil Resources Development Institute (SRDI). The collected soil samples were submitted to the Central Laboratory of SRDI. The test results of the soil samples found that, the soil of the study area contained neutral soil pH (6.87), medium organic matter (3.58%), nitrogen (0.198 Meq/100g), potassium (0.256 Meq/100g) and zinc (1.15 μg/g), low phosphorus (13.503μg/g), sulfur (19.83 μg/g) and boron (0.28 μg/g) and very high iron (53.14 μg/g), calcium (20.288 Meq/100g) and magnesium (10.167 Meq/100g) on average. Interpretation of the soil test results indicate that, fertility condition of the research field will provides a good basis of fertilizer recommendation for the study area farmers. A recommendation of fertilizer doses is prepared according to Fertilizer Recommendation Guide, 2018 of Bangladesh Agricultural Research Council (BARC). The research also helps to suggest some suitable cropping patterns for the study area.