Characterization, Suitability Evaluation and Soil Quality Assessment of Three Soils of Sedimentary Formation for Sustainable Crop Production

Adeyolanu, Olateju Dolapo; Are, Kayode Steven; Adelana, Ayodele Olumide; Denton, O. A.; Oluwatosin, G. A.

doi:10.9734/jaeri/2017/31943

Cited by 7 publications

(7 citation statements)

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“…Several studies have demonstrated the significant correlation between soil suitability and climatic parameters such as temperature and precipitation. The soil resource is an essential aspect of sustainable agriculture, recognized as a crucial agronomic variable that entirely relies on the food production of specific agricultural land, ensuring an increase in food demand [ 49 , 67 , 68 ]. The study has shown the reliability of using low spatial resolution data for large-scale analysis.…”

Section: Discussionmentioning

confidence: 99%

Mapping soil suitability using phenological information derived from MODIS time series data in a semi-arid region: A case study of Khouribga, Morocco

Ismaili,

Krimissa,

Namous

et al. 2024

Heliyon

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Section: Discussionmentioning

confidence: 99%

Mapping soil suitability using phenological information derived from MODIS time series data in a semi-arid region: A case study of Khouribga, Morocco

Ismaili,

Krimissa,

Namous

et al. 2024

Heliyon

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“…Characterized by a tropical climate, Badeggi experiences distinct wet and dry seasons, with annual rainfall averaging 1127 or 32 mm less and a growing season of 200 or 15 days less (Adeyolanu et al 2020). The wet season, from April to October, peaks in September, while the dry season spans November to March.…”

Section: Study Areamentioning

confidence: 99%

Characterization and classification of soils of a paddy field in Badeggi, Niger State, Nigeria

A.A. Panti,

Musa Audu,

M. Yakubu

et al. 2024

JAE

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This study was conducted with the aim of characterizing and classifying the soils of a paddy field in Badeggi Katcha local Government Area of Niger State. Two pedons were dug representing upper and lower slopes of the field and were designated as Badeggi 1 and 2 (BDG1 and BDG2) respectively. The pedons were described on the field following the FAO guidelines for soil description. Soil samples were collected from each identified natural horizons and taken to the laboratory for analysis. Results revealed that BDG1 had greyish brown (10YR 5/2) at the topmost horizon and light brownish grey (10YR 6/2) at the subsoil, while BDG2 had light brownish grey (10YR 6/2) overlying light grey (10YR 7/2) at subsoil. Sand content ranged from 840 to 860 g/kg in BDG 1 and 690 to 830 g/kg in BDG 2, silt ranged from 50 to 70 g/kg in BDG 1 and 90 to 210 g/kg in BDG 2 and clay ranged from 90 to 100 g/kg in BDG 1 and 80 to 100 g/kg in BDG 2. Soils from the two pedons were moderately to slightly acidic, low in organic carbon and available phosphorus, while total nitrogen was rated low to medium and irregularly distributed down the two profiles, but exchangeable Calcium, Magnesium, Potassium and Sodium were high across the study area. Using the USDA soil taxonomy system, the soils were classified as Plinthic Petraquepts (BDG 1) and Fluvaquentic Endoaquepts (BDG 2) which corresponded to Petric Plinthosols (Abruptic) and Fluvic Cambisols (Eutric) respectively, under World Reference Base for Soil Classification (WRB). The study has revealed that BDG1 is moderately well-drained while BDG2 is imperfectly drained. The soils are moderate to slightly acid with low inherent fertility as evidenced by low organic carbon, total nitrogen and available phosphorous. The soils were classified as Inceptisols at Soil Order level.

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“…Due to the different crop nutrient needs and the physico-chemical characteristics of soils, not all soils can be used for agriculture, and not all crops can be successfully produced under certain soil conditions [8]. Researchers believe that mapping land suitability is crucial for this reason [1,9,10]. After rice and corn, wheat is the field crop with the largest cultivation area (217 million hectares), the highest production (776 million tons), and the highest commerce volume (189 million tons) [11].…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence Integrated GIS for Land Suitability Assessment of Wheat Crop Growth in Arid Zones to Sustain Food Security

Behairy

Baroudy

et al. 2023

Agronomy

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Developing countries all over the world face numerous difficulties with regard to food security. The purpose of this research is to develop a new approach for evaluating wheat’s suitability for cultivation. To this end, geographical information systems (GIS) and fuzzy inference systems (FIS) are used as the most appropriate artificial intelligence (AI) tools. Outcomes of investigations carried out in the western Nile Delta, Egypt. The fuzzy inference system used was Mamdani type. The membership functions used in this work are sigmoidal, Gaussian, and zmf membership. The inputs in this research are chemical, physical, and fertility soil indices. To predict the final soil suitability using FIS, it is required to implement 81 IF-THEN rules that were written by some experts. The obtained results show the effectiveness of FIS in predicting the wheat crop’s suitability compared to conventional methods. The research region is split into four classes: around 241.3 km2 is highly suitable for wheat growth, and 224 km2 is defined as having moderate suitability. The third soil suitability class (low), which comprises 252.73 km2, is larger than the unsuitable class, which comprises 40 km2. The method given here can be easily applied again in an arid region. Decision-makers may benefit from the research’s quantitative findings.

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Characterization, Suitability Evaluation and Soil Quality Assessment of Three Soils of Sedimentary Formation for Sustainable Crop Production

Cited by 7 publications

References 0 publications

Mapping soil suitability using phenological information derived from MODIS time series data in a semi-arid region: A case study of Khouribga, Morocco

Mapping soil suitability using phenological information derived from MODIS time series data in a semi-arid region: A case study of Khouribga, Morocco

Characterization and classification of soils of a paddy field in Badeggi, Niger State, Nigeria

Artificial Intelligence Integrated GIS for Land Suitability Assessment of Wheat Crop Growth in Arid Zones to Sustain Food Security

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