Status of Nitrogen Pools Under Important Cropping Systems in Inceptisols and Vertisols of Northern Telangana, India

Shalini, V.; Chaithanya, A. Krishna; Chandrashaker, K.; Kumari, CH. Aruna

doi:10.9734/ijpss/2022/v34i232538

Cited by 1 publication

(2 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The average content of SOC in the study area (i.e., 3.7 g kg -1 ) is rated low, despite the SOC content varying from 2.3 to 5.6 g kg -1 . This is in line with the findings of Narsaiah et al (2018), Vilakar et al (2021), andShalini et al (2022) who reported the low content of soil organic carbon (5 g kg -1 ) in different district of Telangana state. The lower soil organic carbon in the area may be attributed to lower organic manure application and the farmers in that area barely retain crop residues on the field.…”

Section: Descriptive Statistics Of Soils Parameterssupporting

confidence: 92%

“…The EC value showed low CV, skewness and kurtosis (19.05 %, 0.51 and -0.52, respectively). Low variability in EC is attributed due to the non-saline groundwater used for irrigation purposes Narsaiah et al (2018), Ramulu and Kamalakar (2022), Vilakar et al (2021), Mahesh et al (2018) and Shalini et al (2022) were reported non-saline soil i.e. < 2 dS m -1 in a different part of Telangana state.…”

Section: Descriptive Statistics Of Soils Parametersmentioning

confidence: 98%

See 1 more Smart Citation

Delineation and Evaluation of Management Zones for Site Specific Nutrient Management in Maize Tracts of Northern Telangana using Geostatistical and Fuzzy C Mean Cluster approach.

Bhagwan,

Theerthala,

Devi

et al. 2023

Preprint

View full text Add to dashboard Cite

Identification and demarcation of management zones (MZs) are required to maximize profit, reduce environmental damage, and enhance soil and crop health. The management zone with uniform spatial homogeneity and production potential may solve the problem of sustainable soil nutrient management. Hence, this current investigation was carried out to evaluate variations in soil parameters in order to demarcate the soil fertility zone for site-specific nutrient management. Overall, 200 soil samples (0-15 cm depth) with geographical coordinate were collected with a grid size of 14.2 m × 14.2 m from 4 ha maize cultivated area of Bogumpadu village of Ellanthakuntha mandal, Karimnagar district, Telangana, India. The collected samples were tested with different reagents to know the soil reaction and available nutrients in soil. The geostatistical technique was implemented to assess nutrient variability and preparation of variability map. The spatial variability of soil properties was explained by different models whereas spherical, exponential, and Gaussian models identified as the best-fitted models. Furthermore, the management zone was delineated by principal component analysis and fuzzy C-means clustering algorithm. Five PCs with eigenvalue >1, explaining 99.98 % of variation in overall variation were selected for the next statistics. Three management zone were identified by using the fuzzy performance index (FPI) and normalized classification entropy (NCE). The management zone significantly differs from each other. MZ-1 covers an area of 45.5 %, followed by MZ-2 (29.5 %) and MZ-3 (25%). To evaluate the management zone productivity, site-specific nutrient management experiment was conducted in the maize field. The different fertilizer doses were calculated for three management zones by the Soil test crop response model and compared with farmer fertilizer practices. The result showed the highest maize grain yield in MZ-3 (80. 18 q ha-1) followed by MZ -2 (79.25 q ha-1) and MZ-1 (77.89 q ha-1) and the lowest grain yield with farmer fertilizer practice (72.69 q ha-1). The highest N, P2O5 and K2O fertilizer saving was observed in MZ-3 followed by MZ -2 and MZ-1 compared to farmer fertilizer practices. This study concluded that the management zone concept reduced the application of fertilizer, reduced environmental pollution and increased the maize grain yield and profit.

show abstract

Section: Descriptive Statistics Of Soils Parameterssupporting

confidence: 92%