Soil Fertility and Nutrient Management

Nair, Kodoth Prabhakaran

doi:10.1007/978-3-030-15530-8_17

Cited by 19 publications

(10 citation statements)

References 22 publications

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“…Compared with 225 kg/ha, the maximum safe usage internationally recognized [2], the intensity of chemical fertilizer in China's grain production is still in low use efficiency with excessive usage mainly because of poor soil nutrient management [5][6][7], which leads to excessive nutrient pollutants runoff into the natural environment and severe nonpoint source pollution in many Chinese rivers such as the Yangtze rivers and seas such as the Yellow Sea [8][9][10][11], and high environmental governance cost for government [12,13]. The problem will likely continue to increase in the future, as a result of the food demand by a growing population in China [14], and is also widespread in many other developing countries [15].…”

Section: Introductionmentioning

confidence: 99%

Technical Efficiency of Chemical Fertilizer Use and Its Influencing Factors in China’s Rice Production

Sun

2021

Sustainability

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Low technical efficiency and excessive usage of chemical fertilizer in grain production is a problem commonly faced by China and many other developing countries, which leads to serious environment pollution and high environmental governance cost. China is the largest rice producing and consuming country, and several kinds of rice are grown in China and all of which are important edible grain. However, there has been no systematic research on kind difference and provincial difference of technical efficiency of chemical fertilizer use (TEFU) for rice production. Using the data of China’s 22 rice production provinces from the China Agricultural Product Cost-Benefit Compilation and the China Statistical Yearbook, this study measures the TEFU for early indica rice, intermediary indica rice, late indica rice, and japonica rice production by using a stochastic frontier production function (SFPF) model, and then analyzes TEFU’s influencing factors using a Tobit model and conducts the robustness check using a panel data fixed effect model. We found that, on average, TEFU for four kinds of rice production were improved significantly during 1997–2018, increasing by 67.70%, 39.93%, 14.76%, and 21.88%, respectively. TEFU for China’s rice production have significant differences among different kinds and production provinces, and still have large improvement potential. Government’s fiscal support to agriculture, agricultural labor productivity, agricultural mechanization, effective irrigation, and implementation of the “Soil Testing and Formulated Fertilization Program” (STFFP) have significant positive impact on TEFU; and natural disaster and fertilizer price have significant negative impact on TEFU.

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Section: Introductionmentioning

confidence: 99%

Technical Efficiency of Chemical Fertilizer Use and Its Influencing Factors in China’s Rice Production

Sun

2021

Sustainability

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“…Soil pH describes the threshold for physical and chemical activity. Nitrogen, phosphate, and potassium, describe the nutrients available to plants [22]. Fertilizer can be used as a soil enhancer, increasing microorganisms in the soil and supporting sustainable agricultural production [23].…”

Section: A Initial Soil Test Results Toss Compost Fertilizer and Comm...mentioning

confidence: 99%

Comparison of Applications of Various Organic and Inorganic Fertilizers on the Growth and Yield of Cayenne Pepper

Astika¹,

Arthanawa²,

Darmawan³

et al. 2022

Agr. J

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Cayenne pepper is one of the agricultural commodities that has high economic value and its demand continues to increase along with the development of the population. Efforts to increase the production and quality of various types of plants continue to be carried out, by utilizing various types of fertilizers. The purpose of this study was to determine the response of growth and yield of cayenne pepper using organic and inorganic fertilizers. This research was carried out at the Experimental Garden of the Local Waste Processing Site in Kusamba Village, Klungkung Regency, and the Laboratory of the Agrotechnology Study Program, Faculty of Agriculture, Warmadewa University, Denpasar from March to November 2021. The method used in this study was experimental, using a Randomized Block Design (RBD). ) with 1 factor and 4 replications. The variables observed were plant height, number of leaves, stem diameter, number of fruit, fruit weight per plant, and fruit weight per ha. The results showed that the application of various types of fertilizers can increase all observed variables. The best fertilizer for the growth and yield of cayenne pepper is NPK fertilizer.

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“…Loss of SOC indicates a degree of soil degradation, and negatively affects soil health, food production and exacerbates climate change (Smith et al, 2016). Soil degradation is becoming more prevalent in Africa due to intensive tillage systems, low inputs and poor soil management practices (Nair & Nair, 2019;Wulanningtyas et al, 2021). Agriculture management is characterised by lack of accurate and timeous methods to assess SOC.…”

Section: Introductionmentioning

confidence: 99%

“…The SOC pool is a large and most dynamic reservoir of carbon (C) in the global C cycle, having twice the amount of C in the biosphere and atmosphere combined (Lal, 2021;Meena et al, 2020;Wiesmeier et al, 2019). SOC is the main component of soil organic matter (SOM) and constitutes the greater nutrient-rich portion of the soil, and it supports key soil functions for the stabilization of soil structure, retention and release of plant nutrients (Nair & Nair, 2019;Sombrero & De Benito, 2010), and allows for water infiltration and retention (Scavo et al, 2022). SOC is crucial for soil fertility improvement by providing essential nutrients for plants, help maintain soil pH levels and increase the soil's ability to resist erosion (Cooper et al, 2021;Xu et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Estimating Soil Organic Carbon using Sentinel-2 data under Zero Tillage Agriculture: A Machine Learning Approach

Mango,

Narissara,

Som-ard

2024

Preprint

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Soil organic carbon (SOC) is the main component of soil organic matter (SOM) and constitutes the crucial ingredient of the soil. It supports key soil functions, stabilizes soil structure, aid in plant nutrients retention and release, and promote water infiltration and storage. Predicting SOC using Sentinel-2 images integrated with machine learning algorithms under zero tillage practice is inadequately documented for developing countries like Zimbabwe. The purpose of this study is to evaluate the integrated use of Sentinel-2 data together with machine learning (ML) algorithms for SOC estimation. The support vector machine (SVM), artificial neural network (ANN), and partial least square regression (PLSR) models were used with a cross-validation to estimate the SOC content based on 50 georeferenced calibration samples under a zero-tillage practice. The ANN model outperformed the other two models by delivering a coefficient of determination (R2) of between 55-60% of SOC variability and RMSE varies between 5.01-8.78%, whereas for the SVM, R2 varies between 0.53-0.57 and RMSE varies between 6.25-11.39%. The least estimates of SOC are provided by the PLSR algorithm (R2 = 0.44–0.49 and RMSE = 7.59-12.42% for the top 15cm depth SOC estimation. Results with RMSE, MAE and R2 for SVM, ANN and PLSR, show that the ANN model is able to capture SOC variability. Although the ANN algorithm provides more accurate SOC estimates than the SVM algorithm, the difference in accuracy is not significant. Results revealed a satisfactory agreement between the SOC and zero tillage practice (R2, coefficient of variation (CV), mean absolute error (MAE), and root mean square error (RMSE) using SVM, ANN and PLSR for the validation dataset using four predictor variables. The calibration results of SOC indicated that the mean SOC was 5.19% and the validation mean SOC was 5.02%. The calibration dataset had higher degree of variation (27.94%) around its mean compared to the validation dataset (24.30%). The accurate map results can be used as an important tool for informed decisions about soil health and productivity by the farmers, land managers and policy makers.

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Soil Fertility and Nutrient Management

Cited by 19 publications

References 22 publications

Technical Efficiency of Chemical Fertilizer Use and Its Influencing Factors in China’s Rice Production

Technical Efficiency of Chemical Fertilizer Use and Its Influencing Factors in China’s Rice Production

Comparison of Applications of Various Organic and Inorganic Fertilizers on the Growth and Yield of Cayenne Pepper

Estimating Soil Organic Carbon using Sentinel-2 data under Zero Tillage Agriculture: A Machine Learning Approach

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