scholarly journals Soil nutrient maps of Sub-Saharan Africa: assessment of soil nutrient content at 250 m spatial resolution using machine learning

2017 ◽  
Vol 109 (1) ◽  
pp. 77-102 ◽  
Author(s):  
Tomislav Hengl ◽  
Johan G. B. Leenaars ◽  
Keith D. Shepherd ◽  
Markus G. Walsh ◽  
Gerard B. M. Heuvelink ◽  
...  
Keyword(s):  
Machine Learning ◽  
Spatial Resolution ◽  
Soil Nutrient ◽  
Nutrient Content ◽  
Sub Saharan Africa ◽  
Soil Nutrient Content ◽  
Sub Saharan

FERTIGATION OF PRIMOCANE-FRUITING RASPBERRY – LEAF AND SOIL NUTRIENT CONTENT BETWEEN APPLICATIONS

2009 ◽  
pp. 341-348 ◽  
Author(s):  
K.S. Koumanov ◽  
I. Tsareva ◽  
K. Kolev ◽  
G. Kornov
Keyword(s):  
Soil Nutrient ◽  
Nutrient Content ◽  
Soil Nutrient Content

scholarly journals Estimation of Soil Nutrient Content Using Hyperspectral Data

Agriculture ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 1129
Author(s):  
Yiping Peng ◽  
Lu Wang ◽  
Li Zhao ◽  
Zhenhua Liu ◽  
Chenjie Lin ◽  
...  
Keyword(s):  
Least Squares ◽  
Soil Nutrients ◽  
Cross Validation ◽  
Regional Scale ◽  
Soil Nutrient ◽  
Nutrient Content ◽  
New Method ◽  
Accurate Estimation ◽  
Support Vector ◽  
Soil Nutrient Content

Soil nutrients play a vital role in plant growth and thus the rapid acquisition of soil nutrient content is of great significance for agricultural sustainable development. Hyperspectral remote-sensing techniques allow for the quick monitoring of soil nutrients. However, at present, obtaining accurate estimates proves to be difficult due to the weak spectral features of soil nutrients and the low accuracy of soil nutrient estimation models. This study proposed a new method to improve soil nutrient estimation. Firstly, for obtaining characteristic variables, we employed partial least squares regression (PLSR) fit degree to select an optimal screening algorithm from three algorithms (Pearson correlation coefficient, PCC; least absolute shrinkage and selection operator, LASSO; and gradient boosting decision tree, GBDT). Secondly, linear (multi-linear regression, MLR; ridge regression, RR) and nonlinear (support vector machine, SVM; and back propagation neural network with genetic algorithm optimization, GABP) algorithms with 10-fold cross-validation were implemented to determine the most accurate model for estimating soil total nitrogen (TN), total phosphorus (TP), and total potassium (TK) contents. Finally, the new method was used to map the soil TK content at a regional scale using the soil component spectral variables retrieved by the fully constrained least squares (FCLS) method based on an image from the HuanJing-1A Hyperspectral Imager (HJ-1A HSI) of the Conghua District of Guangzhou, China. The results identified the GBDT-GABP was observed as the most accurate estimation method of soil TN ( of 0.69, the root mean square error of cross-validation (RMSECV) of 0.35 g kg−1 and ratio of performance to interquartile range (RPIQ) of 2.03) and TP ( of 0.73, RMSECV of 0.30 g kg−1 and RPIQ = 2.10), and the LASSO-GABP proved to be optimal for soil TK estimations ( of 0.82, RMSECV of 3.39 g kg−1 and RPIQ = 3.57). Additionally, the highly accurate LASSO-GABP-estimated soil TK (R2 = 0.79) reveals the feasibility of the LASSO-GABP method to retrieve soil TK content at the regional scale.

scholarly journals Molecular Mechanisms and Biochemical Pathways for Micronutrient Acquisition and Storage in Legumes to Support Biofortification for Nutritional Security

2021 ◽  
Vol 12 ◽  
Author(s):  
Manish Roorkiwal ◽  
Sarita Pandey ◽  
Dil Thavarajah ◽  
R. Hemalatha ◽  
Rajeev K. Varshney
Keyword(s):  
Molecular Mechanisms ◽  
Food System ◽  
Significant Risk ◽  
Nutrient Deficiency ◽  
Nutrient Content ◽  
Sub Saharan Africa ◽  
Nutritional Security ◽  
Legume Crops ◽  
Sub Saharan ◽  
Poor Nutrition

The world faces a grave situation of nutrient deficiency as a consequence of increased uptake of calorie-rich food that threaten nutritional security. More than half the world’s population is affected by different forms of malnutrition. Unhealthy diets associated with poor nutrition carry a significant risk of developing non-communicable diseases, leading to a high mortality rate. Although considerable efforts have been made in agriculture to increase nutrient content in cereals, the successes are insufficient. The number of people affected by different forms of malnutrition has not decreased much in the recent past. While legumes are an integral part of the food system and widely grown in sub-Saharan Africa and South Asia, only limited efforts have been made to increase their nutrient content in these regions. Genetic variation for a majority of nutritional traits that ensure nutritional security in adverse conditions exists in the germplasm pool of legume crops. This diversity can be utilized by selective breeding for increased nutrients in seeds. The targeted identification of precise factors related to nutritional traits and their utilization in a breeding program can help mitigate malnutrition. The principal objective of this review is to present the molecular mechanisms of nutrient acquisition, transport and metabolism to support a biofortification strategy in legume crops to contribute to addressing malnutrition.

scholarly journals Effects of Two Trichoderma Strains on Plant Growth, Rhizosphere Soil Nutrients, and Fungal Community of Pinus sylvestris var. mongolica Annual Seedlings

Forests ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 758 ◽  
Author(s):  
Saiyaremu Halifu ◽  
Xun Deng ◽  
Xiaoshuang Song ◽  
Ruiqing Song
Keyword(s):  
Enzyme Activity ◽  
Community Structure ◽  
Plant Growth ◽  
Soil Nutrients ◽  
Fungal Community ◽  
Rhizosphere Soil ◽  
Soil Nutrient ◽  
Nutrient Content ◽  
Root Structure ◽  
Soil Nutrient Content

Trichoderma spp. are proposed as major plant growth-promoting fungi that widely exist in the natural environment. These strains have the abilities of rapid growth and reproduction and efficient transformation of soil nutrients. Moreover, they can change the plant rhizosphere soil environment and promote plant growth. Pinus sylvestris var. mongolica has the characteristics of strong drought resistance and fast growth and plays an important role in ecological construction and environmental restoration. The effects on the growth of annual seedlings, root structure, rhizosphere soil nutrients, enzyme activity, and fungal community structure of P. sylvestris var. mongolica were studied after inoculation with Trichoderma harzianum E15 and Trichoderma virens ZT05, separately. The results showed that after inoculation with T. harzianum E15 and T. virens ZT05, seedling biomass, root structure index, soil nutrients, and soil enzyme activity were significantly increased compared with the control (p < 0.05). There were significant differences in the effects of T. harzianum E15 and T. virens ZT05 inoculation on the growth and rhizosphere soil nutrient of P. sylvestris var. mongolica (p < 0.05). For the E15 treatment, the seedling height, ground diameter, and total biomass of seedlings were higher than that those of the ZT05 treatment, and the rhizosphere soil nutrient content and enzyme activity of the ZT05 treatment were higher than that of the E15 treatment. The results of alpha and beta diversity analyses showed that the fungi community structure of rhizosphere soil was significantly different (p < 0.05) among the three treatments (inoculated with T. harzianum E15, T. virens ZT05, and not inoculated with Trichoderma). Overall, Trichoderma inoculation was correlated with the change of rhizosphere soil nutrient content.

scholarly journals Soil Nutrient Content Influences the Abundance of Soil Microbes but Not Plant Biomass at the Small-Scale

PLoS ONE ◽  
2014 ◽  
Vol 9 (3) ◽  
pp. e91998 ◽  
Author(s):  
Kadri Koorem ◽  
Antonio Gazol ◽  
Maarja Öpik ◽  
Mari Moora ◽  
Ülle Saks ◽  
...  
Keyword(s):  
Soil Microbes ◽  
Plant Biomass ◽  
Soil Nutrient ◽  
Nutrient Content ◽  
Small Scale ◽  
Soil Nutrient Content

AGRO SENSORS

2015 ◽  
Vol 3 (4) ◽  
pp. 325-327
Author(s):  
M.R Suja Barathi
Keyword(s):  
Soil Nutrient ◽  
Nutrient Content ◽  
Feedback Mechanism ◽  
Reference Voltage ◽  
Common Input ◽  
Current Output ◽  
Soil Nutrient Content ◽  
The Common ◽  
Effect Transistor ◽  
Resistance Value

Soil nutrient is detected by the use of ISFETs and the corresponding current is obtained from it according to the variation in concentration of the nutrient in soil and their pH. The use of metal oxide coated semiconductors for gas detection is high nowadays. The Ion sensitive field effect transistor has the electrode. This on reaction with the analyst changes its resistance value and corresponding signals are generated and the transducer unit in the sensor gives the varying current output. This could be then processed that is converted to voltage, amplified and then given to a window detector where in the voltage obtained from the sensor could be tested for it be in between two reference voltage levels and these reference voltage levels represent the level of nutrients in the soil either it is deficient, in surplus or in sufficient amounts. This could be used to make the LEDs glow. It proves to be an easy way of observing the soil nutrient content even by an illiterate. The checking of soil nutrient content could be automated and made periodic by the use of microcontroller, the feedback mechanism involving the soil’s nutrient content value as the common input and the ideal or required value as the reference input.

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