scholarly journals Smart Agriculture to Measure Humidity, Temperature, Moisture, Ph. and Nutrient Values of the Soil using IoT

2020 ◽  
Vol 9 (5) ◽  
pp. 394-398
Keyword(s):  
Moisture Content ◽  
Soil Nutrients ◽  
Ph Value ◽  
Ph Sensor ◽  
Soil Nutrient ◽  
Nutrient Content ◽  
Nutrient Level ◽  
Embedded Devices ◽  
Smart Agriculture ◽  
Use Of Internet

Smart Agriculture now-a-days reducing various problems in farming. Farmers get required information and relative data to monitor the plants growth by the use of “INTERNET OF THINGS (IOT)”, which connects the different sensors, actuators and other embedded devices. To provide quality crops based on soil nutrient level and its moisture content along with Ph. factor, also been maintained. Hence, in this project all those parameters are detected and controlled with the help of micro controller. Humidity sensor to detect the moisture content, where colour sensor is used to determine the percentage of soil nutrients (N2 , P4 &K). It will analyse soil nutrient content present in soil at real time and Ph. sensor is used to determine the Ph value of the soil. Monitrring of these it provides the proper fertility to the soil depending upon the soil nutrients. GSM is used to display the information to the farmers. Thus it reduces the growing of husk in terms of wastage and thereby getting good quality and healthy crops.

scholarly journals A Research on IOT Based Smart Automation Irrigation System

2021 ◽  
Vol 9 (VII) ◽  
pp. 2914-2917
Author(s):  
Pooja Jadhav
Keyword(s):  
Soil Moisture ◽  
Real Time ◽  
Ph Value ◽  
Irrigation System ◽  
Ph Sensor ◽  
Soil Nutrient ◽  
Nutrient Content ◽  
Nutrient Level ◽  
Moisture Sensor ◽  
Main Requirement

India is an agricultural country. 70% of people do this. The main requirement within the agriculture field is water and manpower. Nowadays the foremost problem lies in agriculture is water scarcity, manpower, funds, etc. To overcome these problems we've to develop an automation irrigation system using IoT. This technology is employed for creating systems automated using sensors like DHT11, Soil Moisture sensor, some hardware parts, and software. The PH sensor is additionally wont to analyze soil nutrient content present within the soil in real-time and therefore the PH sensor is employed to work out the Ph value of the soil. Monitoring of those provides the right fertility to the soil depending upon the soil nutrients. To provide quality crops supported temperature, humidity, soil moisture, and its nutrient level content and Ph. factor, it has also been maintained. The real-time result will be generated. The generated results PDF are going to be sent to the person through email or web SMS. The overall cost required should be low enough in order that every one can afford it.

scholarly journals A Smart Agriculture System Based On Intel Galileo For Detection Of Cultivable Crops And Implemented On Soil Nutrients

2019 ◽  
Vol 8 (9) ◽  
pp. 98-102
Keyword(s):  
Soil Nutrients ◽  
Soil Nutrient ◽  
Nutrient Content ◽  
Ph Sensors ◽  
Food Grains ◽  
The World ◽  
Current Scenario ◽  
Soil Nutrient Content ◽  
Smart Agriculture ◽  
Intel Galileo

The world is in need of food, water, Shelter and without any of these there is no possibility to live. Agriculture is backbone of our nation which indeed supplies food for the entire people but the producers of food are facing many problems like moisture content, fertility of soil which affects the farming. Because of this reason cultivation and production of food grains are decreased. Current scenario is that the farmers need to go research center to test the fertility content of soil and to predict kind of plants can be cultivable in that land. In this paper perfect cultivable plants can be detected properly without approaching soil research centers which consumes more money as well time. By the application of pH sensors the fertility of soil can be measured. By measuring the pH soil nutrient content can be measured and so the suitable cultivable crop for different soil varieties can be predicted. In this view to give a healthful support to farmers, soil nutrients are analyzed and report the requirement using advanced sensors.

scholarly journals Distribution Characteristics and Seasonal Variation of Soil Nutrients in the Mun River Basin, Thailand

2018 ◽  
Vol 15 (9) ◽  
pp. 1818 ◽  
Author(s):  
Zhonghe Zhao ◽  
Gaohuan Liu ◽  
Qingsheng Liu ◽  
Chong Huang ◽  
He Li ◽  
...  
Keyword(s):  
Seasonal Variation ◽  
River Basin ◽  
Soil Nutrients ◽  
Rainy Season ◽  
Ph Value ◽  
Soil Nutrient ◽  
Nutrient Content ◽  
Dry Season ◽  
Strong Variation ◽  
Geostatistical Methods

Based on soil sampling data from the dry season and the rainy season, the spatial heterogeneity and spatial pattern of soil nutrients in the Mun River Basin, Thailand, were studied and the seasonal variation in soil nutrients was analyzed using classical statistical methods and geostatistical methods. The soil nutrient content in the Mun Basin showed moderate and strong variations, and the descending order of soil variability was as follows: available phosphorous (AP) > electric conductivity (EC) > soil organic matter (SOM) > total nitrogen (TN) > pH value in the dry season, with AP showing strong variation, and EC > AP > SOM > TN > pH in the rainy season, with EC showing strong variation. Different soil nutrients and different soil properties had different spatial variation characteristics, and their corresponding best-fitting models were also different. Based on the nugget (C0), sill (C0 + C), and range (A), spatial analysis was performed for the soil nutrients, pH, and EC in the dry season and in the rainy season. Analysis based on kriging spatial interpolation data showed that pH, SOM, TN, and EC had convex or concave distributions, whereas AP had a patchy distribution. Terrain, vegetation, and human disturbance are the main factors that contribute to the differences in the soil nutrient pattern of the Mun River Basin.

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.

Study on the Relationship between Soil Nutrient and Yield Analysis Based on Bivariate Correlation between

2014 ◽  
Vol 998-999 ◽  
pp. 1466-1469
Author(s):  
Li Ying Cao ◽  
Xiao Xian Zhang ◽  
Yue Ling Zhao ◽  
Gui Fen Chen
Keyword(s):  
Soil Nutrient ◽  
Nutrient Content ◽  
Maize Yield ◽  
Nutrient Level ◽  
Corn Yield ◽  
Yield Analysis ◽  
Bivariate Correlation ◽  
Plot Yield ◽  
The Relationship ◽  
Nitrogen Phosphorus

Soil nutrient level is an important factor affecting the yield of corn, to find out the effect of nitrogen, phosphorus, potassium on maize yield, analysis of bivariate correlation in SPSS based on the relationship between nutrient content, nitrogen, phosphorus, potassium in the plot and each plot yield directly was analyzed, the experimental results show that it doesn't matter: P, K and the yield of corn, corn yield and nitrogen related.

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.

Effect of density of Tephrosia candida stands on soil characteristics

2016 ◽  
Author(s):  
Zhiyang Lie ◽  
Zhuomin Wang ◽  
Li Xue
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Ph Value ◽  
Soil Nutrient ◽  
Stand Density ◽  
Nutrient Content ◽  
Total N ◽  
One Year ◽  
Tephrosia Candida ◽  
Total P

With one-year-old Tephrosia candida trees as experimental material, influence of stand density on soil nutrient content and enzyme activity was studied. The results showed that density had little influenced on pH value in 2, 4 and 8 trees m2 stands. The contents of soil organic matter, effective nitrogen and effective phosphorus significantly increased in 2 trees m2 stands. The contents of soil organic matter and effective nitrogen significantly increased, whereas total N, total P, total K, effective N, effective P and effective K significantly decreased in 4 trees/m2 stand. Soil organic matter and nutrients except for total P significantly decreased in 8 trees m2 stand. Among the three density stands, the activities of urease, catalase and phosphatase were the lowest in 8 trees m2 stand.

scholarly journals Germplasm Screening of Green Manure Rapeseed through the Effects of Short-Term Decomposition on Soil Nutrients and Microorganisms

Agriculture ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 1219
Author(s):  
Xiaodan Wang ◽  
Hua Ma ◽  
Chunyun Guan ◽  
Mei Guan
Keyword(s):  
Soil Nutrients ◽  
Green Manure ◽  
Soil Microorganisms ◽  
Soil Nutrient ◽  
Principal Component ◽  
Nutrient Content ◽  
Germplasm Screening ◽  
Significant Difference ◽  
Soil Nutrient Content ◽  
Phosphorus And Potassium

The rapidly emerging fertilizer rapeseed used as green manure has wide applications for use. However, there have been few studies on its decomposition and effects on soil nutrients and microorganisms after its decay. In this study, 12 rapeseed lines to be screened were decomposed through a randomized block field design with two green-manure-specific varieties as the controls. The contents of nitrogen, phosphorus, and potassium from the plants, soil nutrients, and microbial changes after degradation were measured. There were substantial differences in the rates of decomposition and cumulative release of nutrients among the different lines after 30 days of rolling. The contents of phosphorus and potassium in the soil were 1.23–2.03 and 3.93–6.32 times those before decomposition, respectively. In addition, there was a significant difference in the relative content of soil microorganisms at the phylum level after the decomposition of different species of rapeseeds. Most of the top 20 bacterial groups significantly correlated with the characteristics of plant decomposition and soil nutrient content, including Proteobacteria, Actinomycetes, Armatimonadetes, Rokubacteria, and Planctomycetes. A principal component analysis showed that the soil microorganisms and nutrients are the leading factors that enable the evaluation of the decomposing characteristics of green manure rapeseed. Numbers 5 (purple leaf mustard) and 8 (Xiafang self-seeding) were more effective than two controls, which can be used as excellent types of germplasm to promote the breeding of green manure rapeseed.

scholarly journals IoT Enabled Soil Testing

2018 ◽  
Vol 7 (S1) ◽  
pp. 54-57
Author(s):  
P. Sindhu ◽  
G. Indirani
Keyword(s):  
Plant Growth ◽  
Moisture Content ◽  
Soil Fertility ◽  
Soil Nutrients ◽  
Mobile Application ◽  
Crop Production ◽  
Ph Value ◽  
Vital Role ◽  
Soil Testing

Agriculture is the main occupation of our country and it plays a vital role in our country. Using too much of fertilizers may lead to the inferior quality of the crop production. So the measurement of soil nutrients is greatly required for better plant growth. Determining the amount of nutrients in the soil is the key function. pH value is also one of the most important and informative soil parameter to detect the soil fertility and it is measured to identify the soil fertility. In the proposed system, it determines the crops which are suitable for the particular soil type. It will analyze moisture content, temperature and humidity in soil at real time and it will also suggest the crops based on determined PH of soil. This system is proposed to help the farmers to increase the production and the suggestions are made through the mobile application.

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