Modeling the soybean growth in different amount of nitrogen, phosphorus and potassium using neural network
نویسندگان
چکیده
This paper proposed a simulation model of soybean growth which is effected by major nutrient factors, nitrogen, phosphorus and potassium. A feedforward neural network is used as a basis of the modelling. The combination of different percentage of nitrogen, phosphorus, potassium, time steps and the collected height data of the soybean are used as inputs. The model can predict the height at designated time intervals, whereby the result can be visualized with L-systems.
منابع مشابه
Identification of soybean circular RNAs in response to low nitrogen and phosphorus stress
Soybean, one of the most important sources of edible oil and protein in the world, is exposed to various environmental biotic and abiotic stresses. These stresses can negatively impact the quality and quantity of soybean production. This study aimed to identify genes that express circular RNAs in response to low phosphorus and nitrogen stresses in soybean roots. Soybean seeds were grown under d...
متن کاملThe Effect of Soil Amendments and Precipitation on the Amount of Soil Nutrients in Different Time Periods
Changes in nutrient concentrations of soil can specify optimal management of manure and prevent environmental and water resources pollution. The present study was conducted with the objective of changing macronutrients concentrations of Nitrogen, Phosphorus, and Potassium with amendments application of polyvinyl acetate, bean residual, and a combination of polyvinyl acetate + bean residual for ...
متن کاملEstimation of Phosphorus Reduction from Wastewater by Artificial Neural Network, Random Forest and M5P Model Tree Approaches
This study aims to examine the ability of free floating aquatic plants to remove phosphorus and to predict the reduction of phosphorus from rice mill wastewater using soft computing techniques. A mesocosm study was conducted at the mill premises under normal conditions, and reliable results were obtained. Four aquatic plants, namely water hyacinth, water lettuce, salvinia, and duckweed were use...
متن کاملEstimation of Phosphorus Reduction from Wastewater by Artificial Neural Network, Random Forest and M5P Model Tree Approaches
This study aims to examine the ability of free floating aquatic plants to remove phosphorus and to predict the reduction of phosphorus from rice mill wastewater using soft computing techniques. A mesocosm study was conducted at the mill premises under normal conditions, and reliable results were obtained. Four aquatic plants, namely water hyacinth, water lettuce, salvinia, and duckweed were use...
متن کاملDetermining the effect of plant species type on some soil properties in the mountain rangelands in Kakhk watershed
Abstract Background and objectives: Biological control of erosion in sloping lands and recognizing the effects of plant species, which are used for rangeland improvement, is the most effective and sustainable method for stabilizing and controlling soil fertility in rangeland.Variations of plants composition cause extensive changes in the soil so that in the short term return to the origina...
متن کامل