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"neural network" AND plant growth

Liang Han, Guijun Yang, Huayang Dai, Bo Xu, Hao Yang, Haikuan Feng, Zhenhai Li, Xiaodong Yang
Background: Above-ground biomass (AGB) is a basic agronomic parameter for field investigation and is frequently used to indicate crop growth status, the effects of agricultural management practices, and the ability to sequester carbon above and below ground. The conventional way to obtain AGB is to use destructive sampling methods that require manual harvesting of crops, weighing, and recording, which makes large-area, long-term measurements challenging and time consuming. However, with the diversity of platforms and sensors and the improvements in spatial and spectral resolution, remote sensing is now regarded as the best technical means for monitoring and estimating AGB over large areas...
2019: Plant Methods
C P Devatha, N Pavithra
Triclosan (TCS) is a well-known emerging contaminant got wide use in daily use products of domestic purpose, which provides the way to enter the ecological cycle, and is preferably detected in sewage treatment plants. In this study, TCS degrading bacteria (TDB) was isolated and identified from a wastewater treatment plant at the National Institute of Technology-Karnataka, Surathkal (NITK), India. The isolate was reported as Pseudomonas strain by performing 16S RNA Sequencing using BLAST analysis. Bacterial growth depends upon several environmental factors...
December 1, 2018: Journal of Environmental Management
Md Mehedi Hasan, Joshua P Chopin, Hamid Laga, Stanley J Miklavcic
Background: Field phenotyping by remote sensing has received increased interest in recent years with the possibility of achieving high-throughput analysis of crop fields. Along with the various technological developments, the application of machine learning methods for image analysis has enhanced the potential for quantitative assessment of a multitude of crop traits. For wheat breeding purposes, assessing the production of wheat spikes, as the grain-bearing organ, is a useful proxy measure of grain production...
2018: Plant Methods
Bin Yang, Yuehui Chen, Wei Zhang, Jiaguo Lv, Wenzheng Bao, De-Shuang Huang
Gene regulatory network (GRN) inference can understand the growth and development of animals and plants, and reveal the mystery of biology. Many computational approaches have been proposed to infer GRN. However, these inference approaches have hardly met the need of modeling, and the reducing redundancy methods based on individual information theory method have bad universality and stability. To overcome the limitations and shortcomings, this thesis proposes a novel algorithm, named HSCVFNT, to infer gene regulatory network with time-delayed regulations by utilizing a hybrid scoring method and complex-valued flexible neural network (CVFNT)...
October 15, 2018: International Journal of Molecular Sciences
Augusto Cesar Fonseca Saraiva, André Mesquita, Terezinha Ferreira de Oliveira, Rachel Ann Hauser-Davis
The aim of the present study consisted in evaluating the effects of CO2 enrichment on the growth and biometal/nutrient content and accumulation in Senna reticulata germinated under two different carbon dioxide concentrations: atmospheric (360 mg L-1 ) and elevated (720 mg L-1 ). Biometal/nutrient determinations were performed on three different plant portions (leaflets, stem and root) using flame atomic absorption spectrometry. In general, the biometal and nutrient stoichiometries in roots were increased, probably due to reduced transpiration, and consequent biometal accumulation...
December 2018: Journal of Trace Elements in Medicine and Biology
Sarah Taghavi Namin, Mohammad Esmaeilzadeh, Mohammad Najafi, Tim B Brown, Justin O Borevitz
Background: High resolution and high throughput genotype to phenotype studies in plants are underway to accelerate breeding of climate ready crops. In the recent years, deep learning techniques and in particular Convolutional Neural Networks (CNNs), Recurrent Neural Networks and Long-Short Term Memories (LSTMs), have shown great success in visual data recognition, classification, and sequence learning tasks. More recently, CNNs have been used for plant classification and phenotyping, using individual static images of the plants...
2018: Plant Methods
Shichao Jin, Yanjun Su, Shang Gao, Fangfang Wu, Tianyu Hu, Jin Liu, Wenkai Li, Dingchang Wang, Shaojiang Chen, Yuanxi Jiang, Shuxin Pang, Qinghua Guo
The rapid development of light detection and ranging (Lidar) provides a promising way to obtain three-dimensional (3D) phenotype traits with its high ability of recording accurate 3D laser points. Recently, Lidar has been widely used to obtain phenotype data in the greenhouse and field with along other sensors. Individual maize segmentation is the prerequisite for high throughput phenotype data extraction at individual crop or leaf level, which is still a huge challenge. Deep learning, a state-of-the-art machine learning method, has shown high performance in object detection, classification, and segmentation...
2018: Frontiers in Plant Science
Taewon Moon, Tae In Ahn, Jung Eek Son
In existing closed-loop soilless cultures, nutrient solutions are controlled by the electrical conductivity (EC) of the solution. However, the EC of nutrient solutions is affected by both growth environments and crop growth, so it is hard to predict the EC of nutrient solution. The objective of this study was to predict the EC of root-zone nutrient solutions in closed-loop soilless cultures using recurrent neural network (RNN). In a test greenhouse with sweet peppers ( Capsicum annuum L.), data were measured every 10 s from October 15 to December 31, 2014...
2018: Frontiers in Plant Science
Boštjan Murovec, Damjan Makuc, Sabina Kolbl Repinc, Zala Prevoršek, Domen Zavec, Robert Šket, Klemen Pečnik, Janez Plavec, Blaž Stres
In this study, nuclear magnetic resonance (1 H NMR) spectroscopic profiling was used to provide a more comprehensive view of microbial metabolites associated with poor reactor performance in a full-scale 4 MW mesophilic agricultural biogas plant under fully operational and also under inhibited conditions. Multivariate analyses were used to assess the significance of differences between reactors whereas artificial neural networks (ANN) were used to identify the key metabolites responsible for inhibition and their network of interaction...
September 15, 2018: Journal of Environmental Management
Zhu Lin Chen, Xue Feng Wang
Nitrogen is one of the most important elements for plant growth. Producers often use a lot of nitrogen fertilizer during plant growth process. However, excessive fertilizer often cause ground-water pollution. In this study, we proposed a nondestructive testing method for total nitrogen content in leaves of sandalwood (Santalum album) based on ST-PCA-BP neural network. The results showed that, due to the wide color range of L* a* b* color system and its robustness in illumination change, images obtained from the field which were converted from RGB to L* a* b* color system had a satisfying segmentation result...
May 2018: Ying Yong Sheng Tai Xue Bao, the Journal of Applied Ecology
Mohammad M Arab, Abbas Yadollahi, Hamed Ahmadi, Maliheh Eftekhari, Masoud Maleki
The efficiency of a hybrid systems method which combined artificial neural networks (ANNs) as a modeling tool and genetic algorithms (GAs) as an optimizing method for input variables used in ANN modeling was assessed. Hence, as a new technique, it was applied for the prediction and optimization of the plant hormones concentrations and combinations for in vitro proliferation of Garnem (G × N15) rootstock as a case study. Optimizing hormones combination was surveyed by modeling the effects of various concentrations of cytokinin-auxin, i...
2017: Frontiers in Plant Science
Hao Lu, Zhiguo Cao, Yang Xiao, Bohan Zhuang, Chunhua Shen
Background: Accurately counting maize tassels is important for monitoring the growth status of maize plants. This tedious task, however, is still mainly done by manual efforts. In the context of modern plant phenotyping, automating this task is required to meet the need of large-scale analysis of genotype and phenotype. In recent years, computer vision technologies have experienced a significant breakthrough due to the emergence of large-scale datasets and increased computational resources...
2017: Plant Methods
Yangyang Fan, Tao Wang, Zhengjun Qiu, Jiyu Peng, Chu Zhang, Yong He
Striped stem-borer (SSB) infestation is one of the most serious sources of damage to rice growth. A rapid and non-destructive method of early SSB detection is essential for rice-growth protection. In this study, hyperspectral imaging combined with chemometrics was used to detect early SSB infestation in rice and identify the degree of infestation (DI). Visible/near-infrared hyperspectral images (in the spectral range of 380 nm to 1030 nm) were taken of the healthy rice plants and infested rice plants by SSB for 2, 4, 6, 8 and 10 days...
October 27, 2017: Sensors
Muhammad Raziq Rahimi Kooh, Linda B L Lim, Lee-Hoon Lim, Owais Ahmed Malik
This study investigated the potential of Azolla pinnata (AP) in the removal of toxic methyl violet 2B (MV) dye wastewater using the phytoextraction approach with the inclusion of an Artificial Neural Network (ANN) modelling. Parameters examined included the effects of dye concentration, pH and plant dosage. The highest removal efficiency was 93% which was achieved at a plant dosage of 0.8 g (dye volume = 200 mL, initial pH = 6.0, initial dye concentration = 10 mg L-1 ). A significant decrease in relative frond number (RFN), a growth rate estimator, observed at a dye concentration of 20 mg L-1 MV indicated some toxicity, which coincided with the plant pigments studies where the chlorophyll a content was lower than the control...
April 16, 2018: International Journal of Phytoremediation
Mohammad M Arab, Abbas Yadollahi, Abdolali Shojaeiyan, Hamed Ahmadi
One of the major obstacles to the micropropagation of Prunus rootstocks has, up until now, been the lack of a suitable tissue culture medium. Therefore, reformulation of culture media or modification of the mineral content might be a breakthrough to improve in vitro multiplication of G × N15 (garnem). We found artificial neural network in combination of genetic algorithm (ANN-GA) as a very precise and powerful modeling system for optimizing the culture medium, So that modeling the effects of MS mineral salts ([Formula: see text], [Formula: see text], [Formula: see text], Ca(2+), K(+), [Formula: see text], Mg(2+), and Cl(-)) on in vitro multiplication parameters (the number of microshoots per explant, average length of microshoots, weight of calluses derived from the base of stem explants, and quality index of plantlets) of G × N15...
2016: Frontiers in Plant Science
Dana Luminița Sobariu, Daniela Ionela Tudorache Fertu, Mariana Diaconu, Lucian Vasile Pavel, Raluca-Maria Hlihor, Elena Niculina Drăgoi, Silvia Curteanu, Markus Lenz, Philippe François-Xavier Corvini, Maria Gavrilescu
Certain species of plants can benefit from synergistic effects with plant growth-promoting rhizobacteria (PGPR) that improve plant growth and metal accumulation, mitigating toxic effects on plants and increasing their tolerance to heavy metals. The application of PGPR as biofertilizers and atmospheric nitrogen fixators contributes considerably to the intensification of the phytoremediation process. In this paper, we have built a system consisting of rhizospheric Azotobacter microbial populations and Lepidium sativum plants, growing in solutions containing heavy metals in various concentrations...
October 25, 2017: New Biotechnology
Rengui Jiang, Jiancang Xie, Hailong He, Chun-Chao Kuo, Jiwei Zhu, Mingxiang Yang
As one of the most popular vegetation indices to monitor terrestrial vegetation productivity, Normalized Difference Vegetation Index (NDVI) has been widely used to study the plant growth and vegetation productivity around the world, especially the dynamic response of vegetation to climate change in terms of precipitation and temperature. Alberta is the most important agricultural and forestry province and with the best climatic observation systems in Canada. However, few studies pertaining to climate change and vegetation productivity are found...
September 2016: International Journal of Biometeorology
A Movafeghi, A R Khataee, Z Moradi, F Vafaei
Phytoremediation potential of the aquatic plant Spirodela polyrrhiza was examined for direct blue 129 (DB129) azo dye. The dye removal efficiency was optimized under the variable conditions of the operational parameters including removal time, initial dye concentration, pH, temperature and amount of plant. The study reflected the significantly enhanced dye removal efficiency of S. polyrrhiza by increasing the temperature, initial dye concentration and amount of plant. Intriguingly, artificial neural network (ANN) predicted the removal time as the most dominant parameter on DB129 removal efficiency...
2016: International Journal of Phytoremediation
Yun-Sheng Zhao, Xiu Liu, Fu-Ying Mao, Hong-Ling Tian, De-Guang Wan
OBJECTIVE: To establish an HPLC fingerprint to evaluate the quality of Polygalae Radix, root xylem, and those collected in different growth ages or harvest time. METHOD: Separation was performed at 30 °C on a Kromasil C18 column (4.6 mm x 250 mm, 5 μm); the mobile phases was acetonitrile and 0.05% H3PO4 water in the gradient elution; the flow rate was set at 1.0 mL · min(-1) and the detection wavelength at 314 nm; the quality discriminant analyses were accomplished by means of similarity analysis, cluster analysis, principal component analysis and neural network model...
October 2014: Zhongguo Zhong Yao za Zhi, Zhongguo Zhongyao Zazhi, China Journal of Chinese Materia Medica
Felix Lenk, Thomas Bley
The review presents a comprehensive overview on available solutions for the monitoring and modeling of various aspects of hairy root growth processes. Several online and offline measurement principles get explained exemplary and are being compared. It was found that no direct online measurement principle for hairy root biomass in submerged and solid-state culturing environment is available. However, certain indirect methods involving one or more measurement values have been developed for biomonitoring of hairy roots especially in bioreactors...
2015: Advances in Biochemical Engineering/biotechnology
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