Intelligent system for leaf disease detection using capsule networks for horticulture

2021 ◽  
pp. 1-17
Author(s):  
B. Janakiramaiah ◽  
G. Kalyani ◽  
L.V. Narasimha Prasad ◽  
A. Karuna ◽  
M. Krishna

Horticulture crops take a crucial part of the Indian economy by creating employment, supplying raw materials to different food processing industries. Mangoes are one of the major crops in horticulture. General Infections in Mango trees are common by various climatic and fungal infections, which became a cause for reducing the quality and quantity of the mangos. The most common diseases with bacterial infection are anthracnose and Powdery Mildew. In recent years, it has been perceived that different variants of deep learning architectures are proposed for detecting and classifying the problems in the agricultural domain. The Convolutional Neural Network (CNN) based architectures have performed amazingly well for disease detection in plants but at the same time lacks rotational or spatial invariance. A relatively new neural organization called Capsule Network (CapsNet) addresses these limitations of CNN architectures. Hence, in this work, a variant of CapsNet called Multilevel CapsNet is introduced to characterize the mango leaves tainted by the anthracnose and powdery mildew diseases. The proposed architecture of this work is validated on a dataset of mango leaves collected in the natural environment. The dataset comprises both healthy and contaminated leaf pictures. The test results approved the undeniable level of exactness of the proposed framework for the characterization of mango leaf diseases with an accuracy of 98.5%. The outcomes conceive the higher-order precision of the proposed Multi-level CapsNet model when contrasted with the other classification algorithms such as Support Vector Machine (SVM) and CNNs.

Foods ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 1411
Author(s):  
José Luis P. Calle ◽  
Marta Ferreiro-González ◽  
Ana Ruiz-Rodríguez ◽  
Gerardo F. Barbero ◽  
José Á. Álvarez ◽  
...  

Sherry wine vinegar is a Spanish gourmet product under Protected Designation of Origin (PDO). Before a vinegar can be labeled as Sherry vinegar, the product must meet certain requirements as established by its PDO, which, in this case, means that it has been produced following the traditional solera and criadera ageing system. The quality of the vinegar is determined by many factors such as the raw material, the acetification process or the aging system. For this reason, mainly producers, but also consumers, would benefit from the employment of effective analytical tools that allow precisely determining the origin and quality of vinegar. In the present study, a total of 48 Sherry vinegar samples manufactured from three different starting wines (Palomino Fino, Moscatel, and Pedro Ximénez wine) were analyzed by Fourier-transform infrared (FT-IR) spectroscopy. The spectroscopic data were combined with unsupervised exploratory techniques such as hierarchical cluster analysis (HCA) and principal component analysis (PCA), as well as other nonparametric supervised techniques, namely, support vector machine (SVM) and random forest (RF), for the characterization of the samples. The HCA and PCA results present a clear grouping trend of the vinegar samples according to their raw materials. SVM in combination with leave-one-out cross-validation (LOOCV) successfully classified 100% of the samples, according to the type of wine used for their production. The RF method allowed selecting the most important variables to develop the characteristic fingerprint (“spectralprint”) of the vinegar samples according to their starting wine. Furthermore, the RF model reached 100% accuracy for both LOOCV and out-of-bag (OOB) sets.


2019 ◽  
Vol 1 (3) ◽  
pp. 434-452 ◽  
Author(s):  
Chang ◽  
Mahmud ◽  
Shin ◽  
Nguyen-Quang ◽  
Price ◽  
...  

Strawberry is an important fruit crop in Canada but powdery mildew (PM) results in about 30–70% yield loss. Detection of PM through an image texture-based system is beneficial, as it identifies the symptoms at an earlier stage and reduces labour intensive manual monitoring of crop fields. This paper presents an image texture-based disease detection algorithm using supervised classifiers. Three sites were selected to collect the leaf image data in Great Village, Nova Scotia, Canada. Images were taken under an artificial cloud condition with a Digital Single Lens Reflex (DSLR) camera as red-green-blue (RGB) raw data throughout 2017–2018 summer. Three supervised classifiers, including artificial neural networks (ANN), support vector machine (SVM), and k-nearest neighbors (kNN) were evaluated for disease detection. A total of 40 textural features were extracted using a colour co-occurrence matrix (CCM). The collected feature data were normalized, then used for training and internal, external and cross-validations of developed classifiers. Results of this study revealed that the highest overall classification accuracy was 93.81% using the ANN classifier and lowest overall accuracy was 78.80% using the kNN classifier. Results identified the ANN classifier disease detection having a lower Root Mean Square Error (RMSE) = 0.004 and Mean Absolute Error (MAE) = 0.003 values with 99.99% of accuracy during internal validation and 87.41%, 88.95% and 95.04% of accuracies during external validations with three different fields. Overall results demonstrated that an image texture-based ANN classifier was able to classify PM disease more accurately at early stages of disease development.


2009 ◽  
Vol 35 (5) ◽  
pp. 786-794
Author(s):  
N PUDAKE Ramesh ◽  
Ming-Ming XIN ◽  
Yu-Jing YIN ◽  
Chao-Jie XIE ◽  
Zhong-Fu NI ◽  
...  

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3564
Author(s):  
Arnas Majumder ◽  
Laura Canale ◽  
Costantino Carlo Mastino ◽  
Antonio Pacitto ◽  
Andrea Frattolillo ◽  
...  

The building sector is known to have a significant environmental impact, considering that it is the largest contributor to global greenhouse gas emissions of around 36% and is also responsible for about 40% of global energy consumption. Of this, about 50% takes place during the building operational phase, while around 10–20% is consumed in materials manufacturing, transport and building construction, maintenance, and demolition. Increasing the necessity of reducing the environmental impact of buildings has led to enhancing not only the thermal performances of building materials, but also the environmental sustainability of their production chains and waste prevention. As a consequence, novel thermo-insulating building materials or products have been developed by using both locally produced natural and waste/recycled materials that are able to provide good thermal performances while also having a lower environmental impact. In this context, the aim of this work is to provide a detailed analysis for the thermal characterization of recycled materials for building insulation. To this end, the thermal behavior of different materials representing industrial residual or wastes collected or recycled using Sardinian zero-km locally available raw materials was investigated, namely: (1) plasters with recycled materials; (2) plasters with natural fibers; and (3) building insulation materials with natural fibers. Results indicate that the investigated materials were able to improve not only the energy performances but also the environmental comfort in both new and in existing buildings. In particular, plasters and mortars with recycled materials and with natural fibers showed, respectively, values of thermal conductivity (at 20 °C) lower than 0.475 and 0.272 W/(m⋅K), while that of building materials with natural fibers was always lower than 0.162 W/(m⋅K) with lower values for compounds with recycled materials (0.107 W/(m⋅K)). Further developments are underway to analyze the mechanical properties of these materials.


2021 ◽  
Vol 42 (15) ◽  
pp. 5680-5697
Author(s):  
Pâmela A. Pithan ◽  
Jorge R. Ducati ◽  
Lucas R. Garrido ◽  
Diniz C. Arruda ◽  
Adriane B. Thum ◽  
...  

Geosciences ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 36
Author(s):  
Vayia Xanthopoulou ◽  
Ioannis Iliopoulos ◽  
Ioannis Liritzis

The present study deals with the characterization of a ceramic assemblage from the Late Mycenaean (Late Helladic III) settlement of Kastrouli, at Desfina near Delphi, Central Greece using various analytical techniques. Kastrouli is located in a strategic position supervising the Mesokampos plateau and the entire peninsula and is related to other nearby coeval settlements. In total 40 ceramic sherds and 8 clay raw materials were analyzed through mineralogical, petrographic and microstructural techniques. Experimental briquettes (DS) made from clayey raw materials collected in the vicinity of Kastrouli, were fired under temperatures (900 and 1050 °C) in oxidizing conditions for comparison with the ancient ceramics. The petrographic analysis performed on thin sections prepared from the sherds has permitted the identification of six main fabric groups and a couple of loners. The aplastic inclusions recognized in all fabric groups but one confirmed the local provenance since they are related to the local geology. Fresh fractures of representative sherds were further examined under a scanning electron microscope (SEM/EDS) helping us to classify them into calcareous (CaO > 6%) and non-calcareous (CaO < 6%) samples (low and high calcium was noted in earlier pXRF data). Here, the ceramic sherds with broad calcium separation are explored on a one-to-one comparison on the basis of detailed mineralogical microstructure. Moreover, their microstructure was studied, aiming to estimate their vitrification stage. The mineralogy of all studied samples was determined by means of X-ray powder diffraction (XRPD), permitting us to test the validity of the firing temperatures revealed by the SEM analysis. The results obtained through the various analytical techniques employed are jointly assessed in order to reveal potters’ technological choices.


Cosmetics ◽  
2021 ◽  
Vol 8 (3) ◽  
pp. 62
Author(s):  
Giovanni Tafuro ◽  
Alessia Costantini ◽  
Giovanni Baratto ◽  
Stefano Francescato ◽  
Laura Busata ◽  
...  

As public attention on sustainability is increasing, the use of polysaccharides as rheological modifiers in skin-care products is becoming the first choice. Polysaccharide associations can be used to increase the spreading properties of products and to optimize their sensorial profile. Since the choice of natural raw materials for cosmetics is wide, instrumental methodologies are useful for formulators to easily characterize the materials and to create mixtures with specific applicative properties. In this work, we performed rheological and texture analyses on samples formulated with binary and ternary associations of polysaccharides to investigate their structural and mechanical features as a function of the concentration ratios. The rheological measurements were conducted under continuous and oscillatory flow conditions using a rotational rheometer. An immersion/de-immersion test conducted with a texture analyzer allowed us to measure some textural parameters. Sclerotium gum and iota-carrageenan imparted high viscosity, elasticity, and firmness in the system; carob gum and pectin influenced the viscoelastic properties and determined high adhesiveness and cohesiveness. The results indicated that these natural polymers combined in appropriate ratios can provide a wide range of different textures and that the use of these two complementary techniques represents a valid pre-screening tool for the formulation of green products.


Materials ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3079
Author(s):  
Beata Jaworska ◽  
Dominika Stańczak ◽  
Joanna Tarańska ◽  
Jerzy Jaworski

The generation of energy for the needs of the population is currently a problem. In consideration of that, the biomass combustion process has started to be implemented as a new source of energy. The dynamic increase in the use of biomass for energy generation also resulted in the formation of waste in the form of fly ash. This paper presents an efficient way to manage this troublesome material in the polymer–cement composites (PCC), which have investigated to a lesser extent. The research outlined in this article consists of the characterization of biomass fly ash (BFA) as well as PCC containing this waste. The characteristics of PCC with BFA after 3, 7, 14, and 28 days of curing were analyzed. Our main findings are that biomass fly ash is suitable as a mineral additive in polymer–cement composites. The most interesting result is that the addition of biomass fly ash did not affect the rheological properties of the polymer–cement mortars, but it especially influenced its compressive strength. Most importantly, our findings can help prevent this byproduct from being placed in landfills, prevent the mining of new raw materials, and promote the manufacture of durable building materials.


2019 ◽  
Vol 323 (2) ◽  
pp. 861-874
Author(s):  
Predrag Kuzmanović ◽  
Nataša Todorović ◽  
Jovana Nikolov ◽  
Jovana Knežević ◽  
Bojan Miljević

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