scholarly journals Reliable Deep Learning Plant Leaf Disease Classification Based on Light-Chroma Separated Branches

2021 ◽  
Author(s):  
Joao Paulo Schwarz Schuler ◽  
Santiago Romani ◽  
Mohamed Abdel-Nasser ◽  
Hatem Rashwan ◽  
Domenec Puig
Keyword(s):  
Low Frequency ◽  
Plant Diseases ◽  
Disease Classification ◽  
Plant Leaf ◽  
Food And Agriculture ◽  
Food And Agriculture Organization ◽  
Rgb Images ◽  
Cie Lab ◽  
Salt And Pepper ◽  
Classification Reliability

The Food and Agriculture Organization (FAO) estimated that plant diseases cost the world economy $220 billion in 2019. In this paper, we propose a lightweight Deep Convolutional Neural Network (DCNN) for automatic and reliable plant leaf diseases classification. The proposed method starts by converting input images of plant leaves from RGB to CIE LAB coordinates. Then, L and AB channels go into separate branches along with the first three layers of a modified Inception V3 architecture. This approach saves from 1/3 to 1/2 of the parameters in the separated branches. It also provides better classification reliability when perturbing the original RGB images with several types of noise (salt and pepper, blurring, motion blurring and occlusions). These types of noise simulate common image variability found in the natural environment. We hypothesize that the filters in the AB branch provide better resistance to these types of variability due to their relatively low frequency in the image-space domain.

scholarly journals Analysis on Digital Image Processing for Plant Health Monitoring

2021 ◽  
pp. 5-8
Author(s):  
Alina Granwehr ◽  
Verena Hofer
Keyword(s):  
Image Processing ◽  
Health Monitoring ◽  
Food Production ◽  
Black Spot ◽  
Plant Diseases ◽  
Pests And Diseases ◽  
Food And Agriculture ◽  
Food And Agriculture Organization ◽  
New Research ◽  
Common Plant

The country's ability to become self-sufficient in food production is becoming increasingly important. Agriculture is the primary occupation of a large portion of the population in equatorial countries like India, where the climate is ideal for the spread of plants. Pests and diseases are in control of about 25% of crop loss, according to a recent study released by the Food and Agriculture Organization. Black spot, leaf spot, rust, mildew, and botrytis blight are the most common plant diseases. Deep learning is a relatively new research technique for image processing and pattern recognition that has been proven to be highly productive in detection of plant leaf diseases.

scholarly journals Review on Convolutional Neural Network (CNN) Applied to Plant Leaf Disease Classification

Agriculture ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 707
Author(s):  
Jinzhu Lu ◽  
Lijuan Tan ◽  
Huanyu Jiang
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Plant Disease ◽  
Plant Diseases ◽  
Disease Classification ◽  
Classification Methods ◽  
Widespread Application ◽  
Plant Leaf ◽  
Leaf Disease ◽  
Traditional Classification

Crop production can be greatly reduced due to various diseases, which seriously endangers food security. Thus, detecting plant diseases accurately is necessary and urgent. Traditional classification methods, such as naked-eye observation and laboratory tests, have many limitations, such as being time consuming and subjective. Currently, deep learning (DL) methods, especially those based on convolutional neural network (CNN), have gained widespread application in plant disease classification. They have solved or partially solved the problems of traditional classification methods and represent state-of-the-art technology in this field. In this work, we reviewed the latest CNN networks pertinent to plant leaf disease classification. We summarized DL principles involved in plant disease classification. Additionally, we summarized the main problems and corresponding solutions of CNN used for plant disease classification. Furthermore, we discussed the future development direction in plant disease classification.

Food waste and dynamic complex systems: The case of Peru and a solution model proposal Part 1: Peruvian Anchoveta (Engraulis ringens)

2020 ◽  
Author(s):  
Carlos A Almenara
Keyword(s):  
United Nations ◽  
Complex Systems ◽  
Revenue Management ◽  
Food Waste ◽  
Intelligent Systems ◽  
Solution Model ◽  
Food And Agriculture ◽  
Food And Agriculture Organization ◽  
Engraulis Ringens ◽  
The United Nations

[THE MANUSCRIPT IS A DRAFT] According to the Food and Agriculture Organization of the United Nations (FAO, 2020), food waste and losses comprises nearly 1.3 billion tonnes every year, which equates to around US$ 990 billion worldwide. Ironically, over 820 million people do not have enough food to eat (FAO, 2020). This gap production-consumption puts in evidence the need to reformulate certain practices such as the controversial monocropping (i.e., growing a single crop on the same land on a yearly basis), as well as to improve others such as revenue management through intelligent systems. In this first part of a series of articles, the focus is on the Peruvian anchoveta fish (Engraulis ringens).

To the Empire and Beyond

2018 ◽  
Author(s):  
Gregory A. Barton
Keyword(s):  
Second World War ◽  
World War ◽  
Chemical Fertilizers ◽  
Basic Principles ◽  
Food And Agriculture ◽  
Food And Agriculture Organization ◽  
Organic Farmers ◽  
Southern Rhodesia ◽  
The Government ◽  
Second World

This chapter traces the expansion of industrial agricultural methods after the Second World War. Western governments and the Food and Agriculture Organization pushed for increased use of chemical fertilizers to aid development and resist Soviet encroachment. Meanwhile small groups of organic farmers and gardeners adopted Howard’s methods in the Anglo-sphere and elsewhere in the world. European movements paralleled these efforts and absorbed the basic principles of the Indore Method. British parliament debated the merits of organic farming, but Howard failed to persuade the government to adopt his policies. Southern Rhodesia, however, did implement his ideas in law. Desiccation theory aided his attempts in South Africa and elsewhere, and Louise Howard, after Albert’s death, kept alive a wide network of activists with her publications.

scholarly journals Ensuring Agricultural Sustainability through Remote Sensing in the Era of Agriculture 5.0

2021 ◽  
Vol 11 (13) ◽  
pp. 5911
Author(s):  
Vanesa Martos ◽  
Ali Ahmad ◽  
Pedro Cartujo ◽  
Javier Ordoñez
Keyword(s):  
Remote Sensing ◽  
Sustainable Agriculture ◽  
Information Acquisition ◽  
Industrial Revolution ◽  
Structural Parameters ◽  
Special Focus ◽  
World Population ◽  
Food And Agriculture ◽  
Food And Agriculture Organization ◽  
Zero Hunger

Timely and reliable information about crop management, production, and yield is considered of great utility by stakeholders (e.g., national and international authorities, farmers, commercial units, etc.) to ensure food safety and security. By 2050, according to Food and Agriculture Organization (FAO) estimates, around 70% more production of agricultural products will be needed to fulfil the demands of the world population. Likewise, to meet the Sustainable Development Goals (SDGs), especially the second goal of “zero hunger”, potential technologies like remote sensing (RS) need to be efficiently integrated into agriculture. The application of RS is indispensable today for a highly productive and sustainable agriculture. Therefore, the present study draws a general overview of RS technology with a special focus on the principal platforms of this technology, i.e., satellites and remotely piloted aircrafts (RPAs), and the sensors used, in relation to the 5th industrial revolution. Nevertheless, since 1957, RS technology has found applications, through the use of satellite imagery, in agriculture, which was later enriched by the incorporation of remotely piloted aircrafts (RPAs), which is further pushing the boundaries of proficiency through the upgrading of sensors capable of higher spectral, spatial, and temporal resolutions. More prominently, wireless sensor technologies (WST) have streamlined real time information acquisition and programming for respective measures. Improved algorithms and sensors can, not only add significant value to crop data acquisition, but can also devise simulations on yield, harvesting and irrigation periods, metrological data, etc., by making use of cloud computing. The RS technology generates huge sets of data that necessitate the incorporation of artificial intelligence (AI) and big data to extract useful products, thereby augmenting the adeptness and efficiency of agriculture to ensure its sustainability. These technologies have made the orientation of current research towards the estimation of plant physiological traits rather than the structural parameters possible. Futuristic approaches for benefiting from these cutting-edge technologies are discussed in this study. This study can be helpful for researchers, academics, and young students aspiring to play a role in the achievement of sustainable agriculture.

scholarly journals Strengthening implementation of antimicrobial resistance national action plans

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
M Anderson ◽  
K Schulze ◽  
A Cassini ◽  
D Plauchoras ◽  
E Mossialos
Keyword(s):  
Antimicrobial Resistance ◽  
Policy Design ◽  
Animal Health ◽  
Monitoring And Evaluation ◽  
Basic Structure ◽  
Infection Prevention And Control ◽  
Action Plans ◽  
Governance Framework ◽  
Food And Agriculture ◽  
Food And Agriculture Organization

Abstract Antimicrobial resistance is one of the major challenges of our time. Countries use national action plans as a mechanism to build engagement among stakeholders and coordinate a range of actions across human, animal, and environmental health. However, implementation of recommended policies such as stewardship of antimicrobials, infection prevention and control, and stimulating research and development of novel antimicrobials and alternatives remains inconsistent. Improving the quality of governance within antimicrobial resistance national action plans is an essential step to improving implementation. To date, no systematic approach to governance of national action plans on AMR exists. To address this issue, we aimed to develop the first governance framework to offer guidance for both the development and assessment of national action plans on AMR. We reviewed health system governance framework reviews to inform the basic structure of our framework, international guidance documents from WHO, the Food and Agriculture Organization, the World Organisation for Animal Health, and the European Commission, and sought the input of 25 experts from international organisations, government ministries, policy institutes, and academic institutions to develop and refine our framework. The framework consists of 18 domains with 52 indicators that are contained within three governance areas: policy design, implementation tools, and monitoring and evaluation. Countries must engage with a cyclical process of continuous design, implementation, monitoring and evaluation to achieve these aims.

scholarly journals Plasma and Urinary Amino Acid-Derived Catabolites as Potential Biomarkers of Protein and Amino Acid Deficiency in Rats

Nutrients ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 1567
Author(s):  
Joanna Moro ◽  
Nadezda Khodorova ◽  
Daniel Tomé ◽  
Claire Gaudichon ◽  
Catherine Tardivel ◽  
...  
Keyword(s):  
Amino Acid ◽  
Dietary Intakes ◽  
Analysis Model ◽  
Factorial Method ◽  
New Methods ◽  
Food And Agriculture ◽  
Food And Agriculture Organization ◽  
Weanling Rats ◽  
Urinary Amino ◽  
One Way Anova

Objective: Dietary intakes must cover protein and essential amino acid (EAA) requirements. For this purpose, different methods have been developed such as the nitrogen balance method, factorial method, or AA tracer studies. However, these methods are either invasive or imprecise, and the Food and Agriculture Organization of the United Nations (FAO, 2013) recommends new methods and, in particular, metabolomics. The aim of this study is to determine total protein/EAA requirement in the plasma and urine of growing rats. Methods: 36 weanling rats were fed with diets containing 3, 5, 8, 12, 15, and 20% protein for 3 weeks. During experimentation, urine was collected using metabolic cages, and blood from the portal vein and vena was taken at the end of the experiment. Metabolomics analyses were performed using LC-MS, and the data were analyzed with a multivariate analysis model, partial least Squares (PLS) regression, and independent component-discriminant analysis (ICDA). Each discriminant metabolite identified by PLS or ICDA was tested by one-way ANOVA to evaluate the effect of diet. Results: PLS and ICDA allowed us to identify discriminating metabolites between different diet groups. Protein deficiency led to an increase in the AA catabolism enzyme systems inducing the production of breakdown metabolites in the plasma and urine. Conclusion: These results indicate that metabolites are specific for the state of EAA deficiency and sufficiency. Some types of biomarkers such as AA degradation metabolites appear to be specific candidates for protein/EAA requirement.

scholarly journals Analysis of Antioxidant and Antiallergic Active Components Extracted From the Edible Insect Oxya yezoensis

2021 ◽  
Vol 16 (5) ◽  
pp. 1934578X2110233
Author(s):  
Masahiro Saiki ◽  
Naomichi Takemoto ◽  
Maki Nagata ◽  
Masako Matsumoto ◽  
Yhiya Amen ◽  
...  
Keyword(s):  
Antioxidant Activity ◽  
Phenolic Compounds ◽  
Unsaturated Fatty Acids ◽  
Soluble Fraction ◽  
Total Phenolic ◽  
Key Factors ◽  
Active Components ◽  
Food And Agriculture ◽  
Food And Agriculture Organization

In recent years, entomophagy has attracted increased attention, as it was recommended as a potential source of food by the Food and Agriculture Organization of the United Nations. In Japan, Oxya yezoensisis one of the most widely eaten insect species, but studies of its functionality as a food are limited. In this study, we reported the optimal characterization of the total phenolic compounds in methanolic extract (OME) and different fractions of OME. Additionally, the antioxidant and antiallergic activities of the OME fractions were evaluated. The results showed that the ethyl acetate-soluble fraction of OME has potential antioxidant activity, whereas the n-hexane-soluble fraction showed the strongest inhibition of β-hexosaminidase, which is one of the key factors in allergic reactions. It was concluded that phenolic compounds might contribute to the antioxidant activity while unsaturated fatty acids contribute to the antiallergy activity.

Food and Agriculture Organization

1952 ◽  
Vol 6 (3) ◽  
pp. 430-432
Keyword(s):  
Director General ◽  
Food And Agriculture ◽  
Food And Agriculture Organization ◽  
Sixth Session

The sixth session of the Food and Agriculture Organization Conference, held from November 19 to December 7, 1951 in Rome,1 elected Amintore Fanfani (Italy) chairman and reappointed Norris E. Dodd Director-General for an additional two-year period. On November 21, 1951 the conference voted to admit to FAO Argentina by 53 votes to 0, Japan by 47 votes to 0, Nepal by 49 votes to 1, and Laos by 44 votes to 2.

Sign in / Sign up

Export Citation Format

Share Document