Ozone Effect to Control Lemon Postharvest Diseases in Storage Chamber

2018 ◽  
Vol 2 (2) ◽  
Keyword(s):  
Postharvest Diseases ◽  
Storage Chamber

Field testing CFD-based predictions of storage chamber gross solids separation efficiency

1999 ◽  
Vol 39 (9) ◽  
pp. 161-168 ◽  
Author(s):  
Virginia R. Stovin ◽  
Adrian J. Saul ◽  
Andrew Drinkwater ◽  
Ian Clifforde
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Settling Velocity ◽  
Separation Efficiency ◽  
Flow Patterns ◽  
Total Efficiency ◽  
Separation Performance ◽  
Storage Chamber ◽  
Solids Separation ◽  
Simulated Flow

The use of computational fluid dynamics-based techniques for predicting the gross solids and finely suspended solids separation performance of structures within urban drainage systems is becoming well established. This paper compares the result of simulated flow patterns and gross solids separation predictions with field measurements made in a full size storage chamber. The gross solids retention efficiency was measured for six different storage chambers in the field and simulations of these chambers were undertaken using the Fluent computational fluid dynamics software. Differences between the observed and simulated flow patterns are discussed. The simulated flow fields were used to estimate chamber efficiency using particle tracking. Efficiency results are presented as efficiency cusps, with efficiency plotted as a function of settling velocity. The cusp represents a range of efficiency values, and approaches to the estimation of an overall efficiency value from these cusps are briefly discussed. Estimates of total efficiency based on the observed settling velocity distribution differed from the measured values by an average of ±17%. However, estimates of steady flow efficiency were consistently higher than the observed values. The simulated efficiencies agreed with the field observations in identifying the most efficient configuration.

Understanding the Role of Chlorine and Ozone to Control Postharvest Diseases in Fruit and Vegetables: A Review

2020 ◽  
Vol 16 (4) ◽  
pp. 455-461
Author(s):  
Gabriela M. Baia ◽  
Otniel Freitas-Silva ◽  
Murillo F. Junior
Keyword(s):  
Chlorine Dioxide ◽  
Broad Spectrum ◽  
Fruits And Vegetables ◽  
Low Cost ◽  
Residual Effects ◽  
Pathogenic Microorganisms ◽  
Postharvest Diseases ◽  
Post Harvest ◽  
By Products

Fruits and vegetables are foods that come into contact with various types of microorganisms from planting to their consumption. A lack or poor sanitation of these products after harvest can cause high losses due to deterioration and/ or pathogenic microorganisms. There are practically no post-harvest fungicides or bactericides with a broad spectrum of action that have no toxic residual effects and are safe. However, to minimize such problems, the use of sanitizers is an efficient device against these microorganisms. Chlorine is the most prevalent sanitizing agent because of its broad spectrum, low cost and well-established practices. However, the inevitable formation of disinfection by-products, such as trihalomethanes (THMs) and haloacetic acids (HAAs), is considered one of the main threats to food safety. Alternative sanitizers, such as chlorine dioxide (ClO2) and ozone, are becoming popular as a substitute for traditional post-harvest treatments. Thus, this review addresses the use of chlorine, chlorine dioxide and ozone emphasizing aspects, such as usage, safe application, spectrum of action and legislation. In order to ensure the quality and safety of final products, the adoption of well-prepared sanitation and sanitation programs for post-harvest fruits and vegetables is essential.

scholarly journals Effect of Storage Conditions on Storability and Antioxidant Potential of Pears cv. ‘Conference’

Agriculture ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 545
Author(s):  
Grzegorz P. Łysiak ◽  
Krzysztof Rutkowski ◽  
Dorota Walkowiak-Tomczak
Keyword(s):  
Mass Loss ◽  
Strong Influence ◽  
Storage Conditions ◽  
Quality Parameters ◽  
Soluble Solids ◽  
Controlled Atmosphere ◽  
Postharvest Diseases ◽  
Market Prices ◽  
Long Period ◽  
The Impact

Late pear cultivars, such as ‘Conference’, can be stored for a long period if kept in good storage conditions. A three-year study (2011–2013) compared the impact of six-month storage using four technologies—normal atmosphere, normal atmosphere + 1-methylcyclopropene (1-MCP), controlled atmosphere, and controlled atmosphere + 1-MCP—on the quality parameters of ‘Conference’ pears, such as mass loss, firmness, total soluble solids, acidity, antioxidant capacity, and the incidence of diseases and disorders. Additionally, the study analysed different storage conditions in terms of profitability, based on the market prices for pears in the seasons during which the pears were stored. The storage conditions had a very strong influence on the fruit quality parameters, and were found to affect most visibly the mass loss and the incidence of postharvest diseases and disorders. The storage of ‘Conference’ pears for 180 days in normal atmosphere is not economically viable, even if the fruit is subjected to 1-MCP treatment; at the same time, it is profitable to store ‘Conference’ pears in controlled atmosphere for the same period, no matter whether 1-MCP was applied or not.

scholarly journals Identification of Lasiodiplodia pseudotheobromae Causing Fruit Rot of Citrus in China

Plants ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 202
Author(s):  
Jianghua Chen ◽  
Zihang Zhu ◽  
Yanping Fu ◽  
Jiasen Cheng ◽  
Jiatao Xie ◽  
...  
Keyword(s):  
Phylogenetic Analyses ◽  
Elongation Factor ◽  
Morphological Characteristics ◽  
Citrus Fruit ◽  
Economic Loss ◽  
Fruit Rot ◽  
Post Inoculation ◽  
Citrus Reticulata ◽  
Postharvest Diseases ◽  
Citrus Reticulata Blanco

Considering the huge economic loss caused by postharvest diseases, the identification and prevention of citrus postharvest diseases is vital to the citrus industry. In 2018, 16 decayed citrus fruit from four citrus varieties—Satsuma mandarin (Citrus unshiu), Ponkan (Citrus reticulata Blanco cv. Ponkan), Nanfeng mandarin (Citrus reticulata cv. nanfengmiju), and Sugar orange (Citrus reticulata Blanco)—showing soft rot and sogginess on their surfaces and covered with white mycelia were collected from storage rooms in seven provinces. The pathogens were isolated and the pathogenicity of the isolates was tested. The fungal strains were identified as Lasiodiplodia pseudotheobromae based on their morphological characteristics and phylogenetic analyses using the internal transcribed spacer regions (ITS), translation elongation factor 1-α gene (TEF), and beta-tubulin (TUB) gene sequences. The strains could infect wounded citrus fruit and cause decay within two days post inoculation, but could not infect unwounded fruit. To our knowledge, this is the first report of citrus fruit decay caused by L. pseudotheobromae in China.

scholarly journals AI-Driven Framework for Recognition of Guava Plant Diseases through Machine Learning from DSLR Camera Sensor Based High Resolution Imagery

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3830
Author(s):  
Ahmad Almadhor ◽  
Hafiz Tayyab Rauf ◽  
Muhammad Ikram Ullah Lali ◽  
Robertas Damaševičius ◽  
Bader Alouffi ◽  
...  
Keyword(s):  
Machine Learning ◽  
High Resolution ◽  
Color Difference ◽  
Plant Diseases ◽  
Economic Losses ◽  
Production Loss ◽  
Postharvest Diseases ◽  
Tropical Regions ◽  
Guava Fruit ◽  
Tree Classifier

Plant diseases can cause a considerable reduction in the quality and number of agricultural products. Guava, well known to be the tropics’ apple, is one significant fruit cultivated in tropical regions. It is attacked by 177 pathogens, including 167 fungal and others such as bacterial, algal, and nematodes. In addition, postharvest diseases may cause crucial production loss. Due to minor variations in various guava disease symptoms, an expert opinion is required for disease analysis. Improper diagnosis may cause economic losses to farmers’ improper use of pesticides. Automatic detection of diseases in plants once they emerge on the plants’ leaves and fruit is required to maintain high crop fields. In this paper, an artificial intelligence (AI) driven framework is presented to detect and classify the most common guava plant diseases. The proposed framework employs the ΔE color difference image segmentation to segregate the areas infected by the disease. Furthermore, color (RGB, HSV) histogram and textural (LBP) features are applied to extract rich, informative feature vectors. The combination of color and textural features are used to identify and attain similar outcomes compared to individual channels, while disease recognition is performed by employing advanced machine-learning classifiers (Fine KNN, Complex Tree, Boosted Tree, Bagged Tree, Cubic SVM). The proposed framework is evaluated on a high-resolution (18 MP) image dataset of guava leaves and fruit. The best recognition results were obtained by Bagged Tree classifier on a set of RGB, HSV, and LBP features (99% accuracy in recognizing four guava fruit diseases (Canker, Mummification, Dot, and Rust) against healthy fruit). The proposed framework may help the farmers to avoid possible production loss by taking early precautions.

Essential oils to control postharvest diseases of apples and peaches: elucidation of the mechanism of action

2021 ◽  
pp. 35-42
Author(s):  
D. Spadaro ◽  
H. Banani ◽  
K. Santoro ◽  
A. Garibaldi ◽  
M.L. Gullino
Keyword(s):  
Essential Oils ◽  
Mechanism Of Action ◽  
Postharvest Diseases

Antifungal effects of low environmental risk compounds on development of pear postharvest diseases: Orchard and postharvest applications

2022 ◽  
Vol 295 ◽  
pp. 110862
Author(s):  
María Cecilia Lutz ◽  
Adrián Colodner ◽  
Marisa Alumine Tudela ◽  
Marcelo Anibal Carmona ◽  
María Cristina Sosa
Keyword(s):  
Environmental Risk ◽  
Postharvest Diseases ◽  
Antifungal Effects
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