Feijoa (Pineapple Guava) Fruit

2010 ◽  
pp. 623-628
Keyword(s):  
Guava Fruit ◽  
Pineapple Guava

scholarly journals Development and quality of pineapple guava fruit in two locations with different altitudes in Cundinamarca, Colombia

Bragantia ◽  
2015 ◽  
Vol 74 (3) ◽  
pp. 359-366 ◽  
Author(s):  
Alfonso Parra-Coronado ◽  
Gerhard Fischer ◽  
Jesús Hernán Camacho-Tamayo
Keyword(s):  
Guava Fruit ◽  
Pineapple Guava ◽  
Different Altitudes

scholarly journals Growth model of the pineapple guava fruit as a function of thermal time and altitude

2016 ◽  
Vol 36 (3) ◽  
pp. 6 ◽  
Author(s):  
Alfonso Parra-Coronado ◽  
Gerhard Fischer ◽  
Gerhard Fischer ◽  
Jesus Hernan Camacho-Tamayo ◽  
Jesus Hernan Camacho-Tamayo
Keyword(s):  
Regression Analysis ◽  
San Francisco ◽  
Growth Model ◽  
Cross Validation ◽  
Thermal Time ◽  
Logistic Growth ◽  
Guava Fruit ◽  
Pineapple Guava ◽  
Production Area ◽  
Logistic Growth Model

The growth of the pineapple guava fruit is primarily stimulated by temperature but is also influenced by other climactic factors, such as altitude. The goal of this study was to develop a growth model for the pineapple guava fruit as a function of thermal time (GDD, growing-degree day) and altitude (H) of the production area. Twenty trees per farm were marked in two sites in the Cundinamarca department (Colombia) during the 2012 and 2014 seasons. The measurements were performed every seven days after day 96 and 99 post-anthesis until harvest in the sites of Tenjo (2,580 m.a.s.l.) and San Francisco de Sales (1,800 m.a.s.l.), respectively. A growth model was produced for weight as a function of fruit length and diameter as well as for the weight of the fruit as a function of GDD and H, with this last measure adjusted to a sigmoidal logistic growth model. The parameters for the regression analysis showed that the models satisfactorily predicted fruit growth for both of the sites, with a high determination coefficient. The cross-validation showed good statistical fit between the predicted and observed models; the intercept was not significantly different than zero, and the slope was statistically equal to one.

scholarly journals Post-harvest quality model of pineapple guava fruit according to storage and weather conditions of cultivation

2017 ◽  
Vol 21 (9) ◽  
pp. 634-639
Author(s):  
Alfonso Parra-Coronado ◽  
Gerhard Fischer ◽  
Jesús H. Camacho-Tamayo
Keyword(s):  
San Francisco ◽  
Weather Conditions ◽  
Quality Characteristics ◽  
Quality Model ◽  
Ripe Fruit ◽  
Post Harvest ◽  
Guava Fruit ◽  
Pineapple Guava ◽  
Growing Region

ABSTRACT The post-harvest quality of pineapple guava fruit is determined by the storage and prevailing weather conditions during growth and development. This study proposes a model for post-harvest fruit quality according to the storage and weather conditions in the pineapple guava growing region. Physiologically ripe fruit were collected during two harvests from two locations within the Department of Cundinamarca (Colombia): Tenjo and San Francisco de Sales. The fruits were stored at 18 ± 1 °C (76 ± 5% relative humidity (RH), over 11 days) and at 5 ± 1 °C (87 ± 5% RH, over 31 days), and the quality attributes were evaluated every two days. Models of the most significant physio-chemical quality characteristics of the post-harvest fruit were developed by using the Excel® Solver tool for all data obtained in the two crop periods. The results showed that storage and prevailing weather conditions, which differed according to the altitude of the growing site, had considerable impacts on the physio-chemical characteristics of the fruit throughout the post-harvest ripening process.

Guava (Psidium guajava L.) Fruit Coating with Gum – Arabic for Quality and Fruit Fly Control

1970 ◽  
pp. 01-04
Author(s):  
Esameldin B. M. Kabbashi, Ghada H. Abdelrahman and Nawal A. Abdlerahman
Keyword(s):  
Shelf Life ◽  
Gum Arabic ◽  
Fruit Fly ◽  
Psidium Guajava ◽  
Postharvest Quality ◽  
Guava Fruit ◽  
Fruit Shelf Life ◽  
Fly Control ◽  
And Control ◽  
Subtropical Fruit

Guava (Psidium guajava L.) is a lovely tropical and subtropical fruit that originates in Mexico, Central America, and then taken to other distant and near parts around the world. In Sudan this popular fruit is produced in orchards and household and is so profitable but yet attacked by a lot of fruit fly species of the Genera Ceratitis and Bactrocera and the result is a loss of more than 70%. This research aimed at evaluating the effect of Gum Arabic coating (GAC) in extending the shelf life of guava fruit and disinfesting it from these notorious pests. Guava fruits from Kadaro orchards, Khartoum North, were tested using seven concentrations of Gum Arabic solutions. The results reflect that 1: 4 (25%) and 1: 8 (12.5%) (GA: water) concentrations attained 56 and 40% disinfestation, respectively whereas the other lower concentrations effected corresponding results in a range from 20 – 08%. The reduction in maggots per test fruit reached upto 188% as compared to the control.  The highest concentrations (1: 4 & 1: 8) effected a sustainability of 52% in fruit firmness (FF) with an average of medium (3) FF compared to soft FF (4) in the control. The corresponding results in other lower concentrations (1: 16; 1: 32; 1: 64; 1: 72 & 1: 96) were 36, 24, 24, 20 and 16%, respectively. In addition to an average FF of 4 (soft) for all these concentrations and 5 (very soft) for all the corresponding controls. Nevertheless, the sustainability of fruit color (FC) effected by the test concentrations was 52, 44, 24, 22, 24, 20, and 24%, respectively. Regarding these results, the two highest test concentrations effected a sizeable disinfestation and control of fruit flies and a good extension of shelf life of guava in Khartoum State. These findings support using this treatment as an effective IPM tool to extend guava fruit shelf life and upgrading its postharvest quality.

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.

scholarly journals Seasonal Changes in the Levels of Polyphenols in Guava Fruit and Leaves and some their Properties

1987 ◽  
Vol 56 (1) ◽  
pp. 107-113 ◽  
Author(s):  
Saburo ITOO ◽  
Tomoaki MATSUO ◽  
Yuji IBUSHI ◽  
Nobuto TAMARI
Keyword(s):  
Seasonal Changes ◽  
Guava Fruit

scholarly journals Model of pre-harvest quality of pineapple guava fruits (Acca sellowiana (O. berg) burret) as a function of weather conditions of the crops

Bragantia ◽  
2017 ◽  
Vol 76 (1) ◽  
pp. 177-186 ◽  
Author(s):  
Alfonso Parra-Coronado ◽  
Gerhard Fischer ◽  
Jesús Hernán Camacho-Tamayo
Keyword(s):  
Weather Conditions ◽  
Pineapple Guava ◽  
Acca Sellowiana

scholarly journals Histopathology of Colletotrichum gloeosporioides on guava fruits (Psidium guajava L.)

2013 ◽  
Vol 35 (2) ◽  
pp. 657-664 ◽  
Author(s):  
Sylvia Raquel Gomes Moraes ◽  
Francisco André Osama Tanaka ◽  
Nelson Sidnei Massola Júnior
Keyword(s):  
Electron Microscopy ◽  
Transmission Electron Microscopy ◽  
Colletotrichum Gloeosporioides ◽  
Psidium Guajava ◽  
Mature Stage ◽  
Guava Fruit ◽  
Transmission Electron ◽  
Colonization Process ◽  
Parenchymal Cells ◽  
Appressoria Formation

Anthracnose, caused by Colletotrichum gloeosporioides, produces brown lesions on guava fruits, causing severe losses on postharvest. In this study, the infection and colonization of guava fruits by C. gloeosporioides has been examined using scanning and transmission electron microscopy. Fruits at the physiologically mature stage were inoculated with a 10(5) conidia/mL spore suspension. Afterward, fruits were incubated at 25 °C in a wet chamber for periods of 6, 12, 24, 48, 96 and 120 h to allow examination of the infection and colonization process. Conidia germination and appressoria formation occurred six hours after inoculation (h.a.i). Penetration occurred directly via penetration pegs from appressoria, which penetrated the host cuticle 48 h.a.i. Notably, the appressoria did not produce an appressorial cone surrounding the penetration pore. Infection vesicles were found in epidermal cells 96 h.a.i. The same fungal structures were found in epidermal and parenchymal cells of the host 120 h.a.i. Colonization strategy of C. gloeosporioides on guava fruit was intracellular hemibiotrophic.

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