Effects of deficit irrigation on ‘Koroneiki’ olive tree growth, physiology and olive oil quality at different harvest dates

2021 ◽  
Vol 258 ◽  
pp. 107200
Author(s):  
M. Siakou ◽  
A. Bruggeman ◽  
M. Eliades ◽  
C. Zoumides ◽  
H. Djuma ◽  
...  
Keyword(s):  
Olive Oil ◽  
Tree Growth ◽  
Deficit Irrigation ◽  
Oil Quality ◽  
Olive Tree ◽  
Growth Physiology ◽  
Olive Oil Quality ◽  
Harvest Dates

scholarly journals Mechanical Harvesting and Irrigation Strategy Responses on ‘Arbequina’ Olive Oil Quality

2018 ◽  
Vol 28 (5) ◽  
pp. 607-614 ◽  
Author(s):  
Josep Rufat ◽  
Agustí J. Romero-Aroca ◽  
Amadeu Arbonés ◽  
Josep M. Villar ◽  
Juan F. Hermoso ◽  
...  
Keyword(s):  
Fatty Acids ◽  
Olive Oil ◽  
Deficit Irrigation ◽  
Oil Content ◽  
Oil Quality ◽  
Dry Weight ◽  
Irrigation Strategy ◽  
Crop Load ◽  
Olive Oil Quality ◽  
Oil Characteristics

This study describes the effects of mechanical harvesting and irrigation on quality in ‘Arbequina’ olive oil (Olea europaea L.). Irrigation treatments included a control, deficit irrigation (DI) during pit hardening, and subsurface deficit irrigation (SDI). Results showed that mechanical harvesting damaged the olives and reduced olive oil quality by increasing free fatty acids (FFAs) and peroxide value, and by decreasing fruitiness, stability, bitterness, and pungency. DI resulted in increased fruit dry weight and oil content, which could be explained by their reduced crop load (9.3% of crop reduction for DI and 23.9% for SDI). DI did not affect olive oil characteristics, whereas SDI increased stability, fruitiness, and bitterness, and decreased polyunsaturated fatty acid (PUFAs). In conclusion, mechanical harvesting tended to damage the fruit, resulting in lower quality olive oil, the DI strategy neither affected fruit nor olive oil characteristics, whereas the SDI strategy positively affected oil quality when greater water restrictions were applied.

scholarly journals Virgin olive oil quality of hedgerow ‘Arbequina’ olive trees under deficit irrigation

2016 ◽  
Vol 97 (3) ◽  
pp. 1018-1026 ◽  
Author(s):  
José M García ◽  
Ana Morales-Sillero ◽  
Ana G Pérez-Rubio ◽  
Antonio Diaz-Espejo ◽  
Antonio Montero ◽  
...  
Keyword(s):  
Olive Oil ◽  
Deficit Irrigation ◽  
Oil Quality ◽  
Virgin Olive Oil ◽  
Olive Oil Quality ◽  
Olive Trees

Olive tree (Olea europaea L. cv. Zelmati) grown in hot desert climate: Physio-biochemical responses and olive oil quality

2020 ◽  
Vol 261 ◽  
pp. 108915
Author(s):  
Yesmine Ben Rouina ◽  
Mohamed Zouari ◽  
Nacim Zouari ◽  
Bechir Ben Rouina ◽  
Mohamed Bouaziz
Keyword(s):  
Olive Oil ◽  
Olea Europaea ◽  
Oil Quality ◽  
Olive Tree ◽  
Olea Europaea L ◽  
Biochemical Responses ◽  
Olive Oil Quality ◽  
Desert Climate ◽  
Olea Europaéa

Irrigation effects on phenolic profile and extra virgin olive oil quality of ''Chemlali'' variety grown in South Tunisia

2021 ◽  
Vol 141 ◽  
pp. 322-329
Author(s):  
Jihed Faghim ◽  
Mbarka Ben Mohamed ◽  
Mohamed Bagues ◽  
Kamel Nagaz ◽  
Tebra Triki ◽  
...  
Keyword(s):  
Olive Oil ◽  
Oil Quality ◽  
Virgin Olive Oil ◽  
Extra Virgin Olive Oil ◽  
Phenolic Profile ◽  
Olive Oil Quality ◽  
Irrigation Effects ◽  
South Tunisia

scholarly journals Identification and Quantification of Olive Oil Quality Parameters Using an Electronic Nose

Agriculture ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 674
Author(s):  
Nawaf Abu-Khalaf
Keyword(s):  
Olive Oil ◽  
Electronic Nose ◽  
Chemical Sensor ◽  
Chemical Constituents ◽  
Oil Quality ◽  
Quality Parameters ◽  
Signal Acquisition ◽  
Good Precision ◽  
Olive Oil Quality ◽  
Quality Categories

An electronic nose (EN), which is a kind of chemical sensor, was employed to check olive oil quality parameters. Fifty samples of olive oil, covering the four quality categories extra virgin, virgin, ordinary virgin and lampante, were gathered from different Palestinian cities. The samples were analysed chemically using routine tests and signals for each chemical were obtained using EN. Each signal acquisition represents the concentration of certain chemical constituents. Partial least squares (PLS) models were used to analyse both chemical and EN data. The results demonstrate that the EN was capable of modelling the acidity parameter with a good performance. The correlation coefficients of the PLS-1 model for acidity were 0.87 and 0.88 for calibration and validation sets, respectively. Furthermore, the values of the standard error of performance to standard deviation (RPD) for acidity were 2.61 and 2.68 for the calibration and the validation sets, respectively. It was found that two principal components (PCs) in the PLS-1 scores plot model explained 86% and 5% of EN and acidity variance, respectively. PLS-1 scores plot showed a high performance in classifying olive oil samples according to quality categories. The results demonstrated that EN can predict/model acidity with good precision. Additionally, EN was able to discriminate between diverse olive oil quality categories.

Sign in / Sign up

Export Citation Format

Share Document