Determination of fat and moisture in olives by nearinfrarred reflectance spectroscopy

Near-Infrared (NIR) Spectrometry as a Fast and Reliable Tool for Fat and Moisture Analyses in Olives

The evaluation of fat and moisture contents for olive fruits is crucial for both olive growers and olive oil processors. Reference methods, such as Soxhlet extraction, used for fat content determination in olive fruits are time- and solvent- consuming and labor intensive. Near-infrared (NIR) spectroscopy is proposed as a solution toward rapid and nondestructive analyses of olive fruit fat and moisture contents. In the present work, comparative studies of the fat and moisture quantification methods were performed on four cultivars (Arbosana, Arbequina, Chiquitita, and Koroneiki) during six different harvesting time points to determine the potential of NIR as an alternative methodology. The impact of olive paste crushing degree on NIR performance was also investigated using three different grid sizes (4, 6, and 8 mm) on a hammer mill, in addition to a blade crusher. Results indicate a satisfactory correlation between the reference Soxhlet and NIR methods with R ² = 0.995. A comparison study of moisture content was also done on NIR and the use of conventional oven with the R ² value of 0.995. The crushing blade produced higher values in both moisture and fat contents in comparison to the hammer mill. The evaluation indicates that when building a chemometric model, all crush sizes and blade sizes should be represented in the model for highest accuracy.

Analysis of moisture, oil, and fatty acid composition of olives by near-infrared spectroscopy: development and validation calibration models

BACKGROUND

Olive is a new, expanding crop in Georgia. Its oil content steadily increases with maturity, but eventually plateaus at the maximum when the olives should be promptly harvested, avoiding overripening and quality degradation. This requires frequent testing. However, olive quality analysis by wet chemistry is laborious, slow and costly, whereas near-infrared reflectance spectroscopy (NIRS), being precise, accurate, rapid and cheap, could be suitable. We developed and validated NIRS calibration models for moisture, fresh-matter-oil (oil-FMO), dry-matter-oil (oil-DMO) and major fatty acid composition analyses.

RESULTS

Of the12 models developed, seven constituents - moisture, oil-FMO, oil-DMO, and palmitic, palmitoleic, oleic and linoleic acids (representing 88-97% of the total fatty acids) had low standard errors and high coefficients of determination (R² = 0.81-0.98; 1 - VR = 0.74-0.86) for both calibration and cross-validation. For these seven constituents, predictions of an independent validation set yielded excellent agreement between the NIRS predicted values and the reference values with low standard error of prediction (SEP), low bias, high coefficient of determination (r² = 0.80-0.93) and high ratios of performance to deviation (RPD = SD/SEP; 2.21-3.85).

CONCLUSION

Precise, accurate and rapid analysis of fresh olives for moisture, oil and major fatty acid composition can be done at a low cost using NIRS, meeting the analytical needs of the industry. © 2017 Society of Chemical Industry.

Novel technologies for monitoring the in-line quality of virgin olive oil during manufacturing and storage

The quality of virgin olive oil is related to the agronomic conditions of the olive fruits and the process variables of the production process. Nowadays, food markets demand better products in terms of safety, health and organoleptic properties with competitive prices. Innovative techniques for process control, inspection and classification have been developed in order to to achieve these requirements. This paper presents a review of the most significant sensing technologies which are increasingly used in the olive oil industry to supervise and control the virgin olive oil production process. Throughout the present work, the main research studies in the literature that employ non-invasive technologies such as infrared spectroscopy, computer vision, machine olfaction technology, electronic tongues and dielectric spectroscopy are analysed and their main results and conclusions are presented. These technologies are used on olive fruit, olive slurry and olive oil to determine parameters such as acidity, peroxide indexes, ripening indexes, organoleptic properties and minor components, among others. © 2016 Society of Chemical Industry.

Determination of water content in olive oil by 31P NMR spectroscopy

A method for moisture determination in olive oil using 31P NMR spectroscopy is developed. This method is based on the replacement of the hydrogen atoms of water molecules with the tagging agents 2-chloro-4,4,5,5-tetramethyl-1,3,2-dioxaphospholane and diphenylphosphinic chloride. Both reagents were successful in determining moisture in olive oil. However, only the second reagent provided a clean and instantaneous reaction under mild condition with no side reactions as observed with the first reagent. A study comparison was made to assess the agreement between the present analytical NMR method and the well-established methods of Karl Fischer titration.

Fourier transform Raman spectrometry for the quantitative analysis of oil content and humidity in olives

A method for the direct and fast determination of oil content and humidity in olives using Fourier transform Raman spectrometry is reported. The only sample preparation step required was crushing of the olives using a hammer mill. The crushed olives were placed in a dedicated sample cup, which was rotated excentrically to the horizontal laser beam during spectrum acquisition. This allowed us to sample an increased volume and thus compensate for sample inhomogeneities. In this way the reproducibility of Raman spectra taken from crushed olives was significantly improved. Partial least-squares (PLS) regression was used for the chemometric evaluation of the Raman spectra. Standard errors of prediction for the validation set of 0.81% for oil content (in the range 19.68-35.71%) and 1.54% for humidity (in the range 29.23-51.49%), both expressed as weight percentage referred to fresh matter, were obtained.