Introduction: Roasting is one of the processing steps involved in the nut industry to improve the flavor, color, texture and overall acceptability of the product. Ppeanut is a fruit or pod of the order Leguminosae and contains 47-50% oil, 25-30% protein and is an essential source of minerals and vitamins; thus it makes a substantial contribution to human nutrition. Peanuts are readily acceptable as a cheap protein source and popular snack item that can be eaten alone or combined with other foods. Recently, peanuts have gained much attention as functional food and roasted peanuts is one of the most popular snack foods, in which roasting is a key step in the process and directly impacts the quality (crispness, taste, and flavor) and shelf-life of the final product. …

The brain electrical signal has been widely used in clinical and academic research, due to its ease of recording, non-invasiveness, and precision. One of the applications can be emotion recognition from the brain's electrical signal. Generally, two types of parameters (Valence and Arousal) are used to determine the type of emotion which in turn indicate "positive or negative" and "level of extroversion or excitement" for a specific emotion. The significance of emotion is determined by the effects of this phenomenon on daily tasks, especially in cases where the person is confronted with activities that require careful attention and concentration. In the emotion recognition problem, firstly, using proper emotion stimuli, different emotions are created for the subjects under study and the brain signals corresponding to each stimulus are recorded. The two main steps for solving the emotion recognition problem are extracting suitable features and using appropriate classification or REGRESSION methods. In previous studies, different visual and auditory have been used and various linear and nonlinear features and classifiers have been investigated. In this paper, the main goal was the improvement of linear REGRESSION algorithms to estimate the criteria for recognizing human emotions more efficiently. For this purpose we proposed a new algorithm that uses the sparseness of the mixing vector along with the linear REGRESSION cost function. The effectiveness of the proposed algorithm on simulated data has been investigated and its superiority to linear REGRESSION algorithms such as PLS, LASSO, SOPLS and Ridge was shown. Also, to apply the proposed algorithm on EEG data corresponding to emotion recognition, the DEAP dataset was used and the AR coefficients were extracted from the EEG signals. The results obtained from the proposed algorithm were compared with those of the other linear REGRESSION algorithms, which in total showed the relative superiority of the proposed method.

Remote sensing systems, especially hyper spectral remote sensing require fundamental knowledge of spectral reflectance of desired tree species for recognizing tree species and mapping forest type. Field spectrometry as a field of remote sensing, dealing with determination of these spectral characteristics tries to provide the spectral libraries for different objects. The objectives of this study were 1) investigating the relationship between spectral reflectance and nitrogen content and 2) investigate the species spectral separability of alder, oak and ironwood leaves based on nitrogen varying in species and to define the best wavelength for this aim, the partial least square (PLS) analysis was used. In this study the spectral fingerprint of the most important forest tree species of the northern forest of Iran namely Alder (Alnus subcordata), Oak (Quercus castaneifolia) and Ironwood (Parrotia persica), were acquired. This has been carried out using a full range spectrometer during the summer 2007. A total of 330 leaf ‘pile’ spectral curves of illuminated and shaded leaves were acquired of 55 trees in altitude range between 250 and 2200 m (asl.) under a clear and cloudless sky. Following the measurements, nitrogen of the mentioned leaves was extracted in laboratory. The value of vegetation indices of illuminated leaves was more than shaded ones and the differences were significant in all species. This result has been proved by statistical results obtained by nitrogen data in lab. Based on the Partial Least Square (PLS) results it proved that nitrogen variable has the ability to discriminate species. These results showed that there was the most distinct separation between Ironwood and both Alder and Oak. There were less distinct separation between Alder and Oak. Based on the result obtained by PLS REGRESSION we could conclude that the best wavelength region for spectral separability of species is in red edge region.

Introduction: Labane or concentrated yoghurt is a semi-solid product which is being producedd by dehydration of yoghurt or separation of water and some water-soluble solids from yoghurt. High nutritional value, long shelf life, more desirable taste and texture and feasibility to produce other product are the reasons for high acceptance among customers. There are wide ranges of production methods from traditional methods which are tedious, such as separation of whey by fabric bags, to complicated time-consuming methods which also contaminate product and reduce its nutritional value. These cause demand to establish more suitable methods such as “ wheyless process” by dried milk, concentrated milk protein or concentrated whey protein. On the other hand, one of the methods for enhancing firmness and textural properties of yoghurts, similar to other dairy products is utilization of hydrocolloids. These components are used for enhancing rheological an textural properties of food and commonly used as additives for increasing viscosity, gel forming ability, enhancing physical stability, film forming ability, controlling crystallization, postponing syneresis and textural improvement. Konjac gum (KG) is a neutral polysaccharide that derived from Amorphophallus konjac C. Koch tuber, which is well known in east countries during centuries. Ability to hold water and reduction of cholesterol and glucose are the reasons for grossing demand of this gum. So due to the importance of labane produced through wheyless process, the effect of different ingredients of formulation such as milk protein concentrate, cheese whey powder and konjac gum on physicochemical, rheological and sensory properties of labane was investigated and compared these properties by using Principal component analysis (PCA) and Partial least squares REGRESSION (PLS REGRESSION). Materials and methods: Cow milk was purchased from local market (Mashhad, Iran). Dried skim milk, milk protein concentrate, cheese whey powder and commercial starter provided from Khorasan Razavi Pegah Company (ABY1, Christian Hansen, Horsholm, Denmark) and KG purchased from Food Chem. (China). In order to concentrate the milk, 3% dried skim milk was added to1 Kg milk. Then, according to the experimental design (table 2), MPC and CWP added to milk at 0, 4, 6 and 8% levels which reached the total solid of milk to 21. 5%. KG with percentage of 0, 0. 05, 0. 1, 0. 15, and 0. 2% was added to the mixture at 40˚ C. The mixtures were homogenized at 50˚ C and pasteurized at 90˚ C for 1 min. and then cooled to 43-45˚ C. The mixtures were incubated at 43-45˚ C for 3-4 hours after addition of starter. Then the samples were slowly stirred and packed in polyethylene bags after reaching to suitable pH. The samples were transfered to refrigerator for 24 hours then the tests were conducted. PH was measured according to AOAC 2005 official method NO. 935. 42. 25 gr of samples were centrifuged at 4˚ C for 10 min. at 4500 rpm. Syneresis was evaluated as parentage of separated serum. Texture analyzer was used for combination of back extrusion and texture profile analysis (TPA) test. 50 mm in diameter cylinder with 10 mm in height and probe with 4 mm diameter and 100 mm height with the speed of 1 mm/s were used to conduct the test. Dynamic rheological parameters were evaluated by rheometer (Parphysica). The devise was equipped by 50mm diameter parallel plate with 2 mm gap. Eheo plus/32 version V3. 40 software was used to measure elastic modulus (G’ ), loss modulus (G” ) and η *. Results & discussion: Results showed that none of the linear, quadratic and interaction effect of MPC, CWP and KG was significant on pH of the samples at the first day. Results represented that the pH of the samples was varied from 0. 36 to 0. 94 after 5 days and only linear effect of MPC and CWP (at 99% level of confidence) and interaction effect of CWP-KG (at 95% level of confidence) were significant on that. The effect of MPC and CWP and interaction effect of MPC-KG, CWP-KG and CWP-MPC-KG were significant on syneresis at 99% of confidence. Results showed that hardness of the samples varied between 3. 25-9. 58 N and the interaction effects of MPC-KG, CWP-KG and CWPMPC-KG were significant at 99% of confidence. None of the linear, quadratic and interaction effect of CWP, MPC and KG was not significant on springiness of the samples (p>0. 05). In strain sweep test, two separated regions were distinguishable: linear viscoelastic (LVE) region that elastic and viscous modulus (G’ and G” ) were constant and G’ was higher than G” which showed the solid like behavior, and non-LVE region that G’ and G” decreased by increasing strain and led to a crossover point (flowing point) which G” goes over the G’ and liquid-like behavior shows itself. In this test, strain corresponding to start of the non-LVE region and sharp reduction of G’ define as critical strain (γ c) and the corresponding stress of this point defined as critical stress (τ c). Results represented that G’ LVE and G” LVE of the samples varied from 22. 54 to 750. 1 and 11. 01 to 242. 1 Pa, respectively and the selected model (cubic x quadratic) showed that the interaction effect of MPC-KG, CWP-KG and CWP-MPC-KG on G’ LVE and G” LVE was significant at 99% of confidence while the interaction effect of CWP-MPC was only meaningful on G” LVE. Results also showed that the variation trend of G’ LVE and G” LVE was the same by alteration MPC, CWP and KG in a way that both of these parameters were increased by increasing KG. The effect of MPC-KG and CWP-KG was significant on γ c and τ c at 95% confidence and also, in addition to mentioned effect, the interaction effect of CWP-MPC was significant only on γ c. Increasing KG increased γ c at higher amount of CWP and lower amount MPC which can be concluded that increasing KG amplified the gel strength. Also, the results of the correlation study between sensory and instrumental measures showed that there was a close relationship between the score of sour taste and the overall acceptance of samples, which showed that among the measured characteristics, sour taste score is more important than other parameters.

In the present work we study the use of Fourier transform near infrared spectroscopy (FTNIRS) technique to analysis the calcium (Ca), phosphorus (P) and copper (Cu) contents of fish meal. The REGRESSION methods employed were partial least squares (PLS) and kernel partial least squares (KPLS). The results showed that the efficiency of KPLS was better than PLS. As a whole, the application of FT-NIRS with PLS and KPLS was as a suitable option for replacing the routine chemical analysis to assess the mineral content in fish meal, allowing immediate control of the fish meal without prior sample treatment or destruction.