جستجوی مقالات مرتبط با کلیدواژه « Pistachio » در نشریات گروه « مکانیزاسیون کشاورزی »

Pistachio production has been adversely affected by Psylla, which is a devastating insect. The primary goal of this study was to select sensitive spectral bands to distinguish pistachio leaves infected by Psylla from healthy leaves. Diagnosis of psylla disease before the onset of visual cues is crucial for making decisions about topical garden management. Since it is not possible to diagnose psylla disease even after the onset of symptoms with the help of color images by drones, hyperspectral and multispectral sensors are needed. The main purpose of this study was to extract spectral bands suitable for distinguishing healthy leaves from psylla leaves. For this purpose, in this paper, a new method for selecting sensitive spectral properties from hyperspectral data with the high spectral resolution is presented. The intelligent selection of sensitive bands is a convenient way to build multispectral sensors for a specific application (in this article, the diagnosis of psylla leaves). Knowledge of disease-sensitive wavelengths can also help researchers analyze multispectral and hyperspectral aerial images captured by satellites or drones.

A total number of 160 healthy and diseased leaves were scanned in 64 spectral bands between 400-1100 nm with 10 nm spectral resolution. A random forest algorithm was used to identify the importance of features in classifying the dataset into diseased and healthy leaves. After computing the importance of the features, a clustering algorithm was developed to cluster the most important features into six clusters such that the center of clusters was 50 nm apart. To transfer the hyperspectral dataset into a multispectral dataset, the reflectance was averaged in spectral bands within ±15 nm of each cluster center and achieved six broad multispectral bands. Afterwards a support vector machine algorithm was utilized to classify the diseased and healthy leaves using both hyperspectral and multispectral datasets.

The center of clusters were 468 nm, 598 nm, 710 nm, 791 nm, 858 nm, and 1023 nm, which were calculated by taking the average of all the members assigned to the individual clusters. These are the most informative spectral bands to distinguish the pistachio leaves infected by Psylla from the healthy leaves. The F1-score was 90.91 when the hyperspectral dataset (all bands) was used, while the F1-score was 88.69 for the multispectral dataset. The subtle difference between the F1-scores indicates that the proposed pipeline in this study was able to select appropriately the sensitive bands while retaining all relevant information.

The importance of spectral bands in the visible and near-infrared region (between 400 and 1100 nm) was obtained to identify pistachio tree leaves infected with psylla disease. Based on the importance of spectral properties and using a clustering algorithm, six wavelengths were obtained as the best wavelengths for classifying healthy and diseased pistachio leaves. Then, by averaging the wavelengths at a distance of 15 nm from these six centers, the hyperspectral data (64 bands) became multispectral (6 bands). Since the correlation between the wavelengths in the near-infrared region was very high (more than 95%), out of the three selected wavelengths in the near-infrared region (710, 791, and 1023), only the 710-nm wavelength, which was closer to the visible region, was selected. The results of classification of infected and diseased leaves using hyperspectral and multispectral data showed that the degree of classification accuracy decreases by about 2% and if only 4 bands are used, the degree of accuracy decreases by about 3%.The results of this study revealed that the proposed framework could be used for selecting the most informative spectral bands and accordingly develop custom-designed multispectral sensors for disease detection in pistachio. In addition, we could reduce the dimensionality of the hyperspectral datasets and avoid the issues related to the curse of dimensionalitylity.

The use of organic fertilizers in sustainable agriculture, in addition to increasing the support and activity of beneficial soil microorganisms in order to provide plant nutrients such as nitrogen, phosphorus and soluble potassium and also improves plant growth and yield are so necessary. In pistachio growing areas due to soil constraints such as salinity and sodium content of the soil, lack of proper structure in most areas, poor soil texture and long irrigation cycle, the use of auxiliary substances such as humic acid, can improve the situation and lead to increase nutrient uptake and increase growth and yield and sustainable production.

This experiment was carried out in a randomized complete block design with three replications in MahVelat. The main plot consisted of four types of humic acid (ordinary solid humic acid, Ferti Plus solid humic acid, Iranian liquid humic acid (all three products of Shimi Gol Feyz Khorasan Company) and American Liquid Humic Acid (HUMAX) and subplot including different application levels (0, first level for solid fertilizers 600 kg and liquid fertilizers 40 liters per hectare and second level for solid fertilizers 800 kg and liquid fertilizers 60 liters per hectare). The number of trees tested was 36 trees of 10-year-old almond cultivar. Solid fertilizer was applied once (March 2016) and liquid fertilizer twice (March 2016 and May 2017). Irrigation was drip (Babler) and studies were considered for one year. In August 2017, by random sampling of the leaves of each tree, the concentration of nitrogen, phosphorus, potassium, calcium and magnesium in the plant leaves and also by sampling the soil of the foot of each tree, some soil chemical properties, including pH, Organic carbon content, available nitrogen concentration and available phosphorus concentration in soil, potassium, calcium and magnesium in soil solution extract were measured. In September 2017, yield components (weight of 100 grains, ounce and emptiness percent) of each tree were measured by weight. The results were statistically analyzed using SAS software and the mean of the experimental data were compared with each other by Duncan's multiple range tests at 5% probability level.

The amount of organic carbon (71.42%), nitrogen (72.22%), and soil potassium (43.01%) with all types of humic acids showed a significant increase compared to the control, but no significant difference was observed between the consumed humic acids. The highest amount of available phosphorus (78/30%) in soil, calcium (54/90%) and magnesium (56.05%) was obtained from liquid ShimiGol and Humax. With increasing the amount of humic acid, electrical conductivity (13.71%) decreased but organic carbon (82.88%), nitrogen (55%), phosphorus (75.93%), potassium (23.97%), calcium (46.35%) and magnesium (58.82%) showed a significant increase and the highest amount of these properties was obtained in the highest amount of humic acid consumption. The interaction of humic acid type and its amount on the amount of organic carbon, phosphorus, potassium, calcium and magnesium in the soil was significant and the highest amount of calcium (57.03%) was obtained from the application of 60 liters per hectare of Humax. The highest leaf nitrogen concentrations were obtained from the application of liquid Humax (MAX:42.23%), liquid of Shimi Gol, solid Ferti Plus and ordinary solid ShimiGol, respectively. The highest concentrations of phosphorus (17.65%) and magnesium (16.96%) were obtained from Humax and the highest concentrations of calcium were obtained from three solid humic acids, Ferti Plus, liquid of ShimiGol and liquid of Humax with a significant difference with ordinary solid. The type of humic acid consumed was not significant on any of the yield components (weight of 100 grains (21.69%), ounces (27.45%) and emptiness percent (25.38%)). The amount of humic acid consumed was significant on all measured characteristics. So that the best yield components and the highest element concentration were obtained from the highest amount of humic acid consumption.Humic acid has direct and indirect effects on plants. Indirect effect is usually in the form of changes in environmental conditions such as modification of soil physical condition, enzymatic and hormonal effects and soil pH, improvement of soil structure, aeration, drainage, water holding capacity, soil temperature and direct effects includes increasing biomass and microbial population, antiviral activity and growth modulation, increasing plant resistance to salinity and drought stress. Humic acid increases nutrient uptake, increases germination and root growth, and improves yield quantitatively and qualitatively. Humic substances also dissolve calcium carbonate in the soil and replace calcium with sodium by activating sulfur oxidizing bacteria, as well as reduction of soil pH to improve nutrient uptake. Humic acid can directly release various elements from minerals, absorb them and deliver them to the roots at the right time. Because humic acid is a valuable source of macro and micro nutrients, it provides a good nutritional balance for the plant and leads to greater absorption of nutrients and specific functional responses in the plant.

Application of humic acids in liquid or solid form, domestically or externally produced, can increase the supply of nitrogen, potassium, phosphorus, calcium, magnesium, as well as the content of organic carbon in the soil and reduce pH, increase the concentration of elements in leaves and improve yield components. Of course, it should be noted that among the internal humic acids, the solid Ferty Plus, Shimi Gol were as well as Humax liquid. Relying on internal knowledge can prevent unnecessary outflow of currency.

Hyperspectral imaging technique as a new and efficient method is applied for detecting infection in agricultural products. It was used for classification of healthy and infected pistachio kernels by Aspergillus flavus fungus with and without considering infection stages. Two different fungus isolates, R5 and KK11 with and without capable of producing aflatoxin, respectively, were individually used to infect the pistachio kernel samples. From 960 to 1700 nm, three effective wavelengths of 1090, 1280, and 1700 nm were selected by principle component analysis method. After feature extraction, K-fold cross validation, support vector machine, and artificial neural network methods were used for classification. The results showed that the classification accuracy of the K-fold cross validation method was higher for classifying the healthy and infected pistachios without considering the infection stages and isolate type (99.71%). The maximum accuracy of the developed algorithms in classification of isolate type and infection stage was obtained as 69-91%.

Precision Agriculture by managing in-farm variables and acquiring soil and product variable properties, mapping, analyzing variables, and accepting appropriate management practices lead to optimal use of inputs and increase performance with minimizing environmental effects. Therefore, in order to implement precision Agriculture, the first step is sufficient knowledge about the quantity of the yield. so, in this research, the pistachio yield monitoring system was designed and constructed and the machine performance was investigated in the laboratory tests. in this study the number of Connecting chains and height of the reservoir were selected as Variable factors. The number of chains at 3 levels (2, 3 and 4) and reservoir height at 3 levels (10, 20 and 30 cm) were investigated. The results showed that optimum values for the weighing of the product in the reservoir were not significant for the number of chains, so, in order to achieve better equilibrium in this study, four chains were used. Also, with the 20 cm height of the reservoir, the best results were obtained. The highest error value was 3.6%. After the laboratory tests, the system was transferred to the pistachio orchard and weight data were recorded associated with the location of each pistachio tree (by GPS). Among the methods of IDW interpolation, ordinary kriging, simple kriging, and general kriging, the ordinary Kriging method was introduced as the best method due to lower RMSE (1160.89). At the end, the yield map of the product was created by the usual Kriging method in the GIS software, which can be used along with other data as a prescriptive map for better management of the orchards. Among the methods of IDW interpolation, ordinary kriging, simple kriging, and general kriging, the ordinary Kriging method was introduced as the best method due to lower RMSE (1160.89). At the end, the yield map of the product was created by the usual Kriging method in the GIS software, which can be used along with other data as a prescriptive map for better management of the orchards.

The aim of this study is to develop imaging algorithms to improve the grade of nuts with shell defects such as oily stains, dark stains, adhering hull, damage seed defects, and fungal decay. All these defects indicate the risk of Aflatoxin contamination. Convolutional Neural Networks (CNNs) have become prominent in various fields of machine vision and image classification. In this study, a laboratory hardware setup based on a convolutional neural network is designed for sorting pistachios. The total number of collected data is 958 images, which includes 276 images of defective pistachios and 682 images of healthy pistachios. The classification of healthy and defective images has been accomplished by 3 types of deep convolutional neural networks including Google net, resnet18 and vgg16. The accuracy and specificity of the results obtained using the pre-trained deep neural network models of Google net, resnet18 and vgg16 are 95.8% -97.1%, 97.2% -96.7%, and 95.83% -97.08%, respectively.

Pistachio is one of the most economical cash crops in Iran that is located in arid and semi-arid regions with low soil organic matter and very harmful ions. The enhancement of the organic matter in sufficient quantity and quality plays an important role in agricultural production and soil sustainable management. The application of organic matter promotes physical, chemical, and microbial soil conditions, such as soil aggregate stability, water holding capacity, productivity, and fertility which are essential, particularly in the arid and semi-arid regions of Iran. Municipal solid waste compost (MSWC) and cow manure are two cheap, available, and effective organic materials that can be used in pistachio orchards to improve soil condition and better root growth and more effective nutrient uptake. Gypsum is a chemical material that can replace Ca with Na, especially in saline and sodic soil and cause Na leaching from the soil profile. Sulfur oxidation and gypsum produce acid in the soil and lead to the reduction in pH and the amending of the soil condition. The present study investigated the effects of two organic matters (MSWC and cow manure), two chemical matters (gypsum and sulfur) on some nutrient concentrations in different soil depths (0-20, 20-40, and 40-60 cm depths) and the leaf of pistachio seedlings at the field condition.  A field experiment in a randomized complete block design (split-plot) with three replications was conducted for two years in Izadyaran Company (30 km south of Sirjan, Kerman Province, Iran with hot and dry climates). Treatments were two organic wastes (MSWC and cow manure, 15 Mg ha-1 as the major factor, two chemical amendments (gypsum and sulfur, 10 Mg ha-1) as subplot factor, and soil depths (0-20, 20-40, and 40-60 cm) as the sub-subplot. The organic and chemical matter were poured into the pit of planting and mixed well with soil and a one-year-pistachio seedling was planted (February 2012). In the middle of the summer (August 2013) and at the end of winter (February 2014), plant leaves and soil sampling were done respectively and macro elements’ (Na, K, Ca, Mg, N, and P) concentrations were measured and then statically analyzed with SAS software. MSWC and sulfurs cause the increase of available K in 40-60 cm depth, because of more mobility of K in comparison to other ions. MSW contains K and sulfur through the reduction in pH that leads to MSW decomposing and increases the available K. Sulfur application rises Ca of soil solution more than gypsum because of common ion effect. MSWC and gypsum also enhanced Mg of the soil solution in 20-40 cm depth. Not only MSWC contained Mg but also SO42- solved some parts of solid MgCO3 and increased Mg in soil solution. On the other hand, mineralization of cow manure increased the available P in 20-40 cm depth. None of the treatments were significant on the concentration of soil Na and N. Probably Na was leaching in primary irrigation and mineralized N was quickly absorbed by the plant. Results of this experiment showed that treatments were not significant on the concentration of Na, K, and Mg of pistachio leaves. The application of cow manure increased Ca and P, and cow manure and sulfur increased the N concentration of leaves. The enhanced concentration of elements may be attributed to the increased nutrient levels in cow manure. Sulfur because of sulfuric acid production in soil solution, declined soil pH and led to more nutrient uptake. This phenomenon continuously provides available nutrients in usable form to the plants. These results may be illustrated by the postulated slow release and contiguous storage of nutrients from organic wastes, such as MSWC and cow manure that increased soil nutrient content after a year. Gypsum, with replacing Na with Ca, decreased harmful ions, such as Na and both gypsum and sulfur and because of sulfuric acid production in soil solution, declined soil pH and then led to soil reclamation and more nutrient uptake. The interaction effect of organic and chemical matters’ treatments ,in the same way, can increase some essential nutrients in the soil and plant significantly because of the synergic effect of the organic and chemical soil reclamation.  Results of this study illustrated that it is possible to improve the fertility of saline-sodic soils and plant nutrition with cheap and available organic and chemical materials, such as cow manure and MSWC, gypsum, and sulfur. However, due to the difference in mobility of ions, their concentrations vary in different depths, but with the proper planning, the essential elements can be reached to plants at the right time, especially for a strategic plant like pistachio.

Separation and grading of agricultural products from the production to supply, has notable importance. The separation can be done based on physical, electrical, magnetic, optical properties and etc. It is necessary for any development of new systems to study enough on the properties and behavior of agricultural products.
Some characteristics for separation are size (length, width and thickness), hardness, shape, density, surface roughness, color, speed limit, aerodynamic properties, electrical conductivity, elasticity and coefficient of static friction point.
So far, the friction properties of agricultural products used in the separating process, but the effect of electrostatic charging on static and dynamic coefficients of friction for separation had little attention. The aim of this study was to find out the interactions between electrostatic and friction properties to find a way to separate products that separation is not possible with conventional methods or not sufficiently accurate. In this paper, the separation of close and smiley pistachios by electrostatic charging was investigated.
Kallehghoochi pistachio cultivar has the top rank in production in Iran. Therefore, it was used as a sample.
The experimental design that used in this study, had moisture content at three levels (24.2, 14.5 and 8.1 percent), electric field intensity at three levels (zero, 4000 and 7000 V), speed of movement on the surface at three levels (1300, 2500 and 3300 mm per minute), friction surface (galvanized sheet iron, aluminum and flat rubber) and pistachio type at two levels (filled splits and closed) that was measured and analyzed in completely randomized factorial design.
A friction measuring device (built in Ferdowsi University of Mashhad) used to measure the friction force. It has a removable table that can move in two directions with adjustable speed. The test sample put into the vessel with internal dimensions of 300 × 150 × 25 mm and with wall thickness of 5 mm placed on trolleys. In the bottom of the container a separate aluminum plate was installed as the negative pole of the electric field. The friction plates as a positive pole placed on top of the sample. There were no contact between friction plates and walls of vessel (samples were about 2 to 3 mm higher from the edges of wall).
Frictional force changes due to movement of table, measured and recorded by an accurate load cell. From force-displacement curves, the coefficient of dynamic friction and static coefficient of friction calculated. In general, according to the experimental design, 486 tests were performed.
According to the results of statistical analysis, there is significant interaction affect between pistachios type and electrical field, as well as, the interaction between electrical field and speed, on dynamic coefficient of friction. It means two pistachio types can be separated by electrical charging.
Different physical properties of surface of filled non-splits pistachio nuts (such as corners and edges) and filled splits ones, caused differences in the distribution of electric charge and as a result, its interaction with the electric field were significant.
Changes in dynamic coefficient of friction according to the electric field intensity at different levels of moisture content and speed on the friction surfaces of iron, aluminum and rubber, was drawn in Fig.4, 5 and 6, respectively. These figures reflected the reduction of dynamic coefficient of friction by increasing the movement speed of table.
According to Fig.7, increasing the intensity of the electric field increases the dynamic coefficient of friction. Because this leads to build the opposition charge on samples and galvanized iron sheets, and with increase of electrical field, these charges will rise.
Fig.9 shows different trends of variation of dynamic coefficient of friction against moisture on rubber surface. This chart shows the higher coefficient of friction of filled non-splits samples than filled splits in all cases and shows an increasing trend with increasing humidity.
Table 2 presents the dynamic coefficients of friction in different states on different levels of moisture content. According to this table, the maximum difference was achieved in moisture content of 8% (which is close to the product storage moisture) in rubber surface with field strength of 7000 V and 1300 mm per minute speed. On 14 percent moisture content, the maximum difference was achieved on aluminum surface by 2500 millimeter per minute speed and 7000 V field strength. By the results, on 24 percent moisture content (the moisture close to peeling process) the maximum difference between filled non-splits and filled splits pistachios friction was achieved on aluminum surface, 7000 V electric field strength and 2500 millimeter per minute table speed.
Thus, to have a separation system, the aluminum surface, 7000 V electric field strength and adjustable speed between 1300 to 2500 mm per minute is recommended.

Pistachio nut is one of the most delicious and nutritious nuts in the world and it is being used as a salted and roasted product or as an ingredient in snacks, ice cream, desserts, etc. (Maghsudi, 2010; Kashaninejad et al. 2006). Roasting is one of the most important food processes which provides useful attributes to the product. One of the objectives of nut roasting is to alter and significantly enhance the flavor, texture, color and appearance of the product (Ozdemir, 2001). In recent years, spectral imaging techniques (i.e. hyperspectral and multispectral imaging) have emerged as powerful tools for safequality inspection of various agricultural commodities (Gowen et al., 2007). The objectives of this study were to apply reflectance hyperspectral imaging for non-destructive determination of moisture content and hardness of pistachio kernels roasted in different conditions.

Dried O’hadi pistachio nuts were supplied from a local market in Mashhad. Pistachio nuts were soaked in 5L of 20% salt solution for 20min (Goktas Seyhan, 2003). For roasting process, three temperatures (90, 120 and 150°C), three times (20, 35 and 50 min) and three air velocities (0.5, 1.5 and 2.5 m s-1) were applied. The moisture content of pistachio kernels was measured in triplicate using oven drying (3 gr samples at 105 °C for 12 hours). Uniaxial compression test by a 35mm diameter plastic cylinder, was made on the pistachio kernels, which were mounted on a platform. Samples were compressed at a depth of 2mm and speed of 30 mm min-1. A hyperspectral imaging system in the Vis-NIR range (400-1000 nm) was employed. The spectral pre-processing techniques: first derivative and second derivative, median filter, Savitzkye-Golay, wavelet, multiplicative scatter correction (MSC) and standard normal variate transformation (SNV) were used. To make models at PLSR and ANN methods, ParLeS software and Matlab R2009a were used, respectively. The coefficient of determination (R2), the root mean square error of prediction (RMSEP) and the ratio of the standard deviation of the response variable to RMSEP (known as relative performance determinant (RPD)) were calculated.

Interpretation of hyperspectral data: The results showed that the spectra of the shell, the whole kernel and the internal part of the kernel have different patterns. The internal part of thekernel had 2 peaks at 630 nm and 690 nm, while the shell and the whole kernel had 1 peak at 670 nm and 720 nm, respectively and the peak of the whole kernel was sharper than that of the shell. The highest and lowest intensities were for the internal part of the kernel and the whole kernel, respectively. The spectral slope of the internal part is higher than that of the shell and the whole kernel at 500-700 nm. The effect of different pre-processing techniques and analysis on prediction of pistachio kernels properties: In the absence of pre-processing techniques, low correlation coefficients were observed for prediction of moisture content and hardness. However, with the use of pre-processing techniques, in some models, correlation coefficient and RPD increased and the RMSEP decreased. The results revealed that ANN models would predict moisture content and textural characteristics of roasted pistachio kernels better than PLSR models. Moisture content: ANN models can predict moisture content of roasted pistachio kernels better than PLSR models. In total, PLSR models showed low RPD and R2. For all samples, RPD was lower than 1.5, indicating that the developed models do not give an accurate prediction for moisture content. The best results with ANN method were achieved using a combination of SNV, wavelet and D1 for predicting moisture content with R2 =0.907 and RMSEP=0.179. Hardness: The results indicated that ANN models can predict the hardness better than PLSR models. The best results with PLSR models were achieved using a combination of SNV, wavelet and D1 with R2= 0.643, RMSEP=10.78, RDP= 1.48 and 2 PLSR factors. However, due to high RMSEP and low R2 and RPD, it can be mentioned that prediction of hardness values with ANN model was not sufficiently desirable. However it was better than the PLSR models. The best results with ANN models were achieved using a combination of SNV, wavelet and D2 with R2=0.876 and RMSEP=5.216.

The results of this study showed that employing pre-processing methods causesa decrease in prediction error and improves the quality of the models. ANN models could predict moisture content and hardness of roasted pistachio kernels better than the PLSR models.

Pistachio contamination to aflatoxin has been known as a serious problem for pistachio exportation. With regards to the increasing demand for Raman spectroscopy to detect and classify different materials and also the current experimental and technical problems for measuring toxin (such as being expensive and time-consuming), the main objective of this study was to detect aflatoxin contamination in pistachio by using Raman spectroscopy technique and artificial neural networks. Three sets of samples were prepared: non-contaminated (healthy) and contaminated samples with 20 and 100 ppb of the total aflatoxins (B1+B2+G1+G2). After spectral acquisition, considering to the results, spectral data were normalized and then principal components (PCs) were extracted to reduce the data dimensions. For classification of the samples spectra, an artificial neural network was used with a feed forward back propagation algorithm for 4 inputs and 3 neurons in hidden layer. Mean overall accuracy was achieved to be 98 percent; therefore, non-liner Raman spectra data modeling by ANN for samples classification was successful.

The objective of this study was to evaluate different pistachio hullers and determine the proper harvest time of pistachio nuts for hulling. Three pistachio hulling machines (Helical drum، Helical- blade drum، Rubber drum) at three harvest times and 15 days interval were evaluated. The hulling efficiency، percentage of damaged nuts، faulty hulled nuts and unhulled nuts were measured at each time interval. A factorial experiment was carried out using a randomized complete block design with three replicates. Data were compared using analyses of variance and employing Duncan''s multiple range test. The results showed that the interaction effect of hulling machine type and harvesting time on the hulling efficiency and nut damage in the outlet of hull and nut was significant at the five percent level (p)

Pistachio has a special ranking among Iranian agricultural products. Iran is known as the largest producer and exporter of pistachio in the world. Agricultural products are imposed under different thermal treatments during storage and processing. Designing all these processes requires thermal parameters of the products such as specific heat capacity. Regarding the importance of pistachio processing as an exportable product، in this study the specific heat capacity of nut and kernel of two varieties of Iranian pistachio (Kalle-Ghochi and Badami) were investigated at four levels of moisture content (initial moisture content (5%)، 15%، 25% and 40% w. b.) and three levels of temperature (40، 50 and 60°C). In both varieties، the differences between the data were significant at the 1% of probability; however، the effect of moisture content was greater than that of temperature. The results indicated that the specific heat capacity of both nuts and kernels increase logarithmically with increase of moisture content and also increase linearly with increase of temperature. This parameter has altered for nut and kernel of Kalle-Ghochi and Badami varieties within the range of 1. 039-2. 936 kJ kg-1 K-1، 1. 236-3. 320 kJ kg-1 K-1، 0. 887-2. 773 kJ kg-1 K-1 and 0. 811-2. 914 kJ kg-1 K-1، respectively. Moreover، for any given level of temperature، the specific heat capacity of kernels was higher than that of nuts. Finally، regression models with high R2 values were developed to predict the specific heat capacity of pistachio varieties as a function of moisture content and temperature