Pistachio Yield Research Articles

Random forest, an efficient smart technique for analyzing the influence of soil properties on pistachio yield

Random forest, an efficient smart technique for analyzing the influence of soil properties on pistachio yield

Effect of Arranger of Conductor Tubes of Adjusted Subsurface Drip Irrigation (SSDIadj) on Potassium Absorption and Pistachio Yield at Damghan Region

Effect of Arranger of Conductor Tubes of Adjusted Subsurface Drip Irrigation (SSDIadj) on Potassium Absorption and Pistachio Yield at Damghan Region

Influence of Climatic Factors on Yields of Pistachio, Mango, and Bananas in Iran

The aim of this study was to investigate the impact of climatic variables (minimum temperature, maximum temperature, average precipitation, and precipitation deviation) on the yields of pistachio, banana, and mango in cold, hot–arid, hot–humid, and temperate–humid climates using the Just–Pope function. The Just–Pope function is a relatively new approach in this context. The most effective variables were identified by stepwise regression and the Feiverson algorithm. Data were collected for the period of 1998–2020 and were tested for stationarity. Finally, the coefficients of the Just–Pope function were estimated for the three crops in the four climates. The results showed that the variables affecting pistachio yield were different in each type of climate. Most variables were effective in warm and dry areas, while cropping area, production trend, and lag were effective in cold regions and in hot and humid areas; the maximum deviation and minimum temperature, production lag, cropping area, and production function were significant in hot and dry regions at the 90% level. The Just–Pope function for pistachio, mango, and banana showed that the impact of temperature and average rainfall was region-specific. Based on the results, a 1% increase in rainfall can increase the banana yield up to 0.032 ton/ha. As Iran experiences extensive climatic fluctuations, horticulturists are faced with difficult conditions. Such practices as the use of cultivars that are resistant to temperature and rainfall variations in the regions in order to alleviate the risk of yield variations in orchards are recommended.

A new robust hybrid model based on support vector machine and firefly meta-heuristic algorithm to predict pistachio yields and select effective soil variables

Pistachio production is an economically important crop that grows in arid environments. To predict yield and sustainably manage the use of natural resources such as soil and water, we modelled the effect of soil properties by classification and regression tree, k-nearest neighbors, support vector machines and developed a new hybrid model of support vector machines and the firefly meta-heuristic algorithm. We sampled soils from 124 pistachio orchards in Iran and analyzed them for a range of parameters. Available phosphorus and potassium, exchangeable sodium percentage, soil salinity, gypsum, calcium carbonate and gravel were selected as predictors in the subsequent model based on correlation coefficients, sensitivity analysis and ANOVA hypothesis testing. For modeling, the optimized values for the Kernel function parameters in the hybrid model of ζ, ε and γ were 8.76, 0.001 and 0.99, respectively, while the ideal numerical combinations for p and k parameters in the k-nearest neighbors model were 0.3 and 5, respectively. We checked the difference between the models using paired t-tests which showed that improvements were significant. According to the results, k-nearest neighbors, classification and regression tree and support vector machines algorithms could explain 83, 84 and 88% of the variation of pistachio yield, respectively, but improved to 94% in the hybrid model because it was more able to efficiently capture non-linear relationships. Soil available phosphorus was the most important determinant of pistachio yield, with soil salinity, exchangeable sodium percentage, potassium, gypsum, calcium carbonate and gravel ranked in order of decreasing importance. These outputs can help planners and farmers to better manage soil properties to increase pistachio yield and sustainable production.

Penetration and Development of Meloidogyne Javanica on Four Pistachio Rootstocks and their Defense Responses.

Pistachio yield is annually reduced due to root-knot nematode infections. In order to evaluate its resistance to Meloidogyne javanica, three domestic pistachio rootstocks, namely, Badami, Ghazvini and Sarakhs, and a wild pistachio, Baneh (Pistacia atlantica subsp. mutica), were selected. Their response to the nematode infection was evaluated based on different plant and nematode indexes, 120 days post-inoculation (dpi). The penetration and development rate of nematode in roots of these four pistachio rootstocks were evaluated at different time points by acid fuchsin staining. Based on the measured indexes, Badami, Ghazvini, Sarakhs, and Baneh rootstocks ranked as susceptible, moderately resistant, moderately resistant, and resistant, respectively. The penetration rate of second-stage nematode juveniles (J2) into four rootstocks was discussed. The first "midstage" or swollen juveniles appeared at 4 dpi but to a lesser extent in Ghazvini, Sarakhs, and Baneh cultivars. The first females were seen in Badami at 21 dpi, in Ghazvini and Sarakhs at 35 dpi, and in Baneh at 45 dpi. Three types of defense responses were distinguished and characterized in the examined pistachio rootstocks: (i) a hypersensitive response (HR)-like reaction in the cortex in Ghazvini, Sarakhs, and Baneh root tips at 4 dpi and 6 dpi; (ii) an HR response, degrading J2 which induce giant cells in the vascular cylinder of all rootstocks, at 6 dpi and 10 dpi; and (iii) an HR response, degrading females and giant cells in the vascular cylinder of all rootstocks at 15 dpi onward. These observations open new fields of study in breeding programs of this crop.

Effects of Deficit Irrigation, Rootstock, and Roasting on the Contents of Fatty Acids, Phytoprostanes, and Phytofurans in Pistachio Kernels.

Pistachio (Pistacia vera L.) is a drought-tolerant species grown under the semiarid conditions of the Mediterranean basin. For this reason, it is essential to make an exhaustive quantification of yield and quality benefits of the kernels because the regulated deficit irrigation will allow significant water savings with a minimum impact on yield while improving kernel quality. The goal of this scientific work was to study the influence of the rootstock, water deficit during pit hardening, and kernel roasting on pistachio (P. vera, cv. Kerman) fruit yield, fruit size, and kernel content of fatty acids phytoprostanes (PhytoPs) and phytofurans (PhytoFs) for the first time. Water stress during pit hardening did not affect the pistachio yield. The kernel cultivar showed a lower oleic acid and a higher linoleic acid contents than other cultivars. Kernels from plants grafted on the studied rootstocks showed very interesting characteristics. P. integerrima led to the highest percentage of monounsaturated fatty acids. Regarding the plant oxylipins, P. terebinthus led to the highest contents of PhytoPs and PhytoFs (1260 ng/100 g and 16.2 ng/100 g, respectively). In addition, nuts from trees cultivated under intermediate water deficit during pit hardening showed increased contents of the 9-series F1-phytoprostanes and ent-16(RS)-9-epi-ST-Δ14-10-phytofuran. However, roasting of pistachios led to PhytoP degradation. Therefore, plant cultivar, deficit irrigation, rootstock, and roasting must be considered to enhance biosynthesis of these secondary metabolites. New tools using agricultural strategies to produce hydroSOS pistachios have been opened thanks to the biological properties of these prostaglandin-like compounds linking agriculture, nutrition, and food science technology for further research initiatives.

Studying the relationships between nutrients in pistachio leaves and its yield using hybrid GA-ANN model-based feature selection

Sustainable and reliable management requires special attention to factors affecting crop yield. In the present study, a hybrid model of genetic algorithm and artificial neural network (GA-ANN) was employed to recognize the importance of nutrients in pistachio yield. One hundred seventy-five points in different pistachio orchards of Rafsanjan and Anar regions, Kerman province, the southeast of Iran, were identified and selected for leaf sampling and yield measurement. The concentration of phosphorus (P), potassium (K), iron (Fe), zinc (Zn), copper (Cu), manganese (Mn), calcium (Ca) and magnesium (Mg) was determined. The hybrid GA-ANN model was implemented in MATLAB software, after statistical analysis and multivariate regression modeling. The results showed that the correlation and linear multiple regression analysis could not justify the variations of pistachio yield in relation to leaves' nutrients concentration. The lowest error of the hybrid GA-ANN model was observed by five features including concentrations of K, Mg, Fe, Zn and Cu. Sensitivity analysis of ANN indicated that the highest relative importance for predicting pistachio yield was related to Cu (34.6%), K (28.2%) and Fe (26.1%). The GA-ANN model was able to solve complex and multi-dimensional problems. The accurate and careful interpretation of the results, obtained from this approach can provide a good insight for optimum farm management planning.

Factors Affecting Attitude of Iranian Pistachio Farmers toward Privatizing Extension Activities: Case of Kerman Province

Agricultural extension, as an informal educational system, is one of agricultural development tools that lean on human capitals. Inefficiency of public bureaucracy on the one hand, and managerial problems on the other hand, as well as neglecting real needs of beneficiaries in planning, have determined responsible to transfer administrative tasks to the private sector and reduce government''s tenure. This survey was conducted in Kerman as the first ranked province of pistachio production in Iran to investigate attitudes about extension private services among pistachio farmers. A questionnaire was used as the research tool for data collection. Face validity of the questionnaire was verified by extension experts and Cronbach''s alpha computation showed that reliability of the questionnaire was between 0.8 and 0.89. The study ran among pistachio farmers of five counties (Rafsanjan, Sirjan, Zarand, Kerman and Ravar). Random cluster sampling method, with a sample size of 382 respondents was applied. Finally, the collected data were analyzed using SPSS software. Results revealed that several factors such as education level, participating in extension activities, innovation acceptance, membership in associations, cosmopolitan, positive attitude toward knowledge and information, applying numerous information resources, pistachio yield per hectare, area of the pistachio garden and satisfaction of the private consultants had relation with attitude toward privatization of extension. Also, the level of participation in extension activities and attitude toward the public extension could explain 24.8 percent of changes in attitude toward private extension.

Effect of Exogenous Application of L-arginine and Sodium Nitroprusside on Fruit Abscission and Physiological Disorders of Pistachio (Pistacia Vera L.) Scions

Pistachio yield are often negatively affected by some physiological problems such as abscission of inflorescence buds and fruits, deformed or blank nuts, and non-split shells. In the present study the effect of exogenous application of arginine (Arg) (a substrate for nitric oxide (NO) synthase) and sodium nitroproside (SNP), as a NO-donor was investigated on yield production, fruit and inflorescence buds abscission, and physiological parameters of Pistacia vera. The experiment was conducted in randomized complete block design with factorial structure in a commercial pistachio orchard. Factors were included two levels of Arg (0.5 and 1 mM), two levels of SNP (50 and 100 μM) and their combination applied at two distinct time; one week before full bloom (first stage) and five weeks after full bloom (second stage). Comparing to SNP-treated trees, Arg was more effective on growth and physiological parameters of shoots and on fruit and inflorescence buds abscission, and on fruit parameters such as split and non-split shells, blank nuts, number of nuts per ounce. Effects of these treatments were considerably depending on the time of application and the concentrations of applied compounds. It is proposed that the effects of Arg and SNP may be related to the NO signaling and polyamines production.

Daily and Seasonal Pistachio Evapotranspiration in Saline Condition: Comparison of Satellite-Based and Ground-Based Results

This study was conducted in 2015 to estimate pistachio (Pistacia vera L.) water use in Marvast region, central Iran. Daily and seasonal pistachio actual evapotranspiration (ETa) was first estimated by running the surface energy balance algorithm for land (SEBAL) model, using 12 Landsat 8 satellite images and other ancillary data. Finally, SEBAL estimates of daily and seasonal water use over three experimental sites of pistachio orchards were compared against ones based on performing water balance analysis for the top 150 cm of the soil layer. For this purpose, a simple funnel-shaped device was made and used to collect the beneath rootzone drainage water and determine the leaching fraction (LF) as well as deep percolation at three scattered points across the sub-sections of each experimental site. The results reveal that the LF varies from 0.16 to 0.34, leading to deep percolation from 95.0 to 334.0 mm of the irrigation water. Eventually, the differences between ground-based and SEBAL-based pistachio ETa were 11% (ranged from 5.7 to 14.0%) and 10% (ranged from 7.1 to 16.4%) for daily and seasonal time scales, respectively. Based on the obtained results, more than 60% of Marvast pistachio orchards have seasonal water use of 410.0 to 680.0 mm (with the average of 594.3 mm), while the cumulative ETo and cumulative pistachio ETc of the same period were 1558.0 mm and 920.0 mm, respectively. In other words, Marvast pistachio trees extract less water from the soil compared with their potential water demands. This is due to the effect of salinity on reducing evapotranspiration rate as well as deficit irrigation of pistachio trees in the water scarce area of Marvast region. In any case, the difference between pistachio ETc and ETa is reflected in declination of the pistachio yield.

Effects of soil properties, water quality and management practices on pistachio yield in Rafsanjan region, southeast of Iran

In recent decades, the quantity and quality of irrigation water have been reduced due to a significant increase in pistachio cultivation and uncontrolled exploitation of groundwater resources as well as reduction in rainfall precipitation. Therefore, agricultural producers, researchers and policy makers need to pay more attention to appropriate land management as an important strategy to achieve greater yield per unit area and to use soil and water resources in an optimal way. So, the present study was conducted to model the relationships between pistachio yield and soil, water and management variables in Rafsanjan region, the southeast of Iran. One hundred and ninety nine mature orchards were selected and sampled in such a way that an acceptable range of soil and water quality and management were included. The data set consisted of a dependent variable (pistachio yield) and 67 independent variables including soil, water and management characteristics. The results of hybrid genetic algorithm-artificial neural network (GA-ANN) showed that the lowest error was related to the case in which the 23 features were used in modeling. Then, stepwise multiple linear regression (MLR) and artificial neural network (ANN) techniques were applied to estimate pistachio yield. The results indicated that MLR could explain only 28% of the pistachio yield variation, whereas its accuracy increased when the data became more homogeneous via geographically dividing the study area into four parts with the highest densities of pistachio orchards. ANN-based model had a 90% accuracy to predict pistachio yield in the study area. Thus, an accurate estimation of pistachio yield could be achieved by reducing the data dimensionality using feature selection techniques and modeling with ANN. As the models were highly sensitive to irrigation water features, special attention should be paid to new irrigation methods and management practices as an effective strategy to minimize water losses and increase water use efficiency.

Soil suitability analysis and evaluation of pistachio orchard farming, using canonical multivariate analysis

Soil properties and crop yields are strongly interrelated. Identifying the relation can leads to better management of cultivation and land suitability evaluation. Some difficulties related to statistically analyzing the soil properties, especially in relation with the crops and water, arises from the fact of their high variability and intercorrelation, which causes the multicollinearity problems. Adequate choice and use of multivariate statistical methods is appropriate to approach these areas of investigation. This study deals with the relations and interdependencies of soil physio-chemical attributes and pistachio (Pistacia vera L.) yield, as the most important commercial nut crop of Iran and one of the most worldwide. The study area is the pistachio orchard farms of Anar region in Rafsanjan County, Kerman, Iran; and the employed canonical multivariate methods are redundancy analysis (RDA) and discriminant analysis (DA). Six orchards were chosen with the same managerial procedures, pistachio cultivars (Owhadi) and tree ages. But, due to the aim of distinguishing influential soil properties, the vegetative growth and pistachio yields were different. Each orchard then was divided to two suitable and unsuitable parts, based on the actually measured yields. In each part, three replicates of soil sampling (in to depths of 0–50 and 50–100 cm) and three trees for eachever were considered in order to determining the pistachio yields. To explore the interrelationships between soil properties, orchard suitable/unsuitable parts and yields and distinguishing misclassified orchards based on the yield parameter and vegetative growth, the canonical multivariate RDA was employed. Results showed a relatively strong correspondence between yield and soil properties. Clay, EC, K and B were negatively related and sand and CaCO3 significantly positive correlated and altogether explained 100% of yield total variation. The multivariate DA then adopted to reclassify the orchard samples into two performance groups based on the variations of soil attributes. Results indicated two influential variables of clay and EC in distinguishing land suitability for pistachio farming, were able to classify 80.5% of orchards correctly (73.7% to suitable orchards and 88.2% to unsuitable ones). Overally, results showed a significant difference between soil properties in suitable and unsuitable areas, as well as a significant relationship between some soil properties and the yield of pistachio. Findings, applicably recommend that site suitability for optimal pistachio cultivation can satisfactorily be evaluated using only few and easy-determining soil properties, throughout canonical discriminant functions of appropriate multivariate analysis.

The evaluation of winter kaolin clay and dormant oil applications on chill accumulation and yield in the California pistachio (Pistacia vera) cultivars ‘Kerman’ and ‘Peters’

The California pistachio cultivars 'Kerman' and 'Peters' have an estimated requirement of 58 and 60 chill portions, respectively. In California's Central San Joaquin Valley, the recent combination of warmer winter temperatures and sharply decreased fogs have resulted in a reduction of winter chill accumulation. In 2015 and 2016, kaolin clay was applied to dormant pistachio trees attempting to increase chill accumulation by reflecting radiant heat. Four treatments including kaolin clay, kaolin clay plus 470 dormant oil, 470 dormant oil, and an untreated control were made to nine year old pistachio trees. Kaolin clay applications (33 kg ha-1) were applied twice with the first application occurring after leaf drop in mid-December and the second occurring in early-January. A 6% 470 dormant oil solution was applied at 150 L ha-1 on February 6th, 2016. Treatments were approximately 1.9 ha in size and were replicated four times utilizing a randomized complete block design. Temperature sensors measuring external wood temperature on the north and south side were installed on a single tree in multiple blocks. Yield was determined for each plot and evaluated for size and quality. Local weather station measurements indicate that adequate chill was received in 2015-2016. Never-the-less, wood surface temperatures in kaolin treated trees were lower than the untreated control, producing an increase in chill portion accumulation by ~15%. Yield, however, was higher in the 470 dormant oil than in the kaolin clay or untreated control (3,330 kg ha-1 vs. 2,796 and 2,774 kg ha-1, respectively). Results suggest that kaolin clay may be useful in increasing chill portion accumulation, but only if applied early in the dormant period. Our results also confirmed earlier reports that dormant oil increases pistachio yield in marginal to adequate chill years. Both techniques should be utilized as tools to help mitigate variable climate within pistachio orchards.

Identifying Soil and Plant Nutrition Factors Affecting Yield in Irrigated Mature Pistachio Orchards

ABSTRACTThe main objective of this study was to evaluate the potential use of a hybrid Genetic Algorithm-Artificial Neural Network (GA–ANN) method for predicting pistachio yield and for identifying the determinant factors affecting pistachio yield in Rafsanjan region, Iran. A total of 142 pistachio orchards were selected randomly and soil samples were taken at three depths. Besides, water samples and leaves from branches without fruit were taken in each sampling point. Management information and pistachio yields were achieved by completing a questionnaire. Primarily, 58 variables affecting pistachio yield were measured, and then 26 out of them were selected by minimizing mean square error (MSE) using a feature selection (FS) method. The results showed that the accuracy of the method was acceptable. Furthermore, the sensitivity analysis showed that the main determinant features affecting the pistachio yield were the irrigation water amount, leaf phosphorus, soil soluble magnesium, electrical conductivity (EC), and leaf nitrogen.

Voice-Controlled and Wireless Solid Set Canopy Delivery (VCW-SSCD) System for Mist-Cooling

California growers in the San Joaquin Valley believe that climate change will affect the pistachio yield dramatically. As the central valley fog disappears, insufficient dormant chill accumulation results in poor flowering synchrony, flower quality, and fruit set in this dioecious species. We have developed a novel, user-friendly, and low-cost Voice-Controlled Wireless Solid Set Canopy Delivery (VCW-SSCD) system to increase bud chill accumulation with evaporative cooling on sunny (winter) days. This system includes: (i) an automated solid-state canopy delivery (SSCD) system; (ii) a wireless weather-, crop-related data acquisition system; (iii) a Voice-Controlled (VC) system using Amazon Alexa; (iv) a mobile application to visualize the collected data and wirelessly control the SSCD system; and (v) a smart control system. The proposed system was deployed and evaluated in a commercial pistachio orchard in Bakersfield, CA. The system worked well with no reported errors. Results demonstrated the system’s ability to cool bud temperatures in a low relative humidity climate. At an ambient temperature of 10–20 °C, bud temperatures were lowered 5–10 °C.

A genome-wide transcriptome map of pistachio (Pistacia vera L.) provides novel insights into salinity-related genes and marker discovery

BackgroundPistachio (Pistacia vera L.) is one of the most important commercial nut crops worldwide. It is a salt-tolerant and long-lived tree, with the largest cultivation area in Iran. Climate change and subsequent increased soil salt content have adversely affected the pistachio yield in recent years. However, the lack of genomic/global transcriptomic sequences on P. vera impedes comprehensive researches at the molecular level. Hence, whole transcriptome sequencing is required to gain insight into functional genes and pathways in response to salt stress.ResultsRNA sequencing of a pooled sample representing 24 different tissues of two pistachio cultivars with contrasting salinity tolerance under control and salt treatment by Illumina Hiseq 2000 platform resulted in 368,953,262 clean 100 bp paired-ends reads (90 Gb). Following creating several assemblies and assessing their quality from multiple perspectives, we found that using the annotation-based metrics together with the length-based parameters allows an improved assessment of the transcriptome assembly quality, compared to the solely use of the length-based parameters. The generated assembly by Trinity was adopted for functional annotation and subsequent analyses. In total, 29,119 contigs annotated against all of five public databases, including NR, UniProt, TAIR10, KOG and InterProScan. Among 279 KEGG pathways supported by our assembly, we further examined the pathways involved in the plant hormone biosynthesis and signaling as well as those to be contributed to secondary metabolite biosynthesis due to their importance under salinity stress. In total, 11,337 SSRs were also identified, which the most abundant being dinucleotide repeats. Besides, 13,097 transcripts as candidate stress-responsive genes were identified. Expression of some of these genes experimentally validated through quantitative real-time PCR (qRT-PCR) that further confirmed the accuracy of the assembly. From this analysis, the contrasting expression pattern of NCED3 and SOS1 genes were observed between salt-sensitive and salt-tolerant cultivars.ConclusionThis study, as the first report on the whole transcriptome survey of P. vera, provides important resources and paves the way for functional and comparative genomic studies on this major tree to discover the salinity tolerance-related markers and stress response mechanisms for breeding of new pistachio cultivars with more salinity tolerance.

Temperature-related Variables Associated with Yield of ‘Kerman’ Pistachio in the San Joaquin Valley of California

Information on how annual pistachio yield is affected by air temperature (Ta) during the winter and growing season is lacking. Timely advance knowledge of the magnitude of the yield of the California pistachio harvest would be beneficial for the pistachio industry for efficient allocation of harvest and postharvest resources, such as personnel, harvesting machinery, trucks, processing facility capacity, crop storage facilities, and for making marketing decisions. The objective of this study was to identify parameters, especially Ta variables and time periods, calculated from Ta data during the previous fall, winter, spring, and summer, that were associated most closely with fall nut-crop yield. The premise of this study was that sequential, historical yield records could be regressed against a number of Ta-derived variables to identify Ta thresholds and accumulations that have value in explaining past and predicting subsequent nut yield. Of the 27 regression variables examined in this study, the following, which were all negatively correlated with subsequent yield, explained the greatest proportion of the variability present in predicting yield of ‘Kerman’ pistachio: yield of the previous-year harvest, hourly Ta accumulations above 26.7 or 29.4 °C from the time period between 20 Mar. and 25 Apr., hourly Ta accumulations below 7.2 °C from 15 Nov. to 15 Feb., and hourly Ta accumulations above 18.3 °C from 15 Nov. to 15 Feb.

Boron affects the yield and quality of nonirrigated pistachio (Pistacia vera L.) trees

In Turkey, more than 95% of the pistachio (Pistacia vera L.) orchards are not irrigated. Therefore, a 4-year field trial was conducted to determine the effect of Tarimbor fertiliser (containing 18.5% boron [B]) on the yield, quality, and B content of two pistachio cultivars ('Uzun' and 'Siirt') planted under nonirrigated conditions. Tarimbor was applied to the pistachio trees as a soil application (0, 200, 400, and 600 g/tree) and a foliar spray (0%, 0.1%, 0.2%, and 0.3% w/v, using a tractor-mounted sprayer at the 'early bud break' stage and the 'fully leafed out' stage). Both the soil and foliar applications of Tarimbor had a significant effect on the pistachio yield, quality, and B content compared with the control. However, the foliar application resulted in greater improvements in the B content of leaves in both cultivars and the split nut ratio and kernel ratio in 'Uzun'. The greatest increases in yield were observed for the 0.3% foliar application for 'Uzun' (30%) and the 200 g/tree soil application for 'Siirt' (59%). In terms of quality, the application of Tarimbor appeared to have a greater effect on 'Uzun' than on 'Siirt'. No vegetative symptoms of B toxicity were observed in either cultivar when high concentrations of B were applied. Thus, Tarimbor could be used effectively as a foliar spray to enhance the B levels in the leaves of pistachio trees grown under nonirrigated conditions.

Energy inputs-yield relationship and sensitivity analysis of pistachio (Pistacia vera L.) production in Markazi Region of Iran

Pistachio is considered as an important agricultural commodity in Iran and ranks top amongst all exported agricultural products. Conducting an overall energy audit and economic analysis of pistachio production can provide useful information to help implement management strategies for improving energy efficiency. A study was conducted during 2009 and 2010 to evaluate the overall energy inputs and outputs and to perform an economic analysis of pistachio production in the Iranian province of Markazi. The results revealed that the total energy input for pistachio production was 54305 MJ ha-1. Electricity, followed by diesel fuel and nitrogen fertilizer application were the highest contributors to energy input in pistachio orchards. The contribution of direct energy was higher than indirect energy and share of non-renewable energy was more than renewable energy. Net energy, energy use efficiency, energy productivity and specific energy were 7522 MJ ha-1, 0.86, 0.08 kg MJ-1 and 13.69 MJ kg-1, respectively. Econometric model based on Cobb-Douglas function indicated that impacts of electricity, diesel fuel and chemical fertilizer energy inputs on pistachio yield were positive while the impact of machinery was negative. The marginal physical productivity (MPP) value for diesel fuel was the highest among other variables, followed by energy inputs related to the chemicals and irrigation water. The results revealed that production of pistachios in Markazi Province, under current management practices, are not energy efficient and efforts should be made to improve energy use efficiency.

TREND OF SOIL SALINIZATION AND ITS EFFECT ON PISTACHIO YIELD OF RAFSANJAN ORCHARDS

ISHS XXVIII International Horticultural Congress on Science and Horticulture for People (IHC2010): International Symposium on the Challenge for a Sustainable Production, Protection and Consumption of Mediterranean Fruits and Nuts TREND OF SOIL SALINIZATION AND ITS EFFECT ON PISTACHIO YIELD OF RAFSANJAN ORCHARDS