نشریه زراعت و فناوری زعفران
سال پنجم شماره 4 (پیاپی 18، زمستان 1396)

Studies that investigated the impact of organic fertilizers (manure, compost and biological fertilizers) and agronomical practices (density, method, date and depth of planting) on saffron yield have a long history in Iran. Due to the distribution and inconsistency in the results obtained from different studies, a meta-analytic approach was used in the current study. for this aim, 47 organic fertilizers studies and 44 agronomical practices studies were selected from 202 gathered studies and analyzed. The criteria for the selection of studies were the adequacy of data for the present meta-analysis. Among the individual fertilizer studies, manure fertilizer had the highest impact on saffron dry weight (g= 1.493) at 95% confidence interval. Average amount, 40 to 50ton/ha of cow manure, 20 to 30ton/ha of compost that is used as a combination with Biofertilizer (Nitroxin with Nitrogen-fixing bacteria) were more effective than higher amounts of these fertilizers will be alone. Among the agronomical practices studies, plant density had the highest and depth of planting had the lowest effect size on economical yield and number of flower. The optimal density for maximum yield was 50-100 corm per (m2), optimal consumed weight average 9-12 ton per hectare observed, optimal weight of any corm was 10-20 (g). Among planting methods, row-mass method was the best optimal (inter-planting was 20 cm and intra-planting 10 cm). The best planting dates was the end of May and the first decade of Jun. Optimal planting depth was 15-20cm. Homogeneity between organic fertilizers studies was accepted and the homogeneity between agronomical practices except depth of planting studies was accepted. This heterogeneity was caused by factors such as age of farms and different regions that had the most impact on heterogeneity and effect size. The present meta-analysis aims to provide a better understanding of agronomical and fertilizers management and offer the best possible management for this crop.

This study is aimed at investigating the effect of using humic, bio and nano fertilizers and levels of nitrogen fertilizers in flower yield of saffron (Crocus sativus L.) at the University of Torbat Heydarieh research farm located in Zaveh in 2014-2015. Treatments consisted of three levels of nitrogen application and use of fertilizer sources as the main factor, including Bioumik, Super Humic, combined Super Humic and Bioumik, Humi Ful, Nitrokara and no fertilizer as sub plots as split plot based on randomized complete block design with 18 treatments and three replications. Analysis of data showed that the effect of year and fertilizer sources on all traits measured was significant. The effect of nitrogen treatments was significant (at 1%) except on number of flowers, dry style, mean dry weight stigma, and mean dry weight. Fertilizer sources increased all measured traits significantly. Application of Biomic increased petals and sepals dry weight (736.34 g/m2) by 46.78% in comparison with the control (464.19 g/m2). The highest dry weight stigma (524.2 g/m2) was seen in Super Humic Bioumik treatment compared to the control group (443.1 g/m2). Super Humic treatment increased dry weight stigma by 86.49% relative to control. It seems that the use of humic, bio and nano fertilizers has a good effect on saffron performance.

In order to investigate the effects of different types of nano-fertilizers on some of the physiological characteristics of saffron (i.e. antioxidant enzymes, reducing and non-reducing sugars, photosynthetic pigments, total phenol content and relative water content of leaf) the current experiment was conducted at Malayer University during 2014-2015 growing season. The study was performed based on randomized complete block design (RCBD) with six treatments and three replications. The experimental treatments were control and five different types of nano-fertilizers (iron: Fe, boron: B, manganese: Mn, potassium: K and zinc: Zn). The effects of experimental treatments on relative water content, protein and total phenol content, reducing and non-reducing sugars were significant but there was no significant effect on chlorophyll b, leaf carotenoids, Catalase and Proxidase activity. Although the difference between nano-fertilizers and control treatment for chlorophyll a and also total chlorophyll was not significant but the highest amount of chlorophyll a (1.53 mg.g-1 Fw) measured in Fe treatment and the lowest amount (0.93 mg.g-1 Fw) observed in Mn treatment. Based on results, all of the experimental treatment increased the relative water content of leaf comparing to control. The highest amount of total phenol content (0.27 mg.g-1 FW) with 10.5% increase compared to control observed in Mn treatment and just the difference of this treatment with control treatment was significant. By application of Zn, Mn, K and B nano-fertilizer leaf protein content comparing to control treatment significantly increased whereas the difference between Fe and control wasn’t significant. The highest concentration of leaf protein (1.56 mg.g-1 Fw) with 12% increase compared to control treatment observed in K and B treatments whereas the lowest concentration (1.36 mg.g-1 Fw) with 3% decrease compared to control was related to Fe treatment. The different response of studied characteristic to application of various nano-fertilizer showed that different physiological traits hadn’t the similar sensitivity to all of mineral nutrients therefore application of entire nano-fertilizers with the same concentration isn’t scientifically recommendable .

3Associated professor, Department of Agricultural Engineering Research, Khorasan Razavi Agricultural and Natural Resources Research and Education Center, AREEO, Mashhad, Iran
4Ph. D student of öDept. of Biosystems Engineering, Faculty of Agriculture, Ferdowsi University of Mashhad
˜یÏå [English]
Separation of stigma from petals is one of the required tasks in saffron production. The mechanical separation of saffron flowers may be performed through the following steps: I) singulation of the flowers ii) aligning the flowers iii) cutting the style (Konje) and iv) separating the stigma from the petals. Because of the importance of saffron flower separation, a prototype device was constructed in this project for singulating and aligning of saffron flowers, prior to the cutting operation. This device can also be installed to work with other cutting and separating equipment and produce on an industrial scale. A pickup vacuum cylinder was used for singulating the flowers and an inclined V-shaped surface was employed for aligning of saffron flowers. The constructed apparatus was evaluated from the standpoint of singling efficiency and losses. For this purpose, three types of saffron flowers (buds, open short tail and long tail), three rotational speeds of pickup cylinder (6, 12 and 21. 5 rpm), three levels of suction (30, 70 and 100 mm Hg), and four different inner diameters of finger’s nozzle (2, 3, 4 and 5 mm) were used with three replications. The results of analysis on the constructed device showed that the highest efficiency (75%) is observed for short tailopen saffron flowers with 5 mm inner diameter of sucking nozzles, suction of 100 mm Hg and the rotational speed of 6 rpm. To evaluate the performance of flower aligning, 100 saffron flowers with an average length of 5 cm were selected and tested with 5 replications. The average aligning with the correct direction obtained was equal to 84%.

Yield prediction for agricultural crops plays an important role in export-import planning, purchase guarantees, pricing, secure profits and increasing in agricultural productivity. Crop yield is affected by several parameters especially climate. In this study, the saffron yield in the Khorasan-Razavi province was evaluated by different classification algorithms including artificial neural networks, regression models, local linear trees, decision trees, discriminant analysis, random forest, support vector machine and nearest neighbor analysis. These algorithms analyzed data for 20 years (1989-2009) including 11 climatological parameters. The results showed that a few numbers of climatological parameters affect the saffron yield. The minimum, mean and maximum of temperature, had the highest positive correlations and the relative humidity of 6.5h, sunny hours, relative humidity of 18.5h, evaporation, relative humidity of 12.5h and absolute humidity had the highest negative correlations with saffron cultivation areas, respectively. In addition, in classification of saffron cultivation areas, the discriminant analysis and support vector machine had higher accuracies. The correlation between saffron cultivation area and saffron yield values was relatively high (r=0.38). The nearest neighbor analysis had the best prediction accuracy for classification of cultivation areas. For this algorithm the coefficients of determination were 1 and 0.944 for training and testing stages, respectively. However, the algorithms accuracy for prediction of crop yield from climatological parameters was low (the average coefficients of determination equal to 0.48 and 0.05 for training and testing stages). The best algorithm i.e. nearest neighbor analysis had coefficients of determination equal to 1 and 0.177 for saffron yield prediction. Results showed that, using climatological parameters and data mining algorithms can classify cultivation areas. By this way it is possible to identify areas that have similar climate to prone areas and recognize suitable areas for cultivation.

In terms of quality and quantity, Iranian saffron has a considerable position at the international level and by taking advantage of the existing capacity; we can significantly increase the export earnings from it. On the other hand, sales forecasting based on time series analysis is s a very important element for the designing and implementing of marketing strategies in the international arena. However, the conventional approaches to forecasting, by ignoring the linear (or nonlinear) structure of data, do not provide accurate results. Therefore, the main objective of this study is to design a hybrid model consisting of two methods, artificial neural networks (ANN) and autoregressive integrated moving average (ARIMA), in order to overcome the deficiencies and the use of the unique features of the each of these methods. Using the data related to the export of Iranian saffron during the period 1904-2013, the results of the study showed that the ARIMA–ANN hybrid model is stronger and better performance than ARIMA and ANN individual models in order to forecasting of Iranian saffron export. Therefore, given the considerable performance ARIMA–ANN hybrid model, the use of this model is recommended in setting strategies related to the export and also in the forecasting of the forecasting of time series variables.

Saffron is one of the most important economic plants in the world that also has many pharmaceutical applications. Genus Crocus L. (Saffron) with about 90 species of the Iridaceae family in the northern hemisphere, especially in West Asia and Iran are scattered. The present study was to investigate the antimicrobial activity of extracts of various parts such as cover of corm, corm, perianth and stigma of the variety of saffron (C. sativus var. Haussknechtii) on some pathogenic microorganisms (Bacillus cereus, Enterococcus faecalis, Escherichia coli , Pseudomonas fluorescens, Salmonella typhimurium, Staphylococcus aureus) extrusion. Plant specimens were collected from four different habitats of Kermanshah province and then were identified in the herbarium of Razi University. After preparing raw plant extract four different parts of the plants (cover of corm, corm, perianth, stigma) by soaking (maceration) were extracted. Microbial tests using minimum inhibitory concentration (MIC) of the broth micro-dilution method were determined. The results of analysis by statistical tests showed a significant correlation (001/0