Agriculture
Fatemeh Tashakkori; Ali Mohammadi Torkashvand; Abbas Ahmadi; Mehrdad Esfandiari
Abstract
Saffron (Crocus sativus L.) is one of the most expensive crop which is grown in restricted areas of the world. Due to its economic values, some farmers, based on similarities of climatic conditions have cultivated it in some regions of country regardless of land capability and suitability, which sometimes ...
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Saffron (Crocus sativus L.) is one of the most expensive crop which is grown in restricted areas of the world. Due to its economic values, some farmers, based on similarities of climatic conditions have cultivated it in some regions of country regardless of land capability and suitability, which sometimes the result was not satisfactory. Saffron yield prediction based on soil properties enables us to assess the land suitably for cultivation of this valuable plant. For this purpose, 100 soil samples were collected from Vamenan Saffron fields in Golestan province and the soil chemical and physical properties including the percentage of constituents of the mineral part of soil texture (Sand, Silt, Clay), Phosphorus, potassium, Nitrogen, pH, Electrical Conductivity (EC), Organic matter and Calcium Carbonate Equivalent were measured. In addition, the weight of Saffron wet flower (kg.Ha-1) was measured. In the present study, various combinations of soil properties as input were applied and nine models were developed using artificial neural networks and multiple linear regression models for predicting the saffron yield. Performance of the models was validated using Root Mean Square Error (RMSE), Correlation Coefficient (R) and Geometric Mean of Error Ratio (GMER) methods. The results of the correlation analyses showed phosphorus and organic matter are most effective factors in the production of Saffron. Results showed that performance of the models is much different where R2 value varies from 0.45 to 0.89. Comparing the performance of Saffron yield estimation models indicated the optimal model was obtained from the combination of phosphorous, organic matter, potassium and calcium carbonate equivalent as input and values of R2 and RMSE equal to 0.874 and 0.996 kg.ha-1, respectively.Evaluation of model results indicated that the coefficient varied was obtained from 0.45 to 0.89. The best model in saffron yield estimation was obtained when phosphorous, organic matter, potassium and electrical conductivity were as the input, so that values of R2 and root mean square error (RMSE) were obtained 0.891 and 0.89 kg.ha-1, respectively.
Biotechnology and genetics
Seid Mohammad Alavi-Siney; Jalal Saba; Seyyed Siamak Alavikia; Mohammad Reza Azimi
Abstract
In order to investigate the relationship between quantitative traits and ISSR markers, an experiments were carried out under farm and laboratory conditions at Zanjan University. In this experiment, 20 primers of ISSR marker were used and the agronomic traits (including flower number, fresh weight of ...
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In order to investigate the relationship between quantitative traits and ISSR markers, an experiments were carried out under farm and laboratory conditions at Zanjan University. In this experiment, 20 primers of ISSR marker were used and the agronomic traits (including flower number, fresh weight of Stigma, fresh weight of flower, dry weight of Stigma, dry weight of flower, stigma length, saffron yield, corm number, feresh and dry weight of corm, number of leaf, leaf length, leaf width, leaf area, leaf dry weight, biomass, harvest index), physiological traits (transpiration rate, stomatal conductance, photosynthesis) and secondary metabolites (picocrocin, Safranal and Crocin) were measured during the growing season. Three primers of total did not amplified. 17 ISSR primers amplified 133 loci among 20 saffron ecotypes, with an average of 7.82 loci per primer. The highest number of alleles were for the I-8 primer (15 alleles).
Agriculture
Zahra Hosseini- Evari; Ebrahim Izadi Darbandi; Mohammad Kafi; Hassan Makarian
Abstract
A field study with 3 replications based on RCBD was conducted in order to improve the efficacy of some herbicides using adjuvants in the control of broadleaf weeds of saffron. Oxadiazone, oxyfluorfen, rimsulfuron and dicamba+ tritosulfuron herbicides at recommended rates of 500, 700, 10 and 150 a.i. ...
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A field study with 3 replications based on RCBD was conducted in order to improve the efficacy of some herbicides using adjuvants in the control of broadleaf weeds of saffron. Oxadiazone, oxyfluorfen, rimsulfuron and dicamba+ tritosulfuron herbicides at recommended rates of 500, 700, 10 and 150 a.i. ha-1, respectively without adjuvants and in reduced rates 375, 480, 8.75 and 112, respectively were used when they were tank-mixed with and without citogate (0.2% v.v-1) and humix 99 (0.25% v.v-1) as well as a control plot with no herbicide application and hand weeding. Weed species of Polygonum aviculare and Cardaria draba with relative density of 26% and 20.5%, respectively were the dominant weeds in the experimental field. The results showed that hand weeding significantly increased the yield of saffron flower and corm. Application of oxyflurfen and oxadiazone in reduced rates decreased saffron damage while addition of citogate to these herbicides increased the phytotoxicity damage in saffron. Addition of humix to these herbicides had no effect on phytotoxicity damage. Although application of rimsulfuron and dicamba+ tritosulfuron in reduced rates reduced phytotoxicity damage and increased yield of saffron, these herbicides have the potential to damage saffron even at reduced rates. Adding citogate to these herbicides can increase the efficacy of these herbicides in weeds control but considering the potential of these herbicides in damage to saffron, application of these herbicides in saffron fields is not recommended even at reduced doses. Application of oxyflurfen at 480 a.i. ha-1 without adjuvant and tank-mixed with humix were best treatments for use in saffron fields. However, it is also possible to use oxadiazone at 375 a.i. ha-1 to control saffron broadleaf weeds.
Hossien Riahi Modavar; Abbas Khashei-Siuki; Akram Seifi
Abstract
Because of saffron yield sensitivity and the effects of climate on its performance, and also due to the nonlinear nature of crop yield functions, the Artificial Neural Network (ANN) model is employed in this study for prediction and uncertainty analysis of saffron yield in the South Khorasan province ...
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Because of saffron yield sensitivity and the effects of climate on its performance, and also due to the nonlinear nature of crop yield functions, the Artificial Neural Network (ANN) model is employed in this study for prediction and uncertainty analysis of saffron yield in the South Khorasan province based on 20 years of data. The input vector of the ANN model was optimized from 37 parameters through correlation and variance inflation. The optimum architecture of the model was derived as 1-2-4-11 with a sigmoidal activation function based on the results at three stages of training, testing and verification. The root mean square error (RMSE) and mean absolute error (MAE) were equal to 0.3 and 0.5 in the training step and 0.7 and 1 in the test step, respectively. These results indicate that the ANN is a suitable model for predicting saffron yield. Uncertainty analysis based on R2, d-factor and 95%PPU showed that despite use of inadequate data, model prediction showed acceptable prediction bounds and predicted a satisfactorily saffron yield trend. The R2 values were equal to 0.92 and 0.58 in the training and test steps, respectively, which are statistically significant at the P
Other subject about saffron
Ramin Nazarian; Hossein sahabi; Hassan Feizi; Ahmad Ahmadian
Abstract
In order to study the effect of planting density on flower and corm yield of Spanish and Iranian saffron (Crocus sativus L.) types, an experiment was arranged in factorial with randomized complete block design with three replications. This experiment was conducted on the Research Farm of the Faculty ...
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In order to study the effect of planting density on flower and corm yield of Spanish and Iranian saffron (Crocus sativus L.) types, an experiment was arranged in factorial with randomized complete block design with three replications. This experiment was conducted on the Research Farm of the Faculty of Agriculture, Ferdowsi University of Mashhad in 2013-15. The saffron corm type was considered in two levels (a1: Iranian corm and a2: Spanish corm) and the planting densities were in three levels (d1:40, d2:48 and d3:60 corm.m-2). The two year results showed that the effect of different planting density and saffron corm types on the number of flowers, flower fresh and dry weight (stigma + style) and number of replacement corms were significant (P<0.01) while, the effect of corm type on fresh and dry weight of replacement corms was not significant. The highest number of flowers (30.25 No.m-2), flower fresh weight (15.125 g. m-2) and (stigma + style) dry weight (0.16 g.m-2) were obtained in d2 (48 corm.m-2), respectively. Corm type had significant effects on saffron flower characteristics. The highest numbers of flowers (27.21 No.m-2), flower fresh weight (13.58 g.m-2) and (stigma + style) dry weight (0.144 g.m-2) were obtained from Iranian corms (a1), respectively. However, the highest number (222.83 No.m-2), fresh weight (694.92 g.m-2) and dry weight (270.32 g.m-2) of replacement corms were obtained from Spanish corms (a2), respectively. The years had significant effects on saffron flower and corm characteristics as the highest amounts were obtained in second year (Y2), respectively.
Agriculture
Moein Tosan; Amin Alizadeh; Hosein Ansari; Parviz Rezvani Moghaddam
Abstract
Saffron is cultivated in most part of Iran, because of low water requirement and well adaptation to diverse environmental condition. In recent years, for many reasons such as low water requirement, saffron cultivation areas has been increased especially in Khorasan Razavi province. Temperature is one ...
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Saffron is cultivated in most part of Iran, because of low water requirement and well adaptation to diverse environmental condition. In recent years, for many reasons such as low water requirement, saffron cultivation areas has been increased especially in Khorasan Razavi province. Temperature is one of the most important factors in saffron flowering phenomena. The aim of this research was to evaluate the response of saffron to temperature in Khorasan Razavi province counties (Torbat-e-Heydarieh, Gonabad, Nishabour, Sabzevar and Ghoochan). Climatic data (monthly minimum, average, maximum temperatures and diurnal temperature range) and saffron yield data were collected for past 20 years period. The stepwise regression methods were used to remove extra parameters and only keep the most important ones. By using these equations and ArcGIS software zoning, Spline method was find the best for saffron crop zoning. The results of linear regression in Gonabad showed that minimum, maximum and average temperature and also diurnal temperature range in March and April months had the greatest impact on saffron yield. For each of the four indices (the minimum, maximum and average temperature and also diurnal temperature range) the best area for saffron cultivation was the southern part of the province (particularly Gonabad); so by increasing distance from this area to north areas (such as Kashmar, Torbat-e-Heydarieh, Sabzevar, Nishabour, Mashhad and finally Ghoochan) saffron yield reduced by 30 to 50 percent. Therefore, the northern areas of the province had relatively low saffron yield. According to result of this research, saffron yield in Khorasan Razavi province was significantly influenced by temperature parameters. Flowering which basically is the most important stage of plant growth, is directly setting up with temperature.
