Document Type : Research Paper


1 Ph.D. Student, Department of Agronomy and Crop Breeding, Faculty of Agriculture, Shahrood University, Shahrood - Iran

2 Associate Professor, Department Agronomy and Crop Breeding, Faculty of Agriculture, Shahrood University, Shahrood - Iran

3 Assistant Professor, Department Agronomy and Crop Breeding, Faculty of Agriculture, Shahrood University, Shahrood - Iran


Nitrogen (N) affects adversely the tobacco yield quantity and quality as it increases yield, Chlorine and nicotine contents, but decrease potassium content. This experiment was aimed at optimization of (the balance between) N concentration in leaf, stem and root to increase both yield quantity and quality (high potassium, low Chlorine and medium nicotine contents) using artificial neural network. Two field experiments based on complete block design with three replications were conducted in Tirtash and Urmia tobacco research centers. Treatments were factorial arrangement of two N sources (urea and nitrate ammonium) and four application patterns (basal, 2/3 basal and 1/3 after initiation of rapid growth (AIRG), 1/2 basal and 1/2 at AIRG, 1/3 basal and 2/3 at AIRG). The N concentration of leaf, stem and root (model inputs) was measured in 30, 50, 70, 85 and 100 days after transplanting. After harvesting, the quantity of cured leaf and its Cl, K and nicotine content (model outputs) were also determined. The results indicated that a model with one hidden layer and configuration of 15-15-4 is appropriate and there were no significant different between two N sources. The best pattern was use of nitrate ammonium in 2/3 basal and urea 1/3 basal.  The average value of optimized N concentration was 3.06, 2.42 and 1.5 percent for leaf, stem and root, respectively. These optimized concentrations can lead to potential increase in quality and quantity of tobacco which should be taken into consideration by breeders and agronomists.


1 . Akehurst BC (1981) Tropical Agriculture Series. Longman. New York. Pp. 630- 635.
2 . Allen S and Raven JA (1987) Intracellular PH regulation in Ricinus communis grown with ammonium or nitrate as N source: the role of long distance transport. Journal of Experimental Botany. 38: 580-596.
4 . Chang DH and Islam S (2000) Estimation of soil physical properties using remote sensing and artificial neural network. International Journal Remote Sensing of Environment. 74: 534-544.
5 . Drummond ST, Sudduth KA, Joshi A, Birrell SJ and Kitchen NR (2003) Statistical and neural methods for site specific yield prediction. Transactions of the American Society of Agricultural and Biological Engineers (ASABE). 46: 5-14.
6 . Farrokh AR and Farrokh A (2012) Effect of nitrogen and potassium on yield, agronomy efficiency, physiological efficiency and recovery efficiency of nitrogen and potassium in flue-cured tobacco. International Journal Agriculture Crop Science. 4: 770-778.
7 . Gholipoor M, Emamgholizadeh S, Hassanpour H, Shahsavani D, Shahoseini H, Baghi M and Karimi A (2012) The optimization of root nutrient content for increased sugar beet productivity using an artificial neural network. International Journal Plant Production. 6: 429-442.
8 . Gholipoor M, Rohani A and Torani S (2013) Optimization of traits to increasing barley grain yield using an artificial neural network. International Journal Plant Production.7: 1-17.
9  .Jin YQ and Liu C (1997) Biomass retrieval from high-dimensional active/passive remote sensing data by using artificial neural networks. International Journal Remote Sensing of Environment. 18: 971-979.
10 . Kena K (1990) Effect of N.P.K. fertilizer on the yield and quality of flue-cured leaf tobacco. Ethiopian Journal of Agricultural Science. 12: 77-82.
11 . Liu YX, Li CJ and Zhang FS (2005) Transpiration, potassium uptake and flow in tobacco as affected by nitrogen forms and nutrient levels. Annals of Botany. 95: 991-998.
12 . Long RC and Weybrew JA (1981) Major chemical changes during senescence and curing. Tobacco Science. 7: 40-74.
13 . Marchetti R, Castelli F and Contillo R (2006) Nitrogen requirements for flue-cured tobacco. Agronomy Journal.  98: 666-674.
14 . Marschne H (1995) Mineral Nutrition of Higher Plants. Academic Press, London. Pp. 229-312.
15 . Mohsenzadeh R (2015) Study of quality and chemical characteristics of tobacco cultivars Nicotiana tabaccum (EJAS) [Online]. Available online at Extensive Journal of Applied Sciences. 3: 11-14.
16 . Mumba P and Banda HL (1990) Nicotine content of flue tobacco (Nicotiana tabacum L.) at different stages of growth. Tobacco Science. 30: 179-183.
17 . Rohani A, Abbaspour-Fard MH and Abdolahpour S (2011) Prediction of tractor repair and maintenance costs using artificial neural network. Expert Systems with Applications. 38: 8999-9007.
18 . Sabeti MA and Jabbarzadeh A (2004) Effect of different potassium fertilizer on quantity and quality yield of flue-cured tobacco.Tobacco Research Institute Publishers, Rasht, Iran. Code Number 6: 103-182.
19 . ShamelRostami MT (1996) Effect of different nitrogen resources on quality and quantity of flue- cured tobacco cv. coker 347. Tirtash Tobacco Research Institute Publishers, Mazandaran, Iran. Code Number. 2-101-74.
20 . Skogley EO and McCanns CB (1963) Ammonium and chloride influences on growth characteristics of flue-cured tobacco. Soil Science Society of America, Proceedings. 27: 391-394.
21 . Williams LM and Miner GS (1982) Effect of urea on yield and quality of flue-cured tobacco Nicotiana tabaccum. Agronomy Journal. 74: 457-62.
22 . Zhang WJ and Barrion AT (2006) Function approximation and documentation of sampling data using artificial neural networks. Environ Monit Assessment. 122: 185-201.