This experiment carried out as split plot factorial based on a randomized complete block design with three replications during two consecutive years (2015–2016). The main plot consisted of drought stress: complete irrigation, irrigation withholding at R1 stage, irrigation withholding at R2 stage and subplots included foliar application of micronutrients: distilled water (control), zinc sulfate, manganese sulfate and zinc sulfate + manganese sulfate and cultivar as: Williams and Zan elite. The results showed that proline and linoleic acid were increased significantly, but chlorophyll a and b, seed yield, protein percentage, oleic and linolenic acids were decreased significantly by irrigation withholding. Also, the maximum values of chlorophyll b, protein percentage and linolenic acid were achieved by Williams. The significant increasing effect of zinc was found on the maximum root and stem proline, chlorophyll b, and oleic, linolenic and linoleic unsaturated fatty acids, meanwhile the maximum leaf proline was obtained by manganese sulfate.

This experiment was conducted using a split plot layout in a randomized complete block design with three replications at the research farm of agriculture faculty, Islamic Azad University, Sanandaj Branch during 2013 growing season. The main factor was seed priming with various Nano-sliver particle concentration including 4 levels of 0 (distilled water: control), 20, 40 and 60 ppm, the sub factor was safflower cultivars with 3 levels included: Sina, Faraman and IL111. Results showed that the effects of nanosilver on traits including: fertile and unfertile head number, numbers of seed in head, seed and oil yield were different significantly. The most seed yield was obtained in 40 ppm nanosilver (2180.63 kg/ha), that it produced 33.04 % more yield in compare with control. Also the most oil yield was obtained in 20 ppm nanosilver as 522.87 kg/ha, that it produced 30.8 % more yield as control (399.72 kg/ha). Furthermore the greatest amounts of seed yield were recorded by IL111 cultivar, as it obtained seed yield increasing at the rates of 8.14 and 14 percent compared to Sina and Faraman cultivars, respectively. Finally, in this experiment, the most seed and oil yield was obtained in 20 ppm nanosilver and IL111 cultivar.

Camelina [Camelina sativa (L.) Crantz] is an annual versatile oilseed crop of the Brassicaceae family, with an increasingly cultivated area. Predicting camelina seed yield response to fertilization and planting density is of great importance in understanding production potential and management planning. Therefore, the current study aimed to estimate the seed yield of camelina by response surface methodology (RSM) and artificial neural network (ANN) as affected by different levels of planting row spacing and nitrogen (N), sulfur (S), and cow manure (CM) fertilization. The experiment was conducted in two growing years of 2019–2020 and 2020–2021, based on a central composite design with four factors including row spacing (15–35 cm), N (0–200 kg ha⁻¹), S (0–100 kg ha⁻¹), and CM (0–40 t ha⁻¹). The RSM models for seed yield versus fertilization and row spacing factors in both years were statistically significant and had an acceptable predictive ability. Camelina seed yield decreased with increasing row spacing but showed a positive response to increasing the amount of N, S, and CM fertilizers. Comparing the performance of the models showed that, although the RSM models were significant and had the necessary efficiency in predicting camelina seed yield, the ANN models were more accurate. The performance criteria of coefficient of determination (R²), root mean square error (RMSE), standard error of prediction (SEP), mean absolute error (MAE), and Akaike information criterion (AICc) averaged over the two years for the RSM model were 0.924, 51.60, 5.51, 41.14, and 394.05, respectively, and for the ANN model were 0.968, 32.62, 3.54, 19.55, and 351.33, respectively. Based on the results, the ANN modeling can be used in predicting camelina seed yield in field conditions with more confidence than the RSM technique.

To study the effects of mycorrhiza, fulvic acid, seaweed extract and urea on physiological trait and leaf yield of tobacco, an experiment was carried out as split plots in a randomized complete block design with three replications in Marivan during 2015 year. In this study, the main factor was two levels of inoculation by mycorrhiza including: control: no inoculation and inoculation by mycorrhiza (Glomus interaradices) and subplot were stimulation growth compound in 5 levels as: control-distilled water, fulvic acid, seaweed extract, urea, fulvic acid+ seaweed extract + urea. The results showed that the characters, including: numbers of leaves and dry leaf weight of the middle leaf side of plant were affected significantly by mycorrihza. Hence, numbers of leaf and leaf dry weight of middle leaf side were increased by mycorrhiza inoculations. Also the results of foliar application of stimulation plant growth were showed that relative water content, leaf fresh weight and leaf dry weight in lower side leaves and leaf fresh weight and leaf dry weight in middle side leaves and also spad and leaf fresh weight of upper side leaves of tobacco were affected significantly.