پديد آورندگان :
نه بنداني، عليرضا دانشگاه علوم كشاورزي و منابع طبيعي گرگان - دانشكده توليد گياهي - گروه زراعت، گرگان، ايران , سلطاني، افشين دانشگاه علوم كشاورزي و منابع طبيعي گرگان - دانشكده توليد گياهي - گروه زراعت، گرگان، ايران , زينلي، ابراهيم دانشگاه علوم كشاورزي و منابع طبيعي گرگان - دانشكده توليد گياهي - گروه زراعت، گرگان، ايران , حسيني، فريما دانشگاه آزاد اسلامي گرگان - دانشكده فني و مهندسي - گروه زراعت، گرگان، ايران
چكيده لاتين :
Introduction: Removing the yield gap (the difference between farmed yield and potential yield) is known as the
most important way to increase crop production (Egli and Hatfield, 2014). Therefore, the amount of yield gap and
the reasons for it are important. Soybeans [Glycine max (L.) Merrill] are one of the most important oilseed crops
in the world (FAOSTAT, 2016). In Iran, the area of soybean cultivation is up to 66,000 hectares and annual
production is 151,000 tons (Ministry of Agriculture Jihad, 2013). This does not meet domestic requirements,
however, so soybean production should be increased. For this purpose, a field study was conducted in 138 farms
using an application of regression modeling in 2013-15 in cities of Gorgan and Aliabad Katul.
Materials and methods: Farms were selected with the help of agricultural service centers. Based on information
provided by the service centers, farms were selected based on their diversity in terms of area under cultivation,
management and yield. Management factors included a history of production, planting methods, inoculated or noninoculated
seed with bacteria, seed rate, nitrogen fertilizer (N) rate, phosphorus fertilizer (P2O5) rate, potash
fertilizer rate, the number of plowings, planting date, cultivar type, previous crop, use or non-use of N fertilizer
top-dressing, number of N fertilizer top-dressing, use or non-use of herbicides, use or non-use of pesticides, animal
manure type, irrigation type and amount, harvest methods, and others (a total of 67 management factors). All
information about management operations were recorded and measured. Then, the relationship between actual
yield and the 67 management variables were assessed using stepwise regression.
Results and discussion: The average yield for farms was 2,908 kg per hectare and the maximum yield was 5,100
kg per hectare. Model Root Mean Square Error (RMSE) was 274 kg per hectare and coefficient of variation (CV)
was 9 percent. These statistics showed that the accuracy of the model was acceptable. Therefore, the model could
be used to determine the yield gap and the share of yield constraints. Model yield, on average, was estimated at
2,918 kg per hectare and maximum yield was 4,820 kg per hectare. In this model, total yield gap has been estimated
at 1,902 kg per hectare. Accordingly, the most important factors in yield gap for the region included: number of
irrigations with 29% (equivalent to 535 kg per hectare), net nitrogen with 22% (equivalent to 419 kg per hectare),
P2O5 with 20% (equivalent to 365 kg per hectare), planting date with 16% (equivalent to 302 kg per hectare) and
disk number with 13% (equivalent to 250 kg per hectare).
Conclusion: With optimized items listed, soybean yield could be increased approximately 1,871 kg per
hectare in Gorgan and Aliabad Katul. Use of this method isn’t suitable for determining optimum values. In order
to determine optimum values for each listed item, other methods can be used for yield gap analysis, such as a
boundary line analysis.
