نوع مقاله : علمی - پژوهشی

نویسندگان

1 دانشجوی دکتری زراعت، دانشکده علوم کشاورزی، واحد آیت‌الله آملی، دانشگاه آزاد اسلامی، آمل، ایران

2 استادیار، گروه زراعت، دانشکده علوم کشاورزی، واحد آیت‌الله آملی، دانشگاه آزاد اسلامی، آمل، ایران

3 پژوهشگر پسا دکتری، پژوهشگاه بیوتکنولوژی کشاورزی ایران، کرج، ایران

چکیده

چکیده
مستندسازیفرآیندتولیددرکشاورزیشاملتهیه کلیهاطلاعاتوفعالیت‌هاییاستکهسیرتولید یکمحصول از مرحلهتهیهبستربذرتابرداشترانشانمی‌دهد. لذا، هدف از این پژوهش، برآورد خلأ عملکرد ارقام محلی برنج به روش تحلیل مقایسه کارکرد (CPA) بود. دراینپژوهشتمامیعملیات‌هایمدیریتیانجامشدهازمرحلهتهیهبستربذرتابرداشت برای ارقام محلی برنجازطریق مطالعاتمیدانی در منطقه آمل واقع در استان مازندران و منطقه رشت در استان گیلان طی سال‌های 1395 و 1396 ثبتشد. برای تعیین مدل عملکرد (تولید)، رابطه بین تمامی متغیرها و عملکرد شلتوک از طریق رگرسیون گام‌به‌گام بررسی شد. خلأ عملکرد نیز از تفاضل پتانسیل عملکرد و عملکرد واقعی به‌دست آمد. نتایج نشان داد از حدود 155 متغیر مورد بررسی، مدل نهایی در منطقه آمل و رشت به‌ترتیب با هفت و شش متغیر مستقل انتخاب شد. متوسط عملکرد واقعی ثبت‌شده در دو منطقه آمل و رشت به‌ترتیب برابر 4821 و 4467 کیلوگرم در هکتار بود. در معادله تولید منطقه آمل، متوسط و حداکثر عملکرد به‌ترتیب 4798 و 6505 کیلوگرم در هکتار تخمین زده شد که کل خلأ عملکرد برابر 1707 کیلوگرم در هکتار بود. در معادله تولید منطقه رشت، متوسط و حداکثر عملکرد به‌ترتیب 4443 و 6377 کیلوگرم در هکتار به‌دست آمد که کل خلأ عملکرد برآورد شده برابر 1934 کیلوگرم در هکتار بود. در منطقه آمل، میزان افزایش عملکرد مربوط به متغیرهای تاریخ نشاکاری، تعداد دفعات مصرف سرک و نیتروژن بعد از گلدهی به‌ترتیب برابر 364، 292 و 416 کیلوگرم در هکتار سهمی معادل 21، 17 و 24 درصد از کل خلأ عملکرد را شامل شدند. همچنین، متغیرهای تناوب زراعی، ضدعفونی بذر و برداشت با کمباین از نظر خلأ عملکرد در رتبه‌های بعدی قرار گرفتند. در منطقه رشت، میزان افزایش عملکرد مربوط به متغیرهای مصرف پتاسیم، نیتروژن قبل از نشا و نیتروژن بعد از گلدهی به‌ترتیب با 644، 325 و 730 کیلوگرم در هکتار خلأ عملکرد سهمی معادل 33، 17 و 38 درصد از کل را نشان دادند. بنابراین، بر اساس برازش رابطه بین عملکرد مشاهده‌شده و عملکرد پیش‌بینی‌شده می‌توان بیان کرد که دقت مدل (معادله تولید) مناسب بوده و می‌تواند برای برآورد میزان خلأ عملکرد و تعیین سهم هر یک از متغیرهای محدود‌ کننده عملکرد به‌کار گرفته شود.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Estimation of Yield Gap of Rice by Comparative Performance Analysis (CPA) in Amol and Rasht Regions

نویسندگان [English]

  • Ebrahim Habib 1
  • Yosoof Niknezhad 2
  • Hormoz Fallah 2
  • Salman Dastan 3
  • Davood Barari Tari 2

1 Ph.D. Student of Agronomy, Faculty of Agricultural Sciences, Ayatollah Amoli Branch, Islamic Azad University, Amol, Iran

2 Assistant Professor, Department of Agronomy, Faculty of Agricultural Sciences, Ayatollah Amoli Branch, Islamic Azad University, Amol, Iran

3 Postdoctoral Research Scholar, Agricultural Biotechnology Research Institute of Iran (ABRII), Karaj, Iran

چکیده [English]

Abstract
 
Background and Objectives
Rice (Oryza sativa L.) is the staple food of more than half of the world’s population and has an important role in feeding, income and job creation in the world, especially Iran. Yield gap analysis provides little estimation of increased production capacity which is an important component in designing food-providing strategy in regional, national and global scales. The existing heated discussions regarding food security have increased the number of necessary studies that estimate the quantity of yield gap and the reasons behind it through appropriate statistical methods in Iran and the rest of the world. It seems that by defining the effectiveness of each management parameter regarding the amount of presented yield gap and, consequently, the farmer’s knowledge on that matter the distance between actual yield and attainable yield can be reduced. In this research, estimation of potential yield, yield gap, and determining yield restricting factors and each of their portions in creating rice yield gap have been investigated.
 
Materials and Methods
Research was done in 100 paddy fields in Amol and Rasht regions in 2016 and 2017. All managerial practices from nursery preparation to harvest for local rice cultivars were recorded through fields monitoring. Field selection was done in a way that included all main production procedures with variation in management viewpoint. To define yield model, the relationship between all measured variables and the final model was designed by controlled trial and error method, which could quantify the effect of yield limitations. The average yield was calculated by placing the observed average variables (Xs) in the fields under study in the yield model. Thereafter, by putting the best observed value of the variables in the yield model the maximum obtainable yield was calculated. The difference between these two has been considered yield gap. Different procedures of the software SAS version 9.1 were used for analysis.
 
Results
Data analysis revealed that from 155 variables under study, the final model in Amol and Rasht regions with seven and six independent variables was chosen. In Amol yield model, maximum and average yield were 4798 and 6505 kg ha-1, respectively that estimated yield gap was 1707 kg ha-1. In Rasht yield model, maximum and average yield were 4443 and 6377 kg ha-1, respectively, which estimated that yield gap was 1934 kg ha-1. In Amol region, the amount of increased yield related to transplanting date, top-dressing and nitrogen after flowering variable was 364, 292 and 416 kg ha-1 which equals to 21, 17 and 24 percent of total yield increase. In Rasht region, the yield increase related to the effect of potassium and nitrogen before transplanting, and N after flowering was 644, 325 and 730 kg ha-1 which equals to 33, 17 and 38 percent.
 
Discussion
According to the findings, we suggest that the model precision is appropriate and can be applied for both estimating the quantity of yield gap and determining the portion of each constraints yield variables. Furthermore, considering the fact that the calculated yield potential is reached through actual data in each paddy field, it is suggested that this yield potential is attainable. 

کلیدواژه‌ها [English]

  • Cultivar
  • Documentation
  • Field management
  • Potential yield
  • Relative yield
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