تاثیر تنش شوری بر عملکرد گیاه ذرت بر اساس توابع تولید کلان طی رشد زایشی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشیار، پژوهشکده فناوری تولیدات گیاهی، دانشگاه شهید باهنر کرمان، کرمان، ایران

2 استادیار، گروه علوم خاک، دانشکده علوم کشاورزی، دانشگاه گیلان، رشت، ایران

چکیده

ذرت در مواجهه با تنش شوری، واکنش‌های متفاوتی را طی مراحل مختلف رشدی نشان می­دهد و دوره رشد زایشی، حساس‌ترین دوره زندگی گیاه است. هدف از پژوهش حاضر، ارزیابی توانمندی مدل‌های شبیه‌ساز شوری در تخمین عملکرد ذرت رقم سینگل کراس 704 طی دوره رشد زایشی بود. برای این منظور، مدل­های فرایندی- فیزیکی شامل ماس و هافمن، ونگنوختن و هافمن، دیرکسن و همکاران و همایی و همکاران مورد استفاده قرار گرفتند. به­منظور ایجاد شرایط واقعی رشد در خاک­های شور، از آب شور طبیعی دریاچه نمک نوق واقع در رفسنجان استفاده و برای تهیه تیمارهای شوری مورد مطالعه در این آزمایش با آب معمولی رقیق شد. تیمارهای مورد استفاده در این پژوهش شامل سطوح شوری 1، 2، 4، 6 و 8 دسی­زیمنس بر متر به­همراه یک تیمار آب غیرشور (به­عنوان شاهد) بودند که در سه تکرار مورد مطالعه قرار گرفتند. نتایج حاصل از آماره‌های ضریب کارآیی اصلاح شده (E')، شاخص مطابقت اصلاح شده (d') و ضریب جرم باقیمانده (CRM)، نشان داد که برای متغیر ارتفاع اندام هوایی، مدل ونگنوختن و هافمن با دارا بودن بیش­ترین دقت (91/0=d' و 87/0=E') دقیق‌ترین مدل بود، در حالی­که برای متغیر وزن خشک اندام هوایی، مدل غیرخطی همایی و همکاران (90/0=d' و 86/0=E') و برای متغیر عملکرد نهایی دانه، مدل ماس و هافمن (96/0=d' و 94/0=E') دارای بیش­ترین دقت بودند و بهترین تخمین را ارایه دادند. به‌طور کلی، نتایج این پژوهش نشان داد که مدل‌های شبیه­ساز شوری، توانمندی خوبی در تخمین عملکرد گیاه ذرت تحت شرایط تنش شوری و مدیریت بهتر تخصیص منابع آب کم­کیفیت در مراحل مختلف رشد گیاه داشتند. به­عبارت دیگر، استفاده از مدل‌های چهارگانه ماس و هافمن، ونگنوختن و هافمن، دیرکسن و همکاران و همایی و همکاران، می‌توانند ابزار موثری در استفاده از منابع آب شور با درجات مختلف شوری در جهت دستیابی به تولید بهینه ذرت باشند. بنابراین، با تعیین دقیق مدل بهینه برای هر دوره رشد و پذیرش میزان ریسک افت عملکرد به­ازای میزان شوری آب آبیاری، می‌توان به­طور قابل­توجهی از منابع آب کم­کیفیت نیز در تولید محصول ذرت بهره برد.

کلیدواژه‌ها

عنوان مقاله [English]

The effects of salinity stress on maize yield based on macroscopic production functions at reproductive growth stage

نویسندگان [English]

  • Vahid Reza Jalali 1
  • Safoora Asadi Kapourchal 2
1 Assoc. Prof., Research and Technology Institute of Plant Production (RTIPP), Shahid Bahonar University of Kerman, Kerman, Iran
2 Assist. Prof., Dept. of Soil Science, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran
چکیده [English]

Maize in response to salinity stress exhibits different responses during different growth stages and reproductive growth stage is the most sensitive stage of plant growth. The objective of the present study was to evaluate the ability of salinity simulator models to estimate maize (SC704) yield, during reproductive growth stage. Process-physical models including Maas and Hoffman, van Genuchten and Hoffman, Dirksen et al. and Homaee et al. models were used to access this objective. In order to create real growth conditions in saline soils, natural saline water of Nough lake in Rafsanjan, Kerman province, Iran, with electrical conductivity of 42.6 dS.m-1, was used and diluted with normal fresh water for preparation of salinity treatments studied in this experiment. Treatments used in this study were five salinity levels of 1, 2, 4, 6 and 8 dS/m with a non-saline water (as check treatment) that were studied in three replications. The results of modified efficiency coefficient (E'), modified agreement index (d') and coefficient of residual mass (CRM) statistics showed that the van Genuchten and Hoffman model with the highest accuracy (E'=0.87, d'=0.91) was the most accurate model for shoot height, while for shoot dry weight, the Nonlinear model of Homaee et al. (with the accuracy of E'=0.86 and d'=0.90) and for final grain yield, the Maas and Hoffman model (with the accuracy of E'=0.94 and d'=0.96), had the most accuracy and the best estimate. In total, the results of this study showed that salinity simulation models had good ability to estimate maize yield under salinity stress and better management of allocation of low quality water resources in different stages of plant growth. In other words, the four models of Maas and Hoffman, van Genuchten and Hoffman, Dirksen et al. and Homaee et al. can be effective tools in using saline water sources with varying degrees of salinity to achieve optimal maize production. Therefore, by precisely determining the optimal model for each growth stage and accepting the risk of yield loss due to salinity of irrigation water, low-quality water resources can also be considerably utilized in maize yield production.

کلیدواژه‌ها [English]

  • Abiotic stress
  • Agreement index
  • Simulation
  • Yield decrease

مراجع

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تحقیقات غلات
دوره 10، شماره 1
خرداد 1399
صفحه 45-59

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