اثرات ریزوباکتری‌های تحریک‌کننده رشد و کود نیتروژن بر شاخص‌های رشدی لوبیا (.phaseolus vulgaris l) در شرایط تنش‌کمبود آب

این پژوهش در سال زراعی 95-1394 به صورت کرت‌های خردشده در قالب طرح پایه بلوک‌های کامل تصادفی با سه تکرار در مزرعه تحقیقاتی دانشگاه فردوسی مشهد اجرا شد. سطوح آبیاری در سه سطح شامل: 100 درصد نیاز آبی، 75 درصد نیاز آبی، و 50 درصد نیاز آبی به‌عنوان عوامل کرت اصلی و کود بیولوژیک نیتروکسین، کود بیولوژیک بیوفسفر، کود شیمیایی نیتروژنه (اوره) و شاهد به‌عنوان عوامل کرت فرعی منظور شدند. نتایج آزمایش نشان داد که کودهای بیولوژیک مورد بررسی به ویژه نیتروکسین در مقایسه با شاهد و حتی کود اوره، حداکثر مقادیر شاخص‌های رشدی شامل ماده ‌خشک تجمعی، شاخص سطح برگ، سرعت رشد محصول، سرعت رشد نسبی و سرعت جذب خالص‌ لوبیا را به طور معنی‌داری افزایش دادند. بیشترین و کمترین شاخص سطح ‌برگ در اثر عامل کود ‌بیولوژیک نیتروکسین و شاهد به‌ترتیب برابر 0/2 و 7/1 به‏دست آمد (p≤0.01). بیشترین و کمترین مقادیر سرعت رشد محصول در 77 روز پس از کاشت به‌ترتیب در اثر عامل کود نیتروکسین و شاهد برابر با 04/11 و 81/8 گرم در مترمربع در روز به‏دست آمد (p≤0.05). بیشترین مقادیر شاخص‌های رشدی لوبیا نیز با تامین 100درصد نیاز آبی حاصل شد. کودهای نیتروکسین و بیوفسفر افزایش معنی‌داری (p≤0.05) بر عملکرد دانه لوبیا داشتند و این صفت را به‌ترتیب 3/92 و 1/54 درصد نسبت به تیمار شاهد افزایش دادند. اثرات اصلی و متقابل کود و آبیاری نیز بر طول مخصوص ریشه معنی‌دار (p≤0.05) بود، به‏طوری‌که بیشترین طول مخصوص (15/30 متر در 25 سانتی‌مترمکعب خاک) در نتیجة کود نیتروکسین و 100درصد نیاز آبی به‏دست آمد. به طور کلی، استفاده از کودهای بیولوژیک جایگزین مناسب‌تر کود شیمیایی نیتروژنه در تولید محصول سالم لوبیا می‌باشد.

The effects of growth promoting rhizobacteria and nitrogen fertilizer on growth indices of bean (Phaseolus vulgaris L.) under water shortage stress conditions

IntroductionCommon bean (Phaseolus vulgaris L.) is the world’s most important food legume crop. This staple considered as a nearly perfect food mainly because of its high protein content (about 25 percent) and abundant fiber, complex carbohydrates (about 60 percent), and other daily food needs such as vitamins (folate) and minerals (Cu, Ca, Fe, Mg, Mn, and Zn). Water use in agricultural production as one of the most important environmental factors affecting plant growth and development, especially in arid and semiarid climatic conditions of Iran. Materials and MethodsIn order to study the effect of plant growth promoting Rhizobacteria and nitrogen chemical fertilizer on some characteristics of root and growth indices of bean (Phaseolus vulgaris L.) under water stress conditions, a splitplot design based on RCBD with three replications was conducted during growing season of 201516 at Agricultural Research station, College of Agriculture, Ferdowsi University of Mashhad, Iran. Three levels of irrigation (100%, 75%, 50% water requirement) assigned to main plots and different types of biofertilizers (Nitroxin®, containing Azotobacter sp. and Azospirillum sp., Biophosphor®. containing Phosphatesolubilizing bacteria Bacillus sp. and Pseudomonas sp.), Nitrogen fertilizer) urea form, and Control (no fertilizer) were assigned to sub plots. Destructive sampling was performed to calculate the growth indices (such as TDW (total dry weight), LAI (leaf area index), CGR (crop growth rate), RGR (relative growth rate) and NAR (net assimilation rate)) randomly from competing plants regarding the marginal effects from 1 real completed leaf stage to the end of the growing season from 5 m2 surface (every 7 days; 12 steps). The growth indices of LAI, CGR, RGR and NAR were calculated using equations (14). At the end of the growing season SRL (specific root length) was determined by Tenant Modified Method. Leaf area calculated by Leaf Area Meter device (Delta T, UK). Data analysis of variance and figures preparation were done by Minitab Ver. 16, Slide Write Ver. 2, and Excel 2010 softwares. At the end, Means comparing did by Duncan’s test at probability 5%. Equation 1:LAI= (1/GA)[(LA2+LA1)/2]                                                                           Equation 2:CGR= (1/GA)[(W2–W1)/(t2–t1)]                                                                                Equation 3:RGR= (lnW2–lnW1)/(t2–t1)                                                                            Equation 4:NAR= [(W2–W1)/(t2–t1)] [(lnLA2–lnLA1)/(LA2–LA1)]                                 where GA is ground area (m2), LA is leaf area (m2), W is shoot dry weigh (g) and t is time (day). Results and DiscussionAccording to the result, the effect of biological fertilizers especially Nitroxin significantly increased maximum values of bean`s growth indices included total dry matter (TDM max), leaf area index (LAI max), crop growth rate (CGR max), relative growth rate (RGR max) and net assimilation rate (NAR max) compared to control and even nitrogen fertilizer. So that the highest and the lowest total dry matter (TDM max) at 91 days after planting were observed in Nitroxin (370 g.m2) and control (342 g.m2) traits (p≤0.01), respectively. The highest and the lowest leaf area index (LAI max) at 91 days after planting were observed in Nitroxin (2.0) and control (1.7) traits (p≤0.01), respectively. The highest and the lowest crop growth rate (CGR max) at 77 days after planting was observed in Nitroxin 11.04 g.m2.day1 and control 8.81 g.m2.day1 traits (p≤0.05), respectively. The highest and the lowest relative growth rate (RGR max) at 21 days after planting was observed in Nitroxin 0.23 g.g1.day1 and control 0.20 g.g1.day1 traits (p≤0.01), respectively, and then decreased gradually. Similar to RGR, the highest and the lowest net assimilation rate (NAR max) at 21 day after planting was observed in Nitroxin 35.5 g.m2.day1 and control 28.4 g.m2.day1 traits (p≤0.05), respectively. All attributes, showed highest values at 100% water requirement treatment. Also, the effect of fertilizers (p≤0.05) and water requirement (p≤0.01) were significant on grain yield. The main and interaction effects of fertilizer and irrigation were significant (p≤0.05) on specific root length (SRL). So that, the highest specific root length (30.15 m.25cm3 soil) were obtained from Nitroxin and 100% water requirement. ConclusionIn total, the results showed that it could be possible to produce the healthy production of bean, moreover, attain the optimum yield as equal as to conventional systems.