مدل‌سازی زمان جوانه‌زنی علف‌هرز وایه گل‌سفید (ammi majus l.) در واکنش به دما

مدل‌های مبتنی بر جمعیت، ابزارهای مفیدی برای توصیف رفتار جوانه‌زنی بذرها در پاسخ به دما هستند. در این مطالعه، دقت پیش‌بینی رهیافت‌های مختلف زمان‌گرمایی جهت مدل‌سازی دوره‌های زمانی پیشرفت جوانه‌زنی علف‌هرز وایه گل‌سفید در واکنش به دما ارزیابی شد. آزمون جوانه‌زنی در هشت دمای ثابت 8، 12، 16، 20، 24، 28، 32 و 36 درجه سانتی‌گراد انجام شد. مقادیر rmse و aic نشان داد که وقتی tb (دمای پایه) و θtm (نیاز زمان‌گرمایی برای تکمیل جوانه‌زنی در دماهای بیشتر از بهینه (to)) برای کل جمعیت بذری ثابت بود و توزیع نرمال برای توصیف تنوع θt(g) (نیاز زمان‌گرمایی برای تکمیل جوانه‌زنی هر کسر بذری معین در دماهای بین tb و to) و tm(g) (دمای بیشینه (tm) برای بازدارندگی گرمایی جوانه‌زنی کسر معین 1g در دماهای بین to و tm) بکار رفت، مدل برازش دقیق‌تری به داده‌ها ارائه داد. بر اساس این رویکرد، tb و θtm برای این گیاه به‌ترتیب معادل 1.06 درجه سانتی‌گراد و 1155.41 درجه سانتی‌گراد ساعت برآورد شد. مقادیر θt و tm برای کسر 50 درصد (θt(50) و tm(50)) به‌ترتیب معادل 2708.62 درجه سانتی‌گراد ساعت و 34.55 درجه سانتی‌گراد تعیین شد. مقدار to برای کسرهای مختلف جوانه‌زنی (to(g)) ثابت نبود و برای کسر 50 درصد (to(50)) معادل 24.51 درجه سانتی‌گراد به دست آمد. پارامترهای برآورد شده در این مطالعه می‌تواند برای ساخت مدل‌های پیش‌بینی کننده الگوی رویش علف‌هرز وایه گل‌سفید در مزرعه استفاده شود.

Modeling the Germination Timing of Bishop 's Weed (Ammi majus L.) in Response to Temperature

Introduction: After moisture, temperature is the main driving force affecting seed germination. Populationbased models are useful tools for describing and predicting germination in relation to time and temperature. These models estimate the thermal thresholds for seed germination, taking into account both the speed and final percentage of germination in different temperature regimes. The populationbased approach has been widely used to model the thermal response of various plant processes such as germination and dormancy of seeds as well as seedling emergence in the field. However, the assumptions of this approach on the germination of seeds of some plant species, especially weeds, are not always correct. Therefore, in this research, the accuracy of prediction of different thermaltime approaches for modeling the germination time courses of bishop apos;s weed (Ammi majus L.) in response to constant temperature regimes was evaluated. Bishop apos;s weed was selected because there are no reports regarding the germination response thresholds of this species to temperature in the scientific resources.;Materials and Methods: Experiment was conducted at the Seed Technology Laboratory of Agricultural and Natural Resources University of Khuzestan in November 2017. In this study, germination response of bishop apos;s weed was evaluated at different constant temperatures. The seeds of bishop apos;s weed were collected from the margins of several wheat fields at the time of their natural dispersal in June 2014. The seeds of bishop apos;s weed were incubated in the dark using incubators with controlled environments at eight constant temperatures of 8, 12, 16, 20, 24, 28, 32 and 36 ºC with a range of ±0.2 ºC. These temperature regimes cover both the sub and supraoptimal temperature ranges. The trial was performed in a completely randomized design with four replications. The germinated seeds (criterion, radicle protrusion of gt; 2 mm) were counted and removed at frequent time intervals. The eventtime approach (package drc in R environment software) was applied to determine the time taken for cumulative germination to reach subpopulation percentiles of 20, 50 and 80% of maximum in each temperature regimes. Experimentally obtained cumulativegermination curves were used to perform a nonlinear regression procedure to assess the relative accuracy of different thermalgermination models in predicting germination response under constant incubation temperatures. Assessment of goodnessoffit was performed by the Akaike information criterion (AIC).;Results and Discussion: The values of RMSE and AIC showed that the model had better and more accurate fit to bishop apos;s weed germination data when the Tb (base temperature) and θTm (thermaltime required to complete germination at temperatures greater than optimal (To)) were assumed to be constant for the whole seed population, and Normal distribution was used to describe the variation in θT(g) (thermaltime required to complete the germination of each given seed fraction at a temperatures between the Tb and To) and Tm(g) (maximum temperature (Tm) for seed thermoinhibition of given fraction g at temperatures between the To and Tm). Based on this approach, the Tb and θTm for this plant were estimated to be 1.06 ºC and 1155.41 ºC h, respectively. The values of θT and Tm for seed fraction of 50% (θT(50) and Tm(50)) were determined as 2708.62 ºC h and 34.55 ºC, respectively. The value of To was not constant for different germination fractions (To(g)), and for fraction 50% (To(50)) was determined to be 24.51 ºC. Thermaltime analysis is considered by many researchers to have physiologically and ecologically relevant parameters and, in its standard form, provides several useful indices of seed germination behavior in response to temperature. Despite its popularity, the generality of its assumptions has not been examined systematically. If these assumptions do not hold, at least approximately, in a particular situation, misleading interpretations can easily arise. The thermalgermination model presented here explained some of the adaptive characteristics of the germination response of bishop apos;s weed to ambient temperature. Seed thermoinhibition in this weed species occurred at temperatures beyond 25.43 ºC. In other words, the seeds of bishop apos;s weed do not germinate when temperature will exceed this limit and thus remaining capable of germinating until the environmental conditions change.;Conclusion: In summary, in this study, the thermal thresholds for seed germination of bishop apos;s weed were identified. Our results showed that the Tb was constant for the whole seed population. The thermalgermination model described here gave an acceptable explanation of the observed seed germination patterns. Almost all the concepts and mathematical models described in this study can be applied to modeling seedling emergence in the field.