Volume 8, Issue 1 ((Spring and Summer) 2021)
Iranian J. Seed Res. 2021, 8(1): 123-136 |
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Mijani S, Rastgoo M, Ghanbari A, Nassiri Mahallati M. (2021). Quantification of Tuber Sprouting of Purple Nutsedge (Cyperus rotundus) Response Against Temperature Using Thermal Time Models. Iranian J. Seed Res.. 8(1), : 8 doi:10.52547/yujs.8.1.123
URL: http://yujs.yu.ac.ir/jisr/article-1-462-en.html
URL: http://yujs.yu.ac.ir/jisr/article-1-462-en.html
Ferdowsi University of Mashhad , m.rastgoo@um.ac.ir
Abstract: (4185 Views)
Extended abstract
Introduction: Purple nutsedge (Cyperus rotundus L.) is one of the problematic weeds worldwide prevalent in tropical and subtropical regions. Tubers are major tools through which purple nutsedge is propagated, whereas its seeds have a low ability to germinate. Therefore, evaluation of the response of tubers against environmental agents is great of importance to know the germination and emergence time. Germination, in turn, is mostly affected by temperature, among other environmental factors. Various models that are recognized as the Thermal Time model have been introduced to describe the seed germination pattern against temperature. Since predicting the emergence of reproductive organs through the modeling is great of importance for improving the control strategies; the present study was carried out to investigate the response of tuber sprouting of purple nutsedge (Cyperus rotundus) against temperature using thermal time models.
Material and methods: The experiment was carried out as a randomized complete block design with three replications in a germinator. Each replicate was placed on a separate shelf. For each replicate, 15 tubers were placed inside a 20 cm Petri dish on a filter paper and then 100 ml of water was added. The experiment was performed separately for constant temperatures of 10, 15, 20, 25, 30, 35, and 40 °C in absolute darkness. To analyze the data as modeling, five thermal time models were evaluated based on the statistical distributions of normal, Weibull, Gumble, logistic and log logistic. Indices such as R2, RMSE, RMSE%, and AICc were used to evaluate the models.
Results: The results showed that all models predicted the germination response of purple nutsedge tuber with high accuracy (R2 = 0.95). A comparison of models based on AICc values showed significant superiority of the Gumble model over other models. According to this index, there was no difference between logistic and log logistic models with normal. Among the models, Weibull was identified as the most inappropriate model. Different models estimated the final germination (Gmax) between 0.93 to 0.94 (93 to 94%). The base temperature was estimated through different models from 7.10 to 7.47 °C. Among the models, the model based on the Gumble distribution proved the skew to the right of the thermal time and Tm. According to the Gumble model, the thermal time parameters required to reach 50% germination (θT (50)) equals 123.8 ° C day and the maximum temperature for germination at 50% probability (Tc (50)) was estimated to be 46.10 ° C.
Conclusion: the thermal time model based on the Gumble probability distribution was most plausible among the models. Also, a distributed right skewness related to the thermal time and Tm was proved through the Gumble model. The parameters obtained from the Gumble model can be used to predict the sprouting of purple nutsedge tubers.
Highlights:
Introduction: Purple nutsedge (Cyperus rotundus L.) is one of the problematic weeds worldwide prevalent in tropical and subtropical regions. Tubers are major tools through which purple nutsedge is propagated, whereas its seeds have a low ability to germinate. Therefore, evaluation of the response of tubers against environmental agents is great of importance to know the germination and emergence time. Germination, in turn, is mostly affected by temperature, among other environmental factors. Various models that are recognized as the Thermal Time model have been introduced to describe the seed germination pattern against temperature. Since predicting the emergence of reproductive organs through the modeling is great of importance for improving the control strategies; the present study was carried out to investigate the response of tuber sprouting of purple nutsedge (Cyperus rotundus) against temperature using thermal time models.
Material and methods: The experiment was carried out as a randomized complete block design with three replications in a germinator. Each replicate was placed on a separate shelf. For each replicate, 15 tubers were placed inside a 20 cm Petri dish on a filter paper and then 100 ml of water was added. The experiment was performed separately for constant temperatures of 10, 15, 20, 25, 30, 35, and 40 °C in absolute darkness. To analyze the data as modeling, five thermal time models were evaluated based on the statistical distributions of normal, Weibull, Gumble, logistic and log logistic. Indices such as R2, RMSE, RMSE%, and AICc were used to evaluate the models.
Results: The results showed that all models predicted the germination response of purple nutsedge tuber with high accuracy (R2 = 0.95). A comparison of models based on AICc values showed significant superiority of the Gumble model over other models. According to this index, there was no difference between logistic and log logistic models with normal. Among the models, Weibull was identified as the most inappropriate model. Different models estimated the final germination (Gmax) between 0.93 to 0.94 (93 to 94%). The base temperature was estimated through different models from 7.10 to 7.47 °C. Among the models, the model based on the Gumble distribution proved the skew to the right of the thermal time and Tm. According to the Gumble model, the thermal time parameters required to reach 50% germination (θT (50)) equals 123.8 ° C day and the maximum temperature for germination at 50% probability (Tc (50)) was estimated to be 46.10 ° C.
Conclusion: the thermal time model based on the Gumble probability distribution was most plausible among the models. Also, a distributed right skewness related to the thermal time and Tm was proved through the Gumble model. The parameters obtained from the Gumble model can be used to predict the sprouting of purple nutsedge tubers.
Highlights:
- Thermal time models were evaluated for prediction of tuber sprouting of purple nutsedge.
- The thermal time model based on the Gumble distribution was superior over the normal distribution.
- Thermal time and Tm for tuber sprouting of purple nutsedge were distributed as right skewness.
Article number: 8
Type of Study: Research |
Subject:
General
Received: 2020/04/25 | Revised: 2024/02/20 | Accepted: 2020/12/20 | ePublished: 2021/10/27
Received: 2020/04/25 | Revised: 2024/02/20 | Accepted: 2020/12/20 | ePublished: 2021/10/27
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