Germination Parameters of Selected Summer Weeds: Transferring of the AlertInf Model to Other Geographical Regions

Šoštarčić, Valentina; Masin, Roberta; Loddo, Donato; Brijačak, Ema; Šćepanović, Maja

doi:10.3390/agronomy11020292

Cited by 5 publications

(8 citation statements)

References 31 publications

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“…The average annual temperature in Zagreb is 11.8 °C, while the average annual temperature in Padova is 12.2 °C. A similar trend was observed for another grass weed species, S. pumila, of which the estimated Tb of the Croatian population is 6.6 °C, while the Italian population has a Tb of 10.4 °C [22].…”

Section: Estimation Of Base Temperature and Base Water Potentialsupporting

confidence: 76%

“…For practical purposes, the use of AlertInf by Croatian farmers could be a good way to predict the emergence of E. crus-galli without the need to measure and monitor all of the parameters required as inputs by complex mechanistic models [1,17]. The results of this study encourage us to extend AlertInf to other important maize weed species for which the germination parameters have already been estimated [22]. The possible extension of AlertInf to other geographical areas could be the focus of further experiments.…”

Section: Discussionmentioning

confidence: 90%

“…A linear regression, estimated using the bootstrap method [28], provided the best fit of germination rate (reciprocal of time to 50% germination) against incubation temperature or water potential. The values of T b and Ψ b were estimated as the intercept of the regression line with the temperature or water potential axis [7,22,29].…”

Section: Discussionmentioning

confidence: 99%

“…The aim of the comparison was to verify whether inserting the value of the Croatian population into the AlertInf model is necessary, which would be a model recalibration, whether statistical difference is found between the values of the Italian and Croatian populations, and whether the model can be used without recalibration. The criterion of overlap of the 95% confidence intervals estimated with the bootstrap method was used to compare the values of the germination parameters of Croatian and Italian populations of E. crus-galli as described in Šoštarčić et al [22].…”

Section: Discussionmentioning

confidence: 99%

“…The monitoring of germination was performed as described in Šoštarčić et al [22] and Masin et al [7]. Germination was recorded daily to analyze the germination dynamics at different temperatures and water potentials.…”

Section: Laboratory Experiments-estimation Of Base Temperature and Base Water Potentialmentioning

confidence: 99%

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Predicting the Emergence of Echinochloa crus-galli (L.) P. Beauv. in Maize Crop in Croatia with Hydrothermal Model

et al. 2021

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Echinochloa crus-galli (L.) P. Beauv. is the most common monocotyledonous weed in maize crops in Croatia. Crop–weed interference is influenced by weed emergence patterns, and knowledge of the timing of weed emergence is crucial for the development of an efficient integrated weed-management program. Therefore, two-year field experiments were conducted in a maize crop sown in early May in continental Croatia to determine the emergence pattern of E. crus-galli from natural seedbank. In laboratory studies, the estimated base temperature and base water potential for the Croatian ecotype of E. crus-galli were 10.8 °C and −0.97 MPa, respectively. Then, the estimated germination parameters were compared with the values embedded in the AlertInf model from Italy (Veneto) to calibrate this hydrothermal model. The estimated hydrothermal units were around 28 for the onset (10%) and 93 for the middle (50%) emergence of E. crus-galli. Our findings showed that the AlertInf model satisfactorily simulated the emergence of E. crus-galli in maize crop in Croatia (EF = 0.97 in 2019 and 0.98 in 2020), indicating its potential use in other geographical areas

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Section: Estimation Of Base Temperature and Base Water Potentialsupporting

confidence: 76%

Section: Discussionmentioning

confidence: 90%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Laboratory Experiments-estimation Of Base Temperature and Base Water Potentialmentioning

confidence: 99%

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Predicting the Emergence of Echinochloa crus-galli (L.) P. Beauv. in Maize Crop in Croatia with Hydrothermal Model

et al. 2021

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Modeling weed seedling emergence for time-specific weed management: a systematic review

Marschner,

Colucci,

Stup

et al. 2024

Weed Sci

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Understanding the timing of weed emergence is crucial to effective management. Management practices implemented too early may fail to completely control late-emerging seedlings, whereas management practices implemented too late will suffer from low efficacy. Weed emergence times reflect biological factors, such as seed dormancy and germination requirements, as well as environmental conditions. We conducted a systematic review of studies that developed models to predict weed emergence temporal patterns. We screened 1,854 studies, 98 of which were included in the final dataset. Most included studies were conducted in North America (51) or Europe (30). A wide variety of weed species (102) and families (21) were included, and many studies modeled several weeds. Grass weeds (Poaceae) were modeled most frequently (83 instances). Most weeds (40%) had base temperature T b values between 0 to 5 C and 38% had base water potential ψ b ranging from -1.0 to -0.5 MPa. Most studies used empirical parametric models, such as Weibull (40%) or Gompertz (30%) models. Non-parametric and mechanistic models were also represented. Models varied in their biological and environmental data requirements. In general, empirical parametric models based on hydrothermal time (i.e., time above base temperature and water potential thresholds) represented a good balance between ease of use and prediction accuracy. Soft computing approaches such as artificial neural networks demonstrated substantial potential in situations with complex emergence patterns and limited data availability, although they can be susceptible to overfitting. Our study also demonstrated variability in model performance and limited generalizability across species and regions. This finding underscores the need for context-specific and well-validated weed emergence models to inform management, especially in the context of climate change.

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Germination ecology of Chenopodium album L. and implications for weed management

Tang

Guo²,

Yin³

et al. 2022

PLoS ONE

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Chenopodium album L. is a troublesome annual species in various cropping systems, and a sound knowledge of the ecological response of C. album germination to environmental factors would suggest suitable management strategies for inhibiting its spread. Preliminary laboratory-based research was conducted to investigate germination and emergence requirements of C. album under various environmental conditions (e.g., photoperiods, constant temperature, salinity, moisture, soil pH, burial depth, and oat crop residue). Results showed C. album seeds were found to be photoblastic, with only 13% germination in darkness. The maximum germination (94%) of C. album occurred at an optimal temperature of 25°C, and the depressive effect of other temperatures on germination was more severe at lower rather than higher temperatures. Seed germination was suitably tolerant of salinity and osmotic potential, with germination observed at 200 mM NaCl (37.0%) and -0.8 MPa (20%), respectively. Germination was relatively uniform (88–92%) at pH levels ranging from 4 to 10. The maximum germination of C. album was observed on the soil surface, with no or rare emergence of seeds at a burial depth of 2 cm or under 7000 kg ha-1 oat straw cover, respectively. Information provided by this study will help to develop more sustainable and effective integrated weed management strategies for the control of C. album, including (i) a shallow-tillage procedures to bury weed seeds in conventional-tillage systems and (ii) oat residue retention or coverage on the soil surface in no-tillage systems.

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Germination Parameters of Selected Summer Weeds: Transferring of the AlertInf Model to Other Geographical Regions

Cited by 5 publications

References 31 publications

Predicting the Emergence of Echinochloa crus-galli (L.) P. Beauv. in Maize Crop in Croatia with Hydrothermal Model

Predicting the Emergence of Echinochloa crus-galli (L.) P. Beauv. in Maize Crop in Croatia with Hydrothermal Model

Modeling weed seedling emergence for time-specific weed management: a systematic review

Germination ecology of Chenopodium album L. and implications for weed management

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