scholarly journals Simulating maize phenology as a function of air temperature with a linear and a nonlinear model

2008 ◽  
Vol 43 (4) ◽  
pp. 449-455 ◽  
Author(s):  
Nereu Augusto Streck ◽  
Isabel Lago ◽  
Luana Fernandes Gabriel ◽  
Flavia Kaufmann Samboranha
Keyword(s):  
Nonlinear Model ◽  
Developmental Stages ◽  
Growing Season ◽  
Sowing Date ◽  
Thermal Time ◽  
Time Model ◽  
Data Set ◽  
Physiological Maturity ◽  
Maize Variety ◽  
Thermal Time Model

The objective of this study was to adapt a nonlinear model (Wang and Engel - WE) for simulating the phenology of maize (Zea mays L.), and to evaluate this model and a linear one (thermal time), in order to predict developmental stages of a field-grown maize variety. A field experiment, during 2005/2006 and 2006/2007 was conducted in Santa Maria, RS, Brazil, in two growing seasons, with seven sowing dates each. Dates of emergence, silking, and physiological maturity of the maize variety BRS Missões were recorded in six replications in each sowing date. Data collected in 2005/2006 growing season were used to estimate the coefficients of the two models, and data collected in the 2006/2007 growing season were used as independent data set for model evaluations. The nonlinear WE model accurately predicted the date of silking and physiological maturity, and had a lower root mean square error (RMSE) than the linear (thermal time) model. The overall RMSE for silking and physiological maturity was 2.7 and 4.8 days with WE model, and 5.6 and 8.3 days with thermal time model, respectively.

scholarly journals Comparing two versions of a non-linear model for simulating leaf number and developmental stages in maize based on air temperature

2008 ◽  
Vol 39 (3) ◽  
pp. 642-648 ◽  
Author(s):  
Nereu Augusto Streck ◽  
Luana Fernandes Gabriel ◽  
Flavia Kaufmann Samboranha ◽  
Isabel Lago ◽  
Ana Paula Schwantes ◽  
...  
Keyword(s):  
Air Temperature ◽  
Developmental Stages ◽  
Temperature Response ◽  
Growing Season ◽  
Leaf Number ◽  
Physiological Maturity ◽  
Arithmetic Average ◽  
Daily Minimum ◽  
Maize Variety ◽  
Non Linear

The Wang and Engel (WE) model simulates crop development considering the non-linear response of plant development to temperature. Daily air temperature is the input for the temperature response function [f(T)] in the WE model, and because there are several approaches for computing daily temperatures, there are several ways to calculate the f(T). The objective of this study was to compare two versions of the WE model for simulating leaf number and developmental stages in maize, considering two approaches for imputing daily air temperature (daily mean air temperature and daily minimum/maximum air temperature). A two-year field experiment with the maize variety BRS Missões sown in several sowing dates was conducted in Santa Maria, Rio Grande do Sul State, Brazil, during the 2005-2006 and 2006-2007 growing seasons. The f(T) in the WE model was calculated using daily mean air temperature calculated as the arithmetic average of daily minimum (TN) and maximum (TX) air temperatures (WE Tmean), and calculating an f(T) using TN and an f(T) using TX and then averaging the two f(T)s (WE Tmm). Ligule and tip leaf number, and silking and physiological maturity developmental stages measured in the 2005-2006 growing season were used to estimate model coefficients and the ones measured in the 2006-2007 growing season were used as independent data sets to evaluate models. Predictions of ligule and tip leaf number, silking and physiological maturity of the maize variety BRS Missões were better with the WE Tmm model than with the WE Tmean model.

A Thermal Time Model to Predict Corn Poppy (Papaver rhoeas) Emergence in Cereal Fields

Weed Science ◽  
2009 ◽  
Vol 57 (6) ◽  
pp. 660-664 ◽  
Author(s):  
Jordi Izquierdo ◽  
José L. González-Andújar ◽  
Fernando Bastida ◽  
Juan A. Lezaún ◽  
María J. Sánchez del Arco
Keyword(s):  
Seedling Emergence ◽  
Gompertz Model ◽  
Sowing Date ◽  
Control Measures ◽  
Thermal Time ◽  
Base Temperature ◽  
Time Model ◽  
Data Set ◽  
Winter Cereals ◽  
Cereal Fields

Corn poppy is the most abundant broad-leaved weed in winter cereals of Mediterranean climate areas and causes important yield losses in wheat. Knowledge of the temporal pattern of emergence will contribute to optimize the timing of control measures, thus maximizing efficacy. The objectives of this research were to develop an emergence model on the basis of soil thermal time and validate it in several localities across Spain. To develop the model, monitoring of seedling emergence was performed weekly during the growing season in a cereal field located in northeastern Spain, during 3 yr. Cumulative thermal time from sowing date was used as the independent variable for predicting cumulative emergence. The Gompertz model was fitted to the data set of emergences. A base temperature of 1.0 C was estimated through iteration for maximum fit. The model accounted for 91% of the variation observed. Model validation in several localities and years showed general good performance in predicting corn poppy seedling emergence ( values ranging from 0.64 to 0.99 and root-mean-square error from 4.4 to 24.3). Ninety percent emergence was accurately predicted in most localities. Results showed that the model performs with greater reliability when significant rainfall (10 mm) occurs within 10 d after crop sowing. Complemented with in-field scouting, it may be a useful tool to better timing control measures in areas that are homogeneous enough regarding climate and crop management.

A thermal time model for optimising herbicide dose in maize

Weed Research ◽  
2021 ◽  
Author(s):  
Behnaz Pourmorad Kaleibar ◽  
Mostafa Oveisi ◽  
Hassan Alizadeh ◽  
Heinz Mueller Schaerer
Keyword(s):  
Thermal Time ◽  
Time Model ◽  
Thermal Time Model

Utilizing a Thermal Time Model to Estimate Safe Times to Transplant Tilia Trees

2019 ◽  
Vol 45 (5) ◽  
Author(s):  
Tapio Linkosalo ◽  
Pilvi Siljamo ◽  
Anu Riikonen ◽  
Frank Chmielewski ◽  
Juha Raisio
Keyword(s):  
Geographical Area ◽  
Frost Damage ◽  
Thermal Time ◽  
Weather Data ◽  
Model Parameters ◽  
The European Union ◽  
Time Model ◽  
Large Size ◽  
Nursery Trees ◽  
Thermal Time Model

City trees planted in parks and along streets are typically grown to large size in nurseries before being transplanted to their final growing sites. According to tendering rules within the European Union (EU), any business may compete for public contracts in any EU country, and this applies to purchases of valuable lots of nursery trees. There is however a risk of poor transplanting success if the trees are imported from very distant locations with a different pace of spring development. The aim of this study was to implement a Thermal Time model to predict the spring development of Tilia trees to find out in which geographical area the spring development is sufficiently similar to conditions in southern Finland, so that the success of transplantation of the trees is not unduly risked. We used phenological observations collected at the International Phenological Gardens (IPGs) over the whole of Europe, together with ERA-Interim weather data to estimate the model parameters, and then used the same date to predict the onset of leaf unfolding ofTilia during the years 1980 to 2015. Producing maps of phenological development of Tilia, we concluded that there are no large risks of frost damage if tree import area is limited to northern parts of Baltics or to the west coast of Scandinavia.

Modeling germination of smallflower umbrella sedge (Cyperus difformis L.) seeds from rice fields in California across suboptimal temperatures

2019 ◽  
Vol 33 (5) ◽  
pp. 733-738 ◽  
Author(s):  
Rafael M. Pedroso ◽  
Durval Dourado Neto ◽  
Ricardo Victoria Filho ◽  
Albert J. Fischer ◽  
Kassim Al-Khatib
Keyword(s):  
Growth Models ◽  
Rice Fields ◽  
Control Measures ◽  
Thermal Time ◽  
Model Parameters ◽  
Base Temperature ◽  
Probit Regression ◽  
Time Model ◽  
Thermal Requirements ◽  
Thermal Time Model

AbstractSmallflower umbrella sedge is a prolific C3 weed commonly found in rice fields in 47 countries. The increasing infestation of herbicide-resistant smallflower umbrella sedge populations threatens rice production. Our objectives for this study were to characterize thermal requirements for germination of smallflower umbrella sedge seeds from rice fields in California and to parameterize a population thermal-time model for smallflower umbrella sedge germination. Because the use of modeling techniques is hampered by the lack of thermal-time model parameters for smallflower umbrella sedge seed germination, trials were carried out by placing field-collected seeds in a thermogradient table set at constant temperatures of 11.7 to 41.7 C. Germination was assessed daily for 30 d, and the whole experiment was repeated a month later. Using probit regression analysis, thermal time to median germination [θT(50)], base temperature for germination (Tb), and SD of thermal times for germination [σθT(50)] were estimated from germination data, and model parameters were derived using the Solver tool in Microsoft Excel®. Germination rates increased linearly below the estimated optimum temperatures of 33.5 to 36 C. Estimated Tb averaged 16.7 C, whereas θT(50) equaled 17.1 degree-days and σθT(50) was only 0.1 degree-day. The estimated Tb for smallflower umbrella sedge is remarkably higher than that of japonica and indica types of rice, as well as Tb of important weeds in the Echinochloa complex. Relative to the latter, smallflower umbrella sedge has lower thermal-time requirements to germination and greater germination synchronicity. However, it would also initiate germination much later because of its higher Tb, given low soil temperatures early in the rice growing season in California. When integrated into weed growth models, these results might help optimize the timing and efficacy of smallflower umbrella sedge control measures.

scholarly journals Germination parameterization and development of an after-ripening thermal-time model for primary dormancy release of Lithospermum arvense seeds

2009 ◽  
Vol 103 (8) ◽  
pp. 1291-1301 ◽  
Author(s):  
Guillermo R. Chantre ◽  
Diego Batlla ◽  
Mario R. Sabbatini ◽  
Gustavo Orioli
Keyword(s):  
Thermal Time ◽  
Dormancy Release ◽  
Time Model ◽  
Primary Dormancy ◽  
Thermal Time Model

GROUNDNUT GROWTH AND DEVELOPMENT IN CONTRASTING ENVIRONMENTS. 2. HEAT UNIT ACCUMULATION AND PHOTO-THERMAL EFFECTS ON HARVEST INDEX

1998 ◽  
Vol 34 (1) ◽  
pp. 113-124 ◽  
Author(s):  
M. J. BELL ◽  
G. C. WRIGHT
Keyword(s):  
Harvest Index ◽  
Growing Season ◽  
Sowing Date ◽  
Short Wave ◽  
Thermal Time ◽  
Dominant Factor ◽  
Published Data ◽  
Wide Range ◽  
Semi Arid ◽  
Subtropical Australia

When the same cultivars of groundnuts (Arachis hypogaea) were grown under a wide range of environmental conditions, temperature and irradiance played a major role in determining crop duration and partitioning of dry matter to pods, the latter assessed by harvest index. Utilizing published data for the Virginia groundnut cultivar Early Bunch under non-limiting conditions, we show that accumulation of thermal time using three cardinal temperatures (Tb=9 °C, To=29 °C and Tm=39 °C) has considerable potential for predicting crop maturity. In sixteen sowings ranging from the wet tropics in Indonesia to the elevated subtropics in Australia, harvest date for Early Bunch corresponded to the accumulation of 1808 (±23) degree-days after sowing. In all sowings except one in the semi-arid tropics, this value of thermal time was within eight calendar days of actual harvest maturity. Harvest index varied greatly with both location and sowing date, ranging from 0.31 (Indonesia) to 0.58 (subtropical Australia). Using total short-wave solar radiation incident during the growing season and calculated values of thermal time, the growing season for each sowing in each location was described in terms of a photo-thermal quotient (PTQ, MJ m−2 degree-day−1). Values for PTQ ranged from 0.99 (Indonesia) to 2.11 (subtropical Australia). Variation in harvest index could be explained largely by a curvilinear function of PTQ (R2=0.98), provided data were not confounded by the effects of photoperiod. In the semi-arid tropical environment, decreases in photoperiod associated with delayed sowing were the dominant factor controlling harvest index.

scholarly journals Application of the thermal time model for different Typha domingensis populations

2020 ◽  
Author(s):  
Fanny Mabel Carhuancho León ◽  
Pedro Luis Aguado Cortijo ◽  
María del Carmen Morató Izquierdo ◽  
María Teresa Castellanos Moncho
Keyword(s):  
Seed Germination ◽  
Mean Value ◽  
Thermal Time ◽  
Plant Responses ◽  
Base Temperature ◽  
Typha Domingensis ◽  
Time Model ◽  
Germination Response ◽  
Thermal Regimes ◽  
Thermal Time Model

Abstract Background: Cattail (Typha domingensis Pers.) is a perennial emergent plant which is used in Green Floating Filters (GFFs), one of the most innovative systems of wastewater treatment to bioremediate eutrophic waters and produce biomass as biofuel feedstocks. The establishment of cattails in GFFs depends on the seed germination and plant responses under conditions of a new habitat. This study analysed the germination responses of four different populations of cattails through a thermal time model to know their basic parameters of germination and which population would be more adapted to the conditions tested.Results: Seeds from the Badajoz (Ba), Cuenca (Cu), Madrid (Ma), Seville (Se) and Toledo (To) populations were exposed to different thermal regimes (constant, and alternating temperatures between 15 and 30°C) and different darkness treatments (between 0 and 20 days with 24h dark photoperiod, then exposed to light with 12h light/dark photoperiod) to determine the parameters of the thermal model from germination levels in each treatment. To population was used to validate the thermal time parameters of other populations. Regardless of the other parameters, no germination occurred in total darkness. The mean value of base temperature (Tb) was 16.4±0.2°C in all treatments. Optimum temperature (To) values in Ma and Ba were 25°C, and those in Cu and Se were 22.5°C. The germination response decreased when the temperature approached Tb and increased when it was close to To. In comparison to alternating temperatures, constant temperatures had the highest germination response and lowest thermal time (θT(50)). Darkness treatments had a direct relationship with θT(50). The population origin also affected seed germination; Cu had the highest values of To and germination response but had a lower θT(50), which coincides with the lowest mean ambient temperatures. Conclusion : According to these results, the germination response of cattails was high in all populations under optimal conditions but was affected to a greater or lesser extent depending on thermal regimes, darkness treatments, and populations. The thermal time model allowed us to determine that To was between 22.5-25ºC and that Cu is the best population regarding the germination response under the conditions tested.

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