Hydrothermal Emergence Model for Ripgut Brome (Bromus diandrus)

Weed Science ◽  
2013 ◽  
Vol 61 (1) ◽  
pp. 146-153 ◽  
Author(s):  
Addy L. García ◽  
Jordi Recasens ◽  
Frank Forcella ◽  
Joel Torra ◽  
Aritz Royo-Esnal
Keyword(s):  
Growth Function ◽  
Base Temperature ◽  
Independent Data ◽  
Data Set ◽  
Winter Cereal ◽  
Bromus Diandrus ◽  
Mediterranean Regions ◽  
Cereal Fields ◽  
Base Water Potential ◽  
The Relationship

A model that describes the emergence of ripgut brome was developed using a two-season data set from a no-tilled field in northeastern Spain. The relationship between cumulative emergence and hydrothermal time (HTT) was described by a sigmoid growth function (Chapman). HTT was calculated with a set of water potentials and temperatures, iteratively used, to determine the base water potential and base temperature. Emergence of ripgut brome was well described with a Chapman function. The newly-developed function was validated with four sets of data, two of them belonging to a third season in the same field and the other two coming from independent data from Southern Spain. The model also successfully described the emergence in different field management and tillage systems. This model may be useful for predicting ripgut brome emergence in winter cereal fields of semiarid Mediterranean regions.

Modeling the Emergence of Three Arable Bedstraw (Galium) Species

Weed Science ◽  
2010 ◽  
Vol 58 (1) ◽  
pp. 10-15 ◽  
Author(s):  
Aritz Royo-Esnal ◽  
Joel Torra ◽  
Josep Antoni Conesa ◽  
Frank Forcella ◽  
Jordi Recasens
Keyword(s):  
Water Potential ◽  
Seedling Emergence ◽  
Soil Water Potential ◽  
Base Temperature ◽  
Winter Cereal ◽  
Growth Functions ◽  
The United Kingdom ◽  
Mediterranean Regions ◽  
Cereal Fields ◽  
Base Water Potential

Multiyear field data from Spain were used to model seedling emergence for three bedstraw species (Galium) that can coexist in winter cereal fields. The relationships between cumulative emergence and both growing degree days (GDD) and hydrothermal time (HTT) in soil were analyzed as sigmoid growth functions (Weibull). Iterations of base temperature and base water potential were used to optimize the HTT scale. All species were well described with Weibull functions. Both GDD and HTT models provided good descriptions of catchweed bedstraw emergence, as its seedlings have less dependence on soil water potential than false cleavers and threehorn bedstraw, which were described best with HTT. The HTT model for catchweed bedstraw was validated successfully with independent data from the United Kingdom. The models may be useful for predicting bedstraw emergence in semiarid Mediterranean regions and elsewhere.

Development in Cowpea (Vigna unguiculata). III. Effects of Temperature and Photoperiod on Time to Flowering in Photoperiod-sensitive Genotypes and Screening for Photothermal Responses

1996 ◽  
Vol 32 (1) ◽  
pp. 29-40 ◽  
Author(s):  
P. Q. Craufurd ◽  
A. Qi ◽  
R. J. Summerfield ◽  
R. H. Ellis ◽  
E. H. Roberts
Keyword(s):  
Vigna Unguiculata ◽  
Base Temperature ◽  
Independent Data ◽  
Data Set ◽  
Linear Rate ◽  
Growing Seasons ◽  
The Common ◽  
Effects Of Temperature ◽  
Photoperiod Sensitive ◽  
Response To Temperature

SUMMARYSeventeen photoperiod-sensitive genotypes of cowpea (Vigna unguiculata) were grown in approximately 30 photothermal environments in Nigeria. Photoperiods ranged from 10 to 16 h d−1, mean temperatures from 19° to 30°C and times from sowing to flowering (f) from 32 to 140 d. Rate of progress towards flowering (1/f) was related to mean pre-flowering values of temperature and photoperiod using simple linear rate models comprising one, two or three planes (thermal, photothermal and insensitive). There were no significant differences (p > 0.25) among genotypes in response to temperature within the thermal plane and the common base temperature was estimated to be 7.6°C. Photoperiod-sensitivity varied by a factor of 15 among genotypes, and the critical and ceiling photoperiods varied from 12.2 to 13.4 and from 13.8 to more than 16 h d−1 at a mean temperature of 27°C, respectively. These simple models satisfactorily predicted f in an independent data set (R2 = 0.62) for plants grown in the main cowpea growing seasons at latitudes between 7° and 13°N. The utility of photothermal models and methods to screen for photothermal responses are discussed.

scholarly journals Temperature but not moisture response of germination shows phylogenetic constraints while both interact with seed mass and lifespan

2017 ◽  
Vol 27 (2) ◽  
pp. 110-120 ◽  
Author(s):  
Fabien Arène ◽  
Laurence Affre ◽  
Aggeliki Doxa ◽  
Arne Saatkamp
Keyword(s):  
Water Potential ◽  
Seed Size ◽  
Phylogenetic Signal ◽  
Seed Mass ◽  
Base Temperature ◽  
Data Set ◽  
Negative Relation ◽  
Germination Timing ◽  
Germination Traits ◽  
Base Water Potential

AbstractUnderstanding how plant traits interact with climate to determine plant niches is decisive for predicting climate change impacts. While lifespan and seed size modify the importance of germination timing, germination traits such as base temperature and base water potential directly translate climatic conditions into germination timing, impacting performance in later life stages. Yet we do not know how base temperature, base water potential, seed mass, lifespan and climate are related. We tested the relationships between base temperature and base water potential for germination, seed size and lifespan while controlling for bioclimatic regions. We also quantified the phylogenetic signal in germination traits and seed size using Pagel's λ. We used a worldwide data set of germination responses to temperature and moisture, seed size and lifespan of 240 seed plants from 49 families. Both germination temperature and moisture are negatively related to seed size. Annual plants show a negative relation between seed size and base water potential, whereas perennials display a negative relation between base temperature and seed mass. Pagel's λ highlighted the slow evolution of base temperature for germination, comparable to seed mass while base water potential was revealed to be labile. In the future, base water potential and seed mass can be used when moisture niches of plants are to be predicted. Lifespan, seed size and base temperature should be taken into account when analysing thermal limits of species distributions.

Phenology of sunflower cultivars. III. Models for prediction in field environments

1982 ◽  
Vol 33 (2) ◽  
pp. 263 ◽  
Author(s):  
GL Hammer ◽  
PJ Goyne ◽  
DR Woodruff
Keyword(s):  
Simulation Models ◽  
Field Studies ◽  
Base Temperature ◽  
Data Set ◽  
Rate Of Development ◽  
Cultivar Groups ◽  
Daily Rate ◽  
Australian Continent ◽  
Relationship Of ◽  
The Relationship

Models of the daily rate of development for the stages emergence to head visible and head visible to first anthesis were formed for two sunflower cultivars (Helianthus annuus cvv. Sunfola 68-2 and Hysun 30). The models relate rate of development to photoperiod, daily mean temperature and relative cultivar sensitivity to photoperiod. They were derived from controlled-environment and field studies reported in the first two papers of this series. The two cultivars were found not to differ in sensitivity to temperature. The base temperature for development was found to decrease as the life cycle progressed. The models were validated on an independent data set and are applicable to the entire Australian continent, with one possible limitation on the temperature range at long photoperiods (14-18 h). The relationship of these models to the cultivar groups defined in the first paper of this series is discussed and a rapid method of determining relative cultivar sensitivity factors for new cultivars is outlined. The application of the models in planning for avoidance of frost by selecting the time of planting and the cultivar to be planted was demonstrated for three major sunflower-growing districts in Queensland. The possible use of these phenology models in conjunction with growth simulation models for studies of crop adaptation is discussed.

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.

The visual arrays task…visual storage capacity or attention control?

2019 ◽  
Author(s):  
Jessie Martin ◽  
Jason S. Tsukahara ◽  
Christopher Draheim ◽  
Zach Shipstead ◽  
Cody Mashburn ◽  
...  
Keyword(s):  
Working Memory ◽  
Storage Capacity ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Attention Control ◽  
Data Sets ◽  
Independent Data ◽  
Visual Storage ◽  
Design Selection ◽  
The Relationship

**The uploaded manuscript is still in preparation** In this study, we tested the relationship between visual arrays tasks and working memory capacity and attention control. Specifically, we tested whether task design (selection or non-selection demands) impacted the relationship between visual arrays measures and constructs of working memory capacity and attention control. Using analyses from 4 independent data sets we showed that the degree to which visual arrays measures rely on selection influences the degree to which they reflect domain-general attention control.

PSVI-8 Meta-regression Analysis to Determine the Relationship Between Growing Pig Body Weight and Variation

2021 ◽  
Vol 99 (Supplement_1) ◽  
pp. 218-219
Author(s):  
Andres Fernando T Russi ◽  
Mike D Tokach ◽  
Jason C Woodworth ◽  
Joel M DeRouchey ◽  
Robert D Goodband ◽  
...  
Keyword(s):  
Body Weight ◽  
Regression Analysis ◽  
Sample Size ◽  
Polynomial Regression ◽  
Data Sets ◽  
Regression Equations ◽  
Prediction Equations ◽  
Data Set ◽  
Rate Of Increase ◽  
The Relationship

Abstract The swine industry has been constantly evolving to select animals with improved performance traits and to minimize variation in body weight (BW) in order to meet packer specifications. Therefore, understanding variation presents an opportunity for producers to find strategies that could help reduce, manage, or deal with variation of pigs in a barn. A systematic review and meta-analysis was conducted by collecting data from multiple studies and available data sets in order to develop prediction equations for coefficient of variation (CV) and standard deviation (SD) as a function of BW. Information regarding BW variation from 16 papers was recorded to provide approximately 204 data points. Together, these data included 117,268 individually weighed pigs with a sample size that ranged from 104 to 4,108 pigs. A random-effects model with study used as a random effect was developed. Observations were weighted using sample size as an estimate for precision on the analysis, where larger data sets accounted for increased accuracy in the model. Regression equations were developed using the nlme package of R to determine the relationship between BW and its variation. Polynomial regression analysis was conducted separately for each variation measurement. When CV was reported in the data set, SD was calculated and vice versa. The resulting prediction equations were: CV (%) = 20.04 – 0.135 × (BW) + 0.00043 × (BW)2, R2=0.79; SD = 0.41 + 0.150 × (BW) - 0.00041 × (BW)2, R2 = 0.95. These equations suggest that there is evidence for a decreasing quadratic relationship between mean CV of a population and BW of pigs whereby the rate of decrease is smaller as mean pig BW increases from birth to market. Conversely, the rate of increase of SD of a population of pigs is smaller as mean pig BW increases from birth to market.

Railroad Integration and Uneven Development on the European Periphery, 1870–1910

2021 ◽  
Vol 45 (2) ◽  
pp. 261-289
Author(s):  
Eduard J. Alvarez-Palau ◽  
Alfonso Díez-Minguela ◽  
Jordi Martí-Henneberg
Keyword(s):  
Economic Development ◽  
Positive Impact ◽  
Data Set ◽  
Per Capita Gdp ◽  
Catching Up ◽  
Nation States ◽  
Railroad Network ◽  
Per Capita ◽  
European Periphery ◽  
The Relationship

AbstractThis study explores the relationship between railroad integration and regional development on the European periphery between 1870 and 1910, based on a regional data set including 291 spatial units. Railroad integration is proxied by railroad density, while per capita GDP is used as an indicator of economic development. The period under study is of particular relevance as it has been associated with the second wave of railroad construction in Europe and also coincides with the industrialization of most of the continent. Overall, we found that railroads had a significant and positive impact on the growth of per capita GDP across Europe. The magnitude of this relationship appears to be relatively modest, but the results obtained are robust with respect to a number of different specifications. From a geographical perspective, we found that railroads had a significantly greater influence on regions located in countries on the northern periphery of Europe than in other outlying areas. They also helped the economies of these areas to begin the process of catching up with the continent’s industrialized core. In contrast, the regions on the southern periphery showed lower levels of economic growth, with this exacerbating the preexisting divergence in economic development. The expansion of the railroad network in them was unable to homogenize the diffusion of economic development and tended to further benefit the regions that were already industrialized. In most of the cases, the capital effect was magnified, and this contributed to the consolidation of newly created nation-states.

scholarly journals RESTING HEART RATE MODERATES THE RELATIONSHIP BETWEEN NEUROPSYCHIATRIC SYMPTOMS, MCI, AND ALZHEIMER’S DISEASE

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S641-S641
Author(s):  
Shanna L Burke
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Heart Rate ◽  
Relative Risk ◽  
Neuropsychiatric Symptoms ◽  
Cognitive Status ◽  
Resting Heart Rate ◽  
Data Set ◽  
Increased Risk ◽  
The Relationship

Abstract Little is known about how resting heart rate moderates the relationship between neuropsychiatric symptoms and cognitive status. This study examined the relative risk of NPS on increasingly severe cognitive statuses and examined the extent to which resting heart rate moderates this relationship. A secondary analysis of the National Alzheimer’s Coordinating Center Uniform Data Set was undertaken, using observations from participants with normal cognition at baseline (13,470). The relative risk of diagnosis with a more severe cognitive status at a future visit was examined using log-binomial regression for each neuropsychiatric symptom. The moderating effect of resting heart rate among those who are later diagnosed with mild cognitive impairment (MCI) or Alzheimer’s disease (AD) was assessed. Delusions, hallucinations, agitation, depression, anxiety, elation, apathy, disinhibition, irritability, motor disturbance, nighttime behaviors, and appetite disturbance were all significantly associated (p<.001) with an increased risk of AD, and a reduced risk of MCI. Resting heart rate increased the risk of AD but reduced the relative risk of MCI. Depression significantly interacted with resting heart rate to increase the relative risk of MCI (RR: 1.07 (95% CI: 1.00-1.01), p<.001), but not AD. Neuropsychiatric symptoms increase the relative risk of AD but not MCI, which may mean that the deleterious effect of NPS is delayed until later and more severe stages of the disease course. Resting heart rate increases the relative risk of MCI among those with depression. Practitioners considering early intervention in neuropsychiatric symptomology may consider the downstream benefits of treatment considering the long-term effects of NPS.

scholarly journals Spatial pattern and genetic diversity estimates are linked in stochastic models of population differentiation

2000 ◽  
Vol 23 (3) ◽  
pp. 541-544 ◽  
Author(s):  
José Alexandre Felizola Diniz-Filho ◽  
Mariana Pires de Campos Telles
Keyword(s):  
Genetic Diversity ◽  
Spatial Pattern ◽  
Stochastic Models ◽  
Population Differentiation ◽  
Real Data ◽  
Population Heterogeneity ◽  
Data Set ◽  
Mantel’S Test ◽  
The Relationship ◽  
Diversity Estimates

In the present study, we used both simulations and real data set analyses to show that, under stochastic processes of population differentiation, the concepts of spatial heterogeneity and spatial pattern overlap. In these processes, the proportion of variation among and within a population (measured by G ST and 1 - G ST, respectively) is correlated with the slope and intercept of a Mantel's test relating genetic and geographic distances. Beyond the conceptual interest, the inspection of the relationship between population heterogeneity and spatial pattern can be used to test departures from stochasticity in the study of population differentiation.

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