Crop yield, soil temperature and sensitivity of EPIC under central-eastern Canadian conditions

1998 ◽  
Vol 78 (3) ◽  
pp. 431-439 ◽  
Author(s):  
G. Roloff ◽  
R. Dejong ◽  
M.C. Nolin
Keyword(s):  
Soil Temperature ◽  
Crop Yields ◽  
Potential Evapotranspiration ◽  
Relative Sensitivity ◽  
Weather Data ◽  
Corn Yield ◽  
Eastern Canada ◽  
Nitrate N ◽  
Soil Temperatures ◽  
Central Eastern

The Environmental Policy Integrated Climate (EPIC) model can be an important tool for agricultural and environmental management. Application of EPIC in central-eastern Canada requires testing to evaluate its performance and to indicate eventual changes that ultimately can lead to a more accurate model. We compared crop yields and soil temperatures estimated using EPIC (version 5300) with measured data from two sites — Barrhaven, Ontario and St. Antoine, Quebec — where corn (Zea mays L.) and soybean (Glycine max L.) were grown during 4 yr. The sensitivity of several EPIC outputs to variations in selected input parameters was also determined. EPIC was run with either the Penman-Monteith (PM) or the Baier-Robertson (BR) potential evapotranspiration (PET) method. Mean estimated and measured soybean yields were not different, independent of PET method and location. Mean corn yields were underestimated at Barrhaven with the PM method, whereas they were overestimated by the BR method at St. Antoine. Using the PM method resulted in no difference between estimated and measured yields in 2 out of 5 corn years, while the BR method ensued in no difference in 3 out of 5 years. For soybean, only the BR method resulted in 1 yr of yield different than measured. Performance of the model in relation to experimental error and efficiency of the model varied with crop and location, and indicated that EPIC caused less error and was more efficient in estimating soybean than corn yields. Comparing limited measured soil temperature data with EPIC estimates reveled that EPIC tended to underestimate soil temperature; however no effect on estimated yield was observed. The relative sensitivity of EPIC outputs was least for yield and greatest for leached nitrate-N. The latter also displayed the highest variability in sensitivity. EPIC studies focusing on leached nitrate-N should require the most accurate crop, soil, hydrological and weather data in order to minimize errors. Key words: Environmental modelling, soybean yield, corn yield, sensitivity analysis

Do wheat breeders have suitable genetic variation to overcome short coleoptiles and poor establishment in the warmer soils of future climates?

2016 ◽  
Vol 43 (10) ◽  
pp. 961 ◽  
Author(s):  
Greg J. Rebetzke ◽  
Bangyou Zheng ◽  
Scott C. Chapman
Keyword(s):  
Soil Temperature ◽  
Crop Yields ◽  
Triticum Aestivum L ◽  
Wheat Breeding ◽  
Crop Failure ◽  
Coleoptile Length ◽  
Crop Establishment ◽  
Air Temperatures ◽  
Reduced Height ◽  
Soil Temperatures

Increases in air and soil temperatures will impact cereal growth and reduce crop yields. Little is known about how increasing temperatures will impact seedling growth and crop establishment. Climate forecast models predict that by 2060, mean and maximum air temperatures in the Australian wheatbelt will increase by 2−4°C during the March–June sowing period, and particularly at lower latitudes. Concomitant increases in soil temperature will shorten coleoptile length to reduce crop establishment, particularly where deep sowing to access sub-surface moisture. Mean coleoptile length was reduced in commercial wheat (Triticum aestivum L.) germplasm with increasing soil temperature (106 mm and 51 mm at 15°C and 31°C, respectively). Coleoptile lengths of modern semidwarf varieties were significantly (P < 0.01) shorter than those of older tall wheats at 15°C (95 mm and 135 mm) and 31°C (46 mm and 70 mm). A 12-parent diallel indicated large additive and small non-maternal genetic effects for coleoptile length at 15°C and 27°C. Large genotype rank changes for coleoptile length across temperatures (rs = 0.37, P < 0.05) contributed to smaller entry-mean heritabilities (0.41–0.67) to reduce confidence in selection for long-coleoptile genotypes across contrasting temperatures. General combining ability effects were strongly correlated across temperatures (rp = 0.81, P < 0.01), indicating the potential of some donors in identification of progeny with consistently longer coleoptiles. Warmer soils in future will contribute to poor establishment and crop failure, particularly with deep-sown semidwarf wheat. Breeding long-coleoptile genotypes with improved performance will require targeted selection at warmer temperatures in populations incorporating novel sources of reduced height and greater coleoptile length.

An artificial neural network to estimate soil temperature

1997 ◽  
Vol 77 (3) ◽  
pp. 421-429 ◽  
Author(s):  
Chun-Chieh Yang ◽  
Shiv O. Prasher ◽  
Guy R. Mehuys
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Soil Temperature ◽  
Potential Evapotranspiration ◽  
Daily Rainfall ◽  
Coefficient Of Determination ◽  
Ann Model ◽  
Soil Temperatures ◽  
Ann Models ◽  
Artificial Neural

This study was undertaken to develop an artificial neural network (ANN) model for transient simulation of soil temperature at different depths in the profile. The capability of ANN models to simulate the variation of temperature in soils was investigated by considering readily available meteorologic parameters. The ANN model was constructed by using five years of meteorologic data, measured at a weather station at the Central Experimental Farm in Ottawa, Ontario, Canada. The model inputs consisted of daily rainfall, potential evapotranspiration, and the day of the year. The model outputs were daily soil temperatures at the depths of 100, 500 and 1500 mm. The estimated values were found to be close to the measured values, as shown by a root-mean-square error ranging from 0.59 to 1.82 °C, a standard deviation of errors from 0.61 to 1.81 °C, and a coefficient of determination from 0.937 to 0.987. Therefore, it is concluded that ANN models can be used to estimate soil temperature by considering routinely measured meteorologic parameters. In addition, the ANN model executes faster than a comparable conceptual simulation model by several orders of magnitude. Key words: Artificial neural networks, soil temperature, precipitation, potential evapotranspiration

MACROCLIMATIC MODEL FOR ESTIMATING MONTHLY SOIL TEMPERATURES UNDER SHORT-GRASS COVER IN CANADA

1973 ◽  
Vol 53 (3) ◽  
pp. 263-274 ◽  
Author(s):  
C. E. OUELLET
Keyword(s):  
Soil Temperature ◽  
Potential Evapotranspiration ◽  
Important Variable ◽  
Climatic Variables ◽  
Standard Errors ◽  
Climatic Data ◽  
Regression Equations ◽  
Grass Cover ◽  
Temperature Variations ◽  
Soil Temperatures

A macroclimatic model was developed to estimate monthly soil temperatures under short-grass cover. It involved multiple regression equations for each month and for each of six depths (1, 10, 20, 50, 100, and 150 cm). Data used were obtained from published records of soil temperature and corresponding climatic variables. They were from 41 stations over several years with station-years per regression varying from 88 to 226 according to depths and months. The climatic variables were related to air temperature, rainfall, snowfall, and potential evapotranspiration. An additional important variable was the estimated soil temperature of the previous month. The equations explain 70–96% of the soil temperature variations and the standard errors of estimate varied from 0.7 to 2.2 C. Temperatures estimated for 1 yr and eight stations with climatic data not used in the development of the equations departed from the observed values by less than 0.5, 1.0, and 2.0 C in 34, 62, and 92% of the cases, respectively. Errors resulting from the estimation of monthly normals by this model are expected to be generally less than 1.0 degree C.

scholarly journals Apicidin biosynthesis is linked to accessory chromosomes in Fusarium poae isolates

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Thomas E. Witte ◽  
Linda J. Harris ◽  
Hai D. T. Nguyen ◽  
Anne Hermans ◽  
Anne Johnston ◽  
...  
Keyword(s):  
Fusarium Head Blight ◽  
Crop Yields ◽  
High Resolution Mass Spectrometry ◽  
Gene Clusters ◽  
Biosynthetic Gene ◽  
Metabolome Analysis ◽  
Head Blight ◽  
Eastern Canada ◽  
Fusarium Poae ◽  
Accessory Chromosomes

Abstract Background Fusarium head blight is a disease of global concern that reduces crop yields and renders grains unfit for consumption due to mycotoxin contamination. Fusarium poae is frequently associated with cereal crops showing symptoms of Fusarium head blight. While previous studies have shown F. poae isolates produce a range of known mycotoxins, including type A and B trichothecenes, fusarins and beauvericin, genomic analysis suggests that this species may have lineage-specific accessory chromosomes with secondary metabolite biosynthetic gene clusters awaiting description. Methods We examined the biosynthetic potential of 38 F. poae isolates from Eastern Canada using a combination of long-read and short-read genome sequencing and untargeted, high resolution mass spectrometry metabolome analysis of extracts from isolates cultured in multiple media conditions. Results A high-quality assembly of isolate DAOMC 252244 (Fp157) contained four core chromosomes as well as seven additional contigs with traits associated with accessory chromosomes. One of the predicted accessory contigs harbours a functional biosynthetic gene cluster containing homologs of all genes associated with the production of apicidins. Metabolomic and genomic analyses confirm apicidins are produced in 4 of the 38 isolates investigated and genomic PCR screening detected the apicidin synthetase gene APS1 in approximately 7% of Eastern Canadian isolates surveyed. Conclusions Apicidin biosynthesis is linked to isolate-specific putative accessory chromosomes in F. poae. The data produced here are an important resource for furthering our understanding of accessory chromosome evolution and the biosynthetic potential of F. poae.

scholarly journals Simulation of Daily Mean Soil Temperatures for Agricultural Land Use Considering Limited Input Data

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 441
Author(s):  
Philipp Grabenweger ◽  
Branislava Lalic ◽  
Miroslav Trnka ◽  
Jan Balek ◽  
Erwin Murer ◽  
...  
Keyword(s):  
Soil Temperature ◽  
Input Data ◽  
Agricultural Land ◽  
Soil Column ◽  
Soil Conditions ◽  
Snow Layer ◽  
Time Step ◽  
Soil Temperatures ◽  
Dimensional Simulation ◽  
Limited Input Data

A one-dimensional simulation model that simulates daily mean soil temperature on a daily time-step basis, named AGRISOTES (AGRIcultural SOil TEmperature Simulation), is described. It considers ground coverage by biomass or a snow layer and accounts for the freeze/thaw effect of soil water. The model is designed for use on agricultural land with limited (and mostly easily available) input data, for estimating soil temperature spatial patterns, for single sites (as a stand-alone version), or in context with agrometeorological and agronomic models. The calibration and validation of the model are carried out on measured soil temperatures in experimental fields and other measurement sites with various climates, agricultural land uses and soil conditions in Europe. The model validation shows good results, but they are determined strongly by the quality and representativeness of the measured or estimated input parameters to which the model is most sensitive, particularly soil cover dynamics (biomass and snow cover), soil pore volume, soil texture and water content over the soil column.

scholarly journals A simple model for predicting soil temperature in snow-covered and seasonally frozen soil: model description and testing

2004 ◽  
Vol 8 (4) ◽  
pp. 706-716 ◽  
Author(s):  
K. Rankinen ◽  
T. Karvonen ◽  
D. Butterfield
Keyword(s):  
Heat Capacity ◽  
Simple Model ◽  
Soil Temperature ◽  
Specific Heat ◽  
Specific Heat Capacity ◽  
Frozen Soil ◽  
Model Description ◽  
Freezing And Thawing ◽  
Catchment Scale ◽  
Soil Temperatures

Abstract. Microbial processes in soil are moisture, nutrient and temperature dependent and, consequently, accurate calculation of soil temperature is important for modelling nitrogen processes. Microbial activity in soil occurs even at sub-zero temperatures so that, in northern latitudes, a method to calculate soil temperature under snow cover and in frozen soils is required. This paper describes a new and simple model to calculate daily values for soil temperature at various depths in both frozen and unfrozen soils. The model requires four parameters: average soil thermal conductivity, specific heat capacity of soil, specific heat capacity due to freezing and thawing and an empirical snow parameter. Precipitation, air temperature and snow depth (measured or calculated) are needed as input variables. The proposed model was applied to five sites in different parts of Finland representing different climates and soil types. Observed soil temperatures at depths of 20 and 50 cm (September 1981–August 1990) were used for model calibration. The calibrated model was then tested using observed soil temperatures from September 1990 to August 2001. R2-values of the calibration period varied between 0.87 and 0.96 at a depth of 20 cm and between 0.78 and 0.97 at 50 cm. R2-values of the testing period were between 0.87 and 0.94 at a depth of 20cm, and between 0.80 and 0.98 at 50cm. Thus, despite the simplifications made, the model was able to simulate soil temperature at these study sites. This simple model simulates soil temperature well in the uppermost soil layers where most of the nitrogen processes occur. The small number of parameters required means that the model is suitable for addition to catchment scale models. Keywords: soil temperature, snow model

scholarly journals Quality control of 10-min soil temperatures data at RMI

2015 ◽  
Vol 12 (1) ◽  
pp. 23-30 ◽  
Author(s):  
C. Bertrand ◽  
L. González Sotelino ◽  
M. Journée
Keyword(s):  
Quality Control ◽  
Soil Temperature ◽  
Bare Soil ◽  
Climate Conditions ◽  
Air Temperatures ◽  
Temperature Observation ◽  
Soil Temperatures ◽  
Different Depths ◽  
Temperature Records ◽  
Energy Processes

Abstract. Soil temperatures at various depths are unique parameters useful to describe both the surface energy processes and regional environmental and climate conditions. To provide soil temperature observation in different regions across Belgium for agricultural management as well as for climate research, soil temperatures are recorded in 13 of the 20 automated weather stations operated by the Royal Meteorological Institute (RMI) of Belgium. At each station, soil temperature can be measured at up to 5 different depths (from 5 to 100 cm) in addition to the bare soil and grass temperature records. Although many methods have been developed to identify erroneous air temperatures, little attention has been paid to quality control of soil temperature data. This contribution describes the newly developed semi-automatic quality control of 10-min soil temperatures data at RMI.

Cover crop effects on soil temperature in a clay loam soil in southwestern Ontario

2021 ◽  
pp. 1-10
Author(s):  
X.M. Yang ◽  
W.D. Reynolds ◽  
C.F. Drury ◽  
M.D. Reeb
Keyword(s):  
Soil Temperature ◽  
Cover Crops ◽  
Environmental Performance ◽  
Cover Crop ◽  
Crop Production ◽  
Surface Soil ◽  
Clay Loam ◽  
Near Surface ◽  
Soil Temperatures ◽  
Surface Soil Temperature

Although it is well established that soil temperature has substantial effects on the agri-environmental performance of crop production, little is known of soil temperatures under living cover crops. Consequently, soil temperatures under a crimson clover and white clover mix, hairy vetch, and red clover were measured for a cool, humid Brookston clay loam under a corn–soybean–winter wheat/cover crop rotation. Measurements were collected from August (after cover crop seeding) to the following May (before cover crop termination) at 15, 30, 45, and 60 cm depths during 2018–2019 and 2019–2020. Average soil temperatures (August–May) were not affected by cover crop species at any depth, or by air temperature at 60 cm depth. During winter, soil temperatures at 15, 30, and 45 cm depths were greater under cover crops than under a no cover crop control (CK), with maximum increase occurring at 15 cm on 31 January 2019 (2.5–5.7 °C) and on 23 January 2020 (0.8–1.9 °C). In spring, soil temperatures under standing cover crops were cooler than the CK by 0.1–3.0 °C at 15 cm depth, by 0–2.4 °C at the 30 and 45 cm depths, and by 0–1.8 °C at 60 cm depth. In addition, springtime soil temperature at 15 cm depth decreased by about 0.24 °C for every 1 Mg·ha−1 increase in live cover crop biomass. Relative to bare soil, cover crops increased near-surface soil temperature during winter but decreased near-surface soil temperature during spring. These temperature changes may have both positive and negative effects on the agri-environmental performance of crop production.

scholarly journals Seasonal dynamics of methane emissions from a subarctic fen in the Hudson Bay Lowlands

2013 ◽  
Vol 10 (7) ◽  
pp. 4465-4479 ◽  
Author(s):  
K. L. Hanis ◽  
M. Tenuta ◽  
B. D. Amiro ◽  
T. N. Papakyriakou
Keyword(s):  
Soil Temperature ◽  
Air Temperature ◽  
Growing Season ◽  
Near Surface ◽  
Growing Seasons ◽  
Air Temperatures ◽  
Soil Temperatures ◽  
Surface Soil Temperature ◽  
Filling Method ◽  
Highly Correlated

Abstract. Ecosystem-scale methane (CH4) flux (FCH4) over a subarctic fen at Churchill, Manitoba, Canada was measured to understand the magnitude of emissions during spring and fall shoulder seasons, and the growing season in relation to physical and biological conditions. FCH4 was measured using eddy covariance with a closed-path analyser in four years (2008–2011). Cumulative measured annual FCH4 (shoulder plus growing seasons) ranged from 3.0 to 9.6 g CH4 m−2 yr−1 among the four study years, with a mean of 6.5 to 7.1 g CH4 m−2 yr−1 depending upon gap-filling method. Soil temperatures to depths of 50 cm and air temperature were highly correlated with FCH4, with near-surface soil temperature at 5 cm most correlated across spring, fall, and the shoulder and growing seasons. The response of FCH4 to soil temperature at the 5 cm depth and air temperature was more than double in spring to that of fall. Emission episodes were generally not observed during spring thaw. Growing season emissions also depended upon soil and air temperatures but the water table also exerted influence, with FCH4 highest when water was 2–13 cm below and lowest when it was at or above the mean peat surface.

The effect of soil temperature and light on sprouting and rooting of root cuttings of hybrid aspen clones

2005 ◽  
Vol 35 (11) ◽  
pp. 2671-2678 ◽  
Author(s):  
N Stenvall ◽  
T Haapala ◽  
S Aarlahti ◽  
P Pulkkinen
Keyword(s):  
Soil Temperature ◽  
Populus Tremuloides ◽  
Hybrid Aspen ◽  
Light Conditions ◽  
Dark Treatment ◽  
Sand Mixture ◽  
Negative Effect ◽  
Soil Temperatures ◽  
Time Required ◽  
Better Than

Root cuttings from five clones of hybrid aspen (Populus tremula L. × Populus tremuloides Michx.) obtained from 2-year-old stock plants were grown in a peat–sand mixture (soil) at four soil temperatures (18, 22, 26, and 30 °C). Half of the cuttings were grown in light and the rest in darkness. The root cuttings that were grown at the highest soil temperature sprouted and rooted significantly better than the cuttings grown at the lower temperatures. Light did not affect the sprouting of root cuttings but did have a negative effect on their rooting. Moreover, the clones varied significantly in sprouting and rooting percentages, as well as in the time required for sprouting. In general, higher soil temperatures hastened sprouting of the cuttings. Sprouting was also faster in the light than in the dark treatment. Differences in soil temperature, light conditions, or clone had no significant effect on rooting time.

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