scholarly journals ModellingG×Ewith historical weather information improves genomic prediction in new environments

2017 ◽  
Author(s):  
Jussi Gillberg ◽  
Pekka Marttinen ◽  
Hiroshi Mamitsuka ◽  
Samuel Kaski
Keyword(s):  
Yield Potential ◽  
Strong Impact ◽  
Barley Cultivars ◽  
Weather Information ◽  
Weather Observations ◽  
Main Driver ◽  
New Locations ◽  
Using Data ◽  
New Generation ◽  
Genomic Covariates

Interaction between the genotype and the environment (G×E) has a strong impact on the yield of major crop plants. Although influential, takingG×Eexplictily into account in plant breeding has remained difficult. RecentlyG×Ehas been predicted from environmental and genomic covariates, but existing works have not shown that generalization to new environments and years without access to in-season data is possible and practical applicability remains unclear. Using data from a Barley breeding program in Finland, we construct an in-silico experiment to study the viability ofG×Eprediction under practical constraints. We show that the response to the environment of a new generation of untested Barley cultivars can be predicted in new locations and years using genomic data, machine learning and historical weather observations for the new locations. Our results highlight the need for models ofG×E: non-linear effects clearly dominate linear ones and the interaction between the soil type and daily rain is identified as the main driver forG×Efor Barley in Finland. Our study implies that genomic selection can be used to capture the yield potential inG×Eeffects for future growth seasons, providing a possible means to achieve yield improvements, needed for feeding the growing population.

scholarly journals Modelling G×E with historical weather information improves genomic prediction in new environments

2019 ◽  
Vol 35 (20) ◽  
pp. 4045-4052 ◽  
Author(s):  
Jussi Gillberg ◽  
Pekka Marttinen ◽  
Hiroshi Mamitsuka ◽  
Samuel Kaski
Keyword(s):  
Supplementary Information ◽  
Yield Potential ◽  
Strong Impact ◽  
Barley Cultivars ◽  
Weather Information ◽  
Main Driver ◽  
New Locations ◽  
Using Data ◽  
New Generation ◽  
Genomic Covariates

AbstractMotivationInteraction between the genotype and the environment (G×E) has a strong impact on the yield of major crop plants. Although influential, taking G×E explicitly into account in plant breeding has remained difficult. Recently G×E has been predicted from environmental and genomic covariates, but existing works have not shown that generalization to new environments and years without access to in-season data is possible and practical applicability remains unclear. Using data from a Barley breeding programme in Finland, we construct an in silico experiment to study the viability of G×E prediction under practical constraints.ResultsWe show that the response to the environment of a new generation of untested Barley cultivars can be predicted in new locations and years using genomic data, machine learning and historical weather observations for the new locations. Our results highlight the need for models of G×E: non-linear effects clearly dominate linear ones, and the interaction between the soil type and daily rain is identified as the main driver for G×E for Barley in Finland. Our study implies that genomic selection can be used to capture the yield potential in G×E effects for future growth seasons, providing a possible means to achieve yield improvements, needed for feeding the growing population.Availability and implementationThe data accompanied by the method code (http://research.cs.aalto.fi/pml/software/gxe/bioinformatics_codes.zip) is available in the form of kernels to allow reproducing the results.Supplementary informationSupplementary data are available at Bioinformatics online.

SUMMARY: PAPERS PRESENTED AT INTERNATIONAL WORKSHOP ON INCREASING WHEAT YIELD POTENTIAL, CIMMYT, OBREGON, MEXICO, 20–24 MARCH 2006 Challenges to international wheat improvement

2007 ◽  
Vol 145 (3) ◽  
pp. 223-227 ◽  
Author(s):  
M. P. REYNOLDS ◽  
P. R. HOBBS ◽  
H. J. BRAUN
Keyword(s):  
Management Practices ◽  
International Workshop ◽  
Green Revolution ◽  
Wheat Yield ◽  
Developed Countries ◽  
Yield Potential ◽  
Agronomic Practices ◽  
Agronomic Management ◽  
Genetically Improved ◽  
New Generation

Wheat is grown on 210 million ha throughout the world producing approximately 600 million tonnes of grain (10 year average; FAO 2005) and providing on average one fifth of the total calorific input of the world's population (FAO 2003). For some regions such as North Africa, Turkey and Central Asia, wheat provides half of total dietary energy intake. Of the cultivated wheat area, half is located in less developed countries where there have been steady increases in productivity since the green revolution, associated with genetic improvements in yield potential, resistance to diseases and adaptation to abiotic stresses (Reynolds & Borlaug 2006a, b) as well as better agronomic practices (Derpsch 2005). Nonetheless, challenges to wheat production are still considerable, especially in the developing world, not only because of increased demand but also because of the increased scarcity of water resources (Rosegrant 1997; WMO 1997), ever more unpredictable climates (Fischer et al. 2002), increased urbanization and loss of good quality land away from agriculture (Hobbs 2007), and decreased public sector investment in agriculture and rural affairs (Falcon & Naylor 2005). To meet demand in a sustainable way, more resources are required to breed a new generation of genetically improved cultivars as well as implement resource-conserving agronomic management practices.

scholarly journals Adaptability of prospective spring barley cultivars bred in Federal Agricultural Research Center of the North-East

2021 ◽  
Vol 36 ◽  
pp. 01013
Author(s):  
Irina N. Shchennikova ◽  
Olga N. Shupletsova ◽  
Irina Yu. Zaytseva ◽  
Larissa P. Kokina ◽  
Rimma I. Vyatkina
Keyword(s):  
Agricultural Research ◽  
Spring Barley ◽  
Culture Method ◽  
Field Studies ◽  
Tube Formation ◽  
Yield Potential ◽  
High Yield ◽  
Barley Cultivars ◽  
North East ◽  
Yield Capacity

Based on the statistical assessment of long-term field studies, in competitive variety tests, barley cultivars were identified adaptive to the conditions of the region, promising for transfer to the State variety test. As a result of the studies, a promising breeding material was created. The efficiency of using various methods of creating a new initial material, in particular, the cell culture method, is shown. A statistically significant correlation was established between the value of the hydrothermal coefficient (GTK) in the period “leaf tube formation - heading” and the yield capacity of a cultivar (r = 0.520). High variability (V = 24.4%) in the duration of the inter-stage period “leaf tube formation - heading” was revealed in the cultivars of competitive variety testing. Cultivars 94-13 and 38-15 are distinguished by a high yield potential (up to 6.4… 6.9 t/ha) and the duration of inter-stage periods, at which the main stages of organogenesis occur at the most favorable combination of heat and moisture for the potential development of plant features and properties. Cultivars 207-15, 38-15, and regenerant 550-08, characterized by high annual average yield capacity (5.9…5.7 tons/ha) and adaptability, are promising for transfer to the Russian Federation State variety test.

Understanding the Links between Mentoring and Self-Efficacy in the New Generation of Women STEM Scholars

2010 ◽  
pp. 97-117 ◽  
Author(s):  
Elizabeth Yost ◽  
Donna M. Handley ◽  
Shelia R. Cotten ◽  
Vicki Winstead
Keyword(s):  
Self Efficacy ◽  
Mentoring Programs ◽  
National Study ◽  
Stem Fields ◽  
New Faculty ◽  
Gender Inequity ◽  
Mentoring Practices ◽  
Using Data ◽  
New Generation ◽  
The Impact

American colleges and universities are in need of innovative approaches to recruit and retain the upcoming generation of new faculty members. Specifically within the STEM (Science, Technology, Engineering, and Math) fields, there is an additional need to focus on meeting the needs of women in order to begin to address gender inequity within STEM. This chapter examines the impact of mentoring on self-efficacy for female graduate students and post doctoral fellows in STEM fields. Using data from a national study of selected U.S. academic institutions, recommendations are made in order to enhance mentoring practices that will reduce the barriers women face within STEM fields. Quality mentoring programs represent a viable way to enhance institutional change that may result in increased numbers of women in STEM fields.

scholarly journals Propagation of soil moisture memory to streamflow and evapotranspiration in Europe

2013 ◽  
Vol 17 (10) ◽  
pp. 3895-3911 ◽  
Author(s):  
R. Orth ◽  
S. I. Seneviratne
Keyword(s):  
Soil Moisture ◽  
Low Frequency ◽  
Balance Model ◽  
Catchment Scale ◽  
Meteorological Forcing ◽  
Main Driver ◽  
Memory Persistence ◽  
New Perspective ◽  
Using Data ◽  
Frequency Variations

Abstract. As a key variable of the land-climate system soil moisture is a main driver of streamflow and evapotranspiration under certain conditions. Soil moisture furthermore exhibits outstanding memory (persistence) characteristics. Many studies also report distinct low frequency variations for streamflow, which are likely related to soil moisture memory. Using data from over 100 near-natural catchments located across Europe, we investigate in this study the connection between soil moisture memory and the respective memory of streamflow and evapotranspiration on different time scales. For this purpose we use a simple water balance model in which dependencies of runoff (normalised by precipitation) and evapotranspiration (normalised by radiation) on soil moisture are fitted using streamflow observations. The model therefore allows us to compute the memory characteristics of soil moisture, streamflow and evapotranspiration on the catchment scale. We find considerable memory in soil moisture and streamflow in many parts of the continent, and evapotranspiration also displays some memory at monthly time scale in some catchments. We show that the memory of streamflow and evapotranspiration jointly depend on soil moisture memory and on the strength of the coupling of streamflow and evapotranspiration to soil moisture. Furthermore, we find that the coupling strengths of streamflow and evapotranspiration to soil moisture depend on the shape of the fitted dependencies and on the variance of the meteorological forcing. To better interpret the magnitude of the respective memories across Europe, we finally provide a new perspective on hydrological memory by relating it to the mean duration required to recover from anomalies exceeding a certain threshold.

EFFETS DES METHODES DE SEMIS SUR L’EVALUATION DES CULTIVARS DE CEREALES

1975 ◽  
Vol 55 (1) ◽  
pp. 233-239
Author(s):  
C. A. ST-PIERRE ◽  
J. P. DUBUC ◽  
F. M. GAUTHIER ◽  
H. R. KLINCK
Keyword(s):  
Experimental Testing ◽  
Triticum Aestivum L ◽  
Yield Potential ◽  
Individual Plant ◽  
Hordeum Vulgare L ◽  
Yield Increase ◽  
Testing Procedures ◽  
Barley Cultivars ◽  
Adequate Evaluation ◽  
Significant Yield

The differential response of a number of cultivars of wheat (Triticum aestivum L.), barley (Hordeum vulgare L.) and oats (Avena sativa L.) to different methods of seeding was studied. Results of eight station–years with wheat show significant differences in yield among the cultivars and among seeding methods. The highest rate of seeding of wheat, 118 kg/ha, resulted in a significant yield increase, but the yield increase was smaller with narrower rows. The interaction of methods of seeding × cultivars was not significant, indicating that the presently used testing procedures give adequate evaluation of yield potential of wheat cultivars. The stable cultivar performance at the various rates of seeding suggests that efficient individual plant selection could be made at lower rates of seeding in rows 15 cm apart. Results of eight station–years with barley and 12 station–years with oats show that the experimental testing procedures used are adequate to evaluate oats and barley cultivars for yield.

scholarly journals Extracting weather information from a plantation document

2019 ◽  
Vol 15 (2) ◽  
pp. 477-492
Author(s):  
Gregory Burris ◽  
Jane Washburn ◽  
Omar Lasheen ◽  
Sophia Dorribo ◽  
James B. Elsner ◽  
...  
Keyword(s):  
Historical Period ◽  
Climate Data ◽  
Temperature Index ◽  
Weather Information ◽  
Historical Archives ◽  
Weather Observations ◽  
Weather And Climate ◽  
Climate Studies ◽  
Modern Era ◽  
Local Weather

Abstract. The authors introduce a method for extracting weather and climate data from a historical plantation document. They demonstrate the method on a document from Shirley Plantation in Virginia (USA) covering the period 1816–1842. They show how the resulting data are organized into a spreadsheet that includes direct weather observations and information on various cultivars. They then give three examples showing how the data can be used for climate studies. The first example is a comparison of spring onset between the plantation era and the modern era. A modern median final spring freeze event (for the years 1943–2017) occurs a week earlier than the historical median (for the years 1822–1839). The second analysis involves developing an index for midsummer temperatures from the timing of the first malaria-like symptoms in the plantation population each year. The median day when these symptoms would begin occurring in the modern period is a month and a half earlier than the median day they occurred in the historical period. The final example is a three-point temperature index generated from ordinal weather descriptions in the document. The authors suggest that this type of local weather information from historical archives, either direct from observations or indirect from phenophase timing, can be useful toward a more complete understanding of climates of the past.

Application of the Nelson model to four timelag fuel classes using Oklahoma field observations: model evaluation and comparison with National Fire Danger Rating System algorithms

2007 ◽  
Vol 16 (2) ◽  
pp. 204 ◽  
Author(s):  
J. D. Carlson ◽  
Larry S. Bradshaw ◽  
Ralph M. Nelson ◽  
Randall R. Bensch ◽  
Rafal Jabrzemski
Keyword(s):  
Fire Danger ◽  
Rating System ◽  
Field Observations ◽  
Fuel Moisture ◽  
Next Generation ◽  
Nelson Model ◽  
Weather Information ◽  
Weather Observations ◽  
Fire Danger Rating System ◽  
Better Than

The application of a next-generation dead-fuel moisture model, the ‘Nelson model’, to four timelag fuel classes using an extensive 21-month dataset of dead-fuel moisture observations is described. Developed by Ralph Nelson in the 1990s, the Nelson model is a dead-fuel moisture model designed to take advantage of frequent automated weather observations. Originally developed for 10-h fuels, the model is adaptable to other fuel size classes through modification of the model’s fuel stick parameters. The algorithms for dead-fuel moisture in the National Fire Danger Rating System (NFDRS), on the other hand, were originally developed in the 1970s, utilise once-a-day weather information, and were designed to estimate dead-fuel moisture for mid-afternoon conditions. Including all field observations over the 21-month period, the Nelson model showed improvement over NFDRS for each size fuel size class, with r2 values ranging from 0.51 (1000-h fuels) to 0.79 (10-h fuels). However, for observed fuel moisture at or below 30%, the NFDRS performed better than the Nelson model for 1-h fuels and was about the same accuracy as the Nelson for 10-h fuels. The Nelson model is targeted for inclusion in the next-generation NFDRS.

The Future of the Global Weather Enterprise: Opportunities and Risks

2018 ◽  
Vol 99 (10) ◽  
pp. 2003-2008 ◽  
Author(s):  
Alan Thorpe ◽  
David Rogers
Keyword(s):  
Value Chain ◽  
Mutual Understanding ◽  
Continual Improvement ◽  
Know How ◽  
Weather Information ◽  
Research Technology ◽  
Economic Output ◽  
A Value ◽  
Weather Observations ◽  
To Come

AbstractThe Global Weather Enterprise (GWE) encompasses the scientific research, technology, observations, modeling, forecasting, and forecast products that need to come together to provide accurate and reliable weather information and services that save lives, protect infrastructure, and enhance economic output. It is a value chain from weather observations to, ultimately, the creation of actionable analysis-and-forecast weather information of huge benefit to society. The GWE is a supreme exemplar of the value of international cooperation, public–private engagement, and scientific and technological know-how. It has been a successful enterprise, but one that has ever-increasing requirements for continual improvement as population density increases and climate change takes place so that the impacts of weather hazards can be mitigated as far as possible. However, the GWE is undergoing a period of significant change arising, for example, from the growing need for more accurate and reliable weather information, advances coming from science and technology, and the expansion of private sector capabilities. These changes offer real opportunities for the GWE but also present a number of obstacles and risks that could, if not addressed, stifle this development, adversely impacting the societies it aims to serve. This essay aims to catalyze the GWE to address the issues collectively, by dialogue, engagement, and mutual understanding.

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