scholarly journals Genetic and management adaptation of field bean (Vicia faba L.) in Finland

1981 ◽  
Vol 53 (5) ◽  
pp. 328-340
Author(s):  
Seppo Pulli ◽  
Mauritz Vestberg
Keyword(s):  
Population Density ◽  
Maximum Yield ◽  
Grain Filling ◽  
Climatic Conditions ◽  
Plant Diseases ◽  
Field Bean ◽  
Early Variety ◽  
Seeding Time ◽  
Grain Filling Period ◽  
The University

The investigation of field bean adaptation in Finnish climatic conditions was carried out at the University of Helsinki in 1976—77. The main objectives were to study the effects of seeding time and population density on the quantity and quality of the yield and the vegetative features in the development of two different types of field bean varieties. Field bean yielded 4061 kg/ha in 1976. In 1977only 2042kg/ha was harvested due to the lack of light during the grain filling period and the presense of plant diseases. Delayed seeding lowered yields in both years. Maximum yield was obtained with the seed rate of 240 kg/ha. Two weeks delay in the seeding speeded up flowering by two days. Temperature sum in degree days from seeding to emergence was 140—170°C, from seeding to flowering 618—637°C and from seeding to maturity 1670—1890°C. LAI was 5.7 for early variety and 4.3 for late variety at the time of pod setting representing very effective situation for CGR. Number and distribution of internodes, pods and seeds were primarily influenced by population density and secondly by the differences between varieties.

scholarly journals Using Satellite Data to Optimize Wheat Yield and Quality under Climate Change

2021 ◽  
Vol 13 (11) ◽  
pp. 2049
Author(s):  
Shilo Shiff ◽  
Itamar M. Lensky ◽  
David J. Bonfil
Keyword(s):  
Land Surface ◽  
Wheat Yield ◽  
Grain Filling ◽  
High Temperature Stress ◽  
Climatic Conditions ◽  
Google Earth ◽  
Sowing Time ◽  
Wheat Field ◽  
Yield And Quality ◽  
Grain Filling Period

Climatic conditions during the grain-filling period are a major factor affecting wheat grain yield and quality. Wheat in many semi-arid and arid areas faces high-temperature stress during this period. Remote sensing can be used to monitor both crops and environmental temperature. The objective of this study was to develop a tool to optimize field management (cultivar and sowing time). Analysis of 155 cultivar experiments (from 10 growth seasons) representing different environmental conditions revealed the required degree-days for each Israeli spring wheat cultivar to reach heading (from emergence). We developed a Google Earth Engine (GEE) app to analyze time series of gap-filled 1 km MODIS land surface temperature (LSTcont). By changing the cultivar and/or emergence date in the GEE app, the farmer can “expose” each wheat field to different climatic conditions during the grain-filling period, thereafter enabling him to choose the best cultivar to be sown in the field with the right timing. This approach is expected to reduce the number of fields that suffer from heat stress during the grain-filling period. The app can be also used to assess the effects of different global warming scenarios and to plan adaptation strategies in other regions too.

Effects of plant population density on determinate and indeterminate forms of winter field beans (Vicia faba) 2. Growth and development

1991 ◽  
Vol 116 (3) ◽  
pp. 385-393 ◽  
Author(s):  
C. J. Pilbeam ◽  
P. D. Hebblethwaite ◽  
T. E. Nyongesa ◽  
H. E. Ricketts
Keyword(s):  
Population Density ◽  
Leaf Area ◽  
Plant Population ◽  
Field Bean ◽  
Matter Production ◽  
Competition For Light ◽  
Plant Population Density ◽  
The University ◽  
Field Beans ◽  
Target Plant

SUMMARYIn studies at the University of Nottingham at Sutton Bonington in two consecutive seasons beginning in 1986/87, Bourdon, an indeterminate cultivar, and 858, a determinate selection (provided by Plant Breeding International, Cambridge), were compared under six target plant population densities ranging from 10 to 80 plants/m2.As the season progressed, total dry matter production increased to a maximum and then declined. However, growth rates slowed at pod set because, it is suggested, of the change in the chemical composition of the newly synthesized biomass, from carbohydrate to protein, at that time. Leaf area duration was greater in Bourdon than in 858, especially during pod set, but it bore no relation to seed yield. Specific leaf area was unaffected by competition for light. It is proposed that changes in plant population density affect the competition for assimilates within a plant rather than the competition for light between different plants. Losses of branches and reproductive nodes, with time, are cited as evidence for this. The apparent causes of the lower yield of determinate forms of winter field bean relative to indeterminate forms are discussed.

scholarly journals Management techniques of maize crop in the marginal growing area in Finland

1979 ◽  
Vol 51 (1) ◽  
pp. 210-221
Author(s):  
Seppo Pulli ◽  
Osmo Kara ◽  
P. M. A. Tigerstedt
Keyword(s):  
Maximum Yield ◽  
Weather Conditions ◽  
Management Technique ◽  
Maize Crop ◽  
Forage Crop ◽  
Maize Population ◽  
Silage Maize ◽  
Seeding Time ◽  
Growing Conditions ◽  
The University

Silage maize management studies were carried out in 1976—78 on the University farm in Siuntio in southern Finland. Seeding time trials in 1976—77 consisted of three different types of varieties seeded at four different times between May 11 and June 8. In 1978 three seeding dates were tested in relation to the seeding depth of the maize. Population density studies were carried out in 1976—77. As a result of the management studies it can be concluded that the weather conditions were so unfavorable that true differences could not be found because even the best alternative in the management technique did not give a satisfactory agronomic result. Seeding dates from May 15 to May 25 can be recommended. Relatively heavy frosts in early June (—4°C to—6° C) will hurt stands but they do not kill the plant. The advance earned with early planting is thus not totally lost through the frosts Seeding depths of 5 to 7 cm are recommended. Population densities more than 10 plants/m2 are not necessary for the maximum yield. In average or better than average growing conditions the planting densities of 6 to 8 plants/m2 could yield a more mature forage crop.

Influence of Canopy Temperature (CT) During Grain-Filling Period on Yield and Effects of Several CT-Associated SSR Loci

2015 ◽  
Vol 41 (4) ◽  
pp. 548 ◽  
Author(s):  
Dong-Ling ZHANG ◽  
Hong-Na ZHANG ◽  
Chen-Yang HAO ◽  
Lan-Fen WANG ◽  
Tian LI ◽  
...  
Keyword(s):  
Canopy Temperature ◽  
Grain Filling ◽  
Ssr Loci ◽  
Grain Filling Period

Effect of PASP-KT-NAA on Leaf Senescence and Grain Filling Rate during the Grain-Filling Period in Different Temperature Zones

2013 ◽  
Vol 38 (9) ◽  
pp. 1698-1709
Author(s):  
Tian-Jun XU ◽  
Zhi-Qiang DONG ◽  
Jiao GAO ◽  
Chuan-Xiao CHEN ◽  
Liu JIAO ◽  
...  
Keyword(s):  
Leaf Senescence ◽  
Grain Filling ◽  
Filling Rate ◽  
Grain Filling Rate ◽  
Grain Filling Period

Grain Filling Period of Sorghum Parents and Hybrids 1

Crop Science ◽  
1972 ◽  
Vol 12 (5) ◽  
pp. 690-691 ◽  
Author(s):  
J. R. Quinby
Keyword(s):  
Grain Filling ◽  
Grain Filling Period

scholarly journals The Impact of Health Policies and Sociodemographic Factors on Doubling Time of the COVID-19 Pandemic in Mexico

2021 ◽  
Vol 18 (5) ◽  
pp. 2354
Author(s):  
Lina Díaz-Castro ◽  
Héctor Cabello-Rangel ◽  
Kurt Hoffman
Keyword(s):  
Population Density ◽  
Doubling Time ◽  
Sociodemographic Factors ◽  
Health Policies ◽  
Government Response ◽  
University Of Oxford ◽  
Negative Effect ◽  
Population Sizes ◽  
The University ◽  
The Impact

Background. The doubling time is the best indicator of the course of the current COVID-19 pandemic. The aim of the present investigation was to determine the impact of policies and several sociodemographic factors on the COVID-19 doubling time in Mexico. Methods. A retrospective longitudinal study was carried out across March–August, 2020. Policies issued by each of the 32 Mexican states during each week of this period were classified according to the University of Oxford Coronavirus Government Response Tracker (OxCGRT), and the doubling time of COVID-19 cases was calculated. Additionally, variables such as population size and density, poverty and mobility were included. A panel data model was applied to measure the effect of these variables on doubling time. Results. States with larger population sizes issued a larger number of policies. Delay in the issuance of policies was associated with accelerated propagation. The policy index (coefficient 0.60, p < 0.01) and the income per capita (coefficient 3.36, p < 0.01) had a positive effect on doubling time; by contrast, the population density (coefficient −0.012, p < 0.05), the mobility in parks (coefficient −1.10, p < 0.01) and the residential mobility (coefficient −4.14, p < 0.01) had a negative effect. Conclusions. Health policies had an effect on slowing the pandemic’s propagation, but population density and mobility played a fundamental role. Therefore, it is necessary to implement policies that consider these variables.

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