scholarly journals Determination of annual generations of Phytomyza orobanchia Kalt. (Diptera: Agromyzidae), using growing degree-days in Alexandria region, Egypt

2018 ◽  
Vol 28 (1) ◽  
Author(s):  
M. A. S. Al-Eryan ◽  
Amany M. H. Abu-Shall ◽  
Alaa H. Ibrahim
Keyword(s):  
Growing Degree Days ◽  
Degree Days ◽  
Phytomyza Orobanchia

Studies on Determination of Critical Growing Degree Days, Base Temperature (Tb) and Response of Temperature Variations on Flowering and Yield per se in Cowpea [Vigna unguiculata (L.) Walp.]

2020 ◽  
Author(s):  
Venkatesh Bondade ◽  
Sanjeev K Deshpande
Keyword(s):  
Dry Matter ◽  
Significant Negative Correlation ◽  
Growing Degree Days ◽  
Base Temperature ◽  
Degree Days ◽  
Temperature Variations ◽  
Days To Flowering ◽  
Matter Production ◽  
Flowering Initiation

Growing degree days (GDD) or heat units accumulation is the major factor that affects the dry matter production in the plants. In the present investigation eleven genotypes were used to screen for temperature insensitivity through staggered plantings across the seasons in a year. Days to flowering initiation was recorded and base temperature (Tb) was determined using mean daily air temperature (MAT). GDD of individual genotypes was estimated using base temperatures of particular genotypes. It was observed that the GDD, days to flowering initiation and yield were exhibited high variation across the seasons, the flowering time from days to planting (FTDAP) registered significant negative correlation with GDD and MAT and positively correlated with yield. Whereas GDD is positively correlated with MAT and negatively correlated with yield. Here three genotypes namely, IC202926, IC198326 and IC257428 were identified as temperature insensitive genotypes as their performances were comparable across the seasons without much fluctuations.

scholarly journals Present and future responses of growing degree days for Crete Island in Greece

2017 ◽  
Vol 14 ◽  
pp. 1-5 ◽  
Author(s):  
Spyridon Paparrizos ◽  
Andreas Matzarakis
Keyword(s):  
Plant Species ◽  
Spatial Interpolation ◽  
Agricultural Science ◽  
Growing Degree Days ◽  
Degree Days ◽  
Factors Affecting ◽  
Crete Island ◽  
The Future ◽  
Flower Phenology

Abstract. Climate affects practically all the physiological processes that determine plant life (IPCC, 2014). A major challenge and objective of the agricultural science is to predict the occurrences of specific physical or biological events. For this reason, flower phenology has been widely used to study the flowering in plant species of economic interest, and in this concept, temperature and heat units have been widely accepted as the most important factors affecting processes leading to flowering. The determination of heat requirements in the first developing phases of plants has been expressed as Growing Degree Days (GDD). Determination of GDD is useful for achieving a better understanding of the flowering season development in several plant species, and for forecasting when flowering will occur (Paparrizos and Matzarakis, 2017). Temperature and GDD represent two important spatially-dynamic climatic variables, as they both play vital roles in influencing forest development by directly affecting plant functions such as evapotranspiration, photosynthesis and plant transpiration. Understanding the spatial distribution of GDD is crucial to the practice of sustainable agricultural and forest management, as GDD relates to the integration of growth and provides precise point estimates (Hasan et al., 2007; Matzarakis et al., 2007). The aim of the current study was to estimate and map through downscaling spatial interpolation and multi-linear regression techniques, the future variation of GDD for the periods 2021–2050 and 2071–2100, under the A1B and B1 IPCC emission scenarios in relation with the reference periods for Crete Island in Greece. Future temperature data were obtained, validated and analysed from the ENSEMBLES European project. A combination of dynamical and statistical approach was conducted in order to downscale and perform the spatial interpolation of GDD through ArcGIS 10.2.1. The results indicated that in the future, GDD will be increased and the existing cultivations can reach maturity sooner. Nevertheless, rough topography will act as an inhibitor towards the expansion of the existing cultivations in higher altitudes.

Evaluation of Finger Millet Varieties under Rainfed Condition of Eastern India

2017 ◽  
Vol 4 (03) ◽  
Author(s):  
M. K. Singh ◽  
VINOD KUMAR ◽  
SHAMBHU PRASAD
Keyword(s):  
Field Experiment ◽  
Finger Millet ◽  
Yield Potential ◽  
Growing Degree Days ◽  
Eastern India ◽  
Degree Days ◽  
Rainfed Condition ◽  
Net Returns ◽  
Humid Environment ◽  
Use Efficiency

A field experiment was carried out during the kharif of 2014 and 2015 to evaluate the yield potential, economics and thermal utilization in eleven finger millet varieties under the rainfed condition of the sub-humid environment of South Bihar of Eastern India. Results revealed that the significantly higher grain yield (20.41 q ha-1), net returns (Rs 25301) and B: C ratio (1.51) was with the finger millet variety ‘GPU 67’ but was being at par to ‘GPU28’and ‘RAU-8’, and significantly superior over remaining varieties. The highest heat units (1535.1oC day), helio-thermal units (7519.7oC day hours), phenothermal index (19.4 oC days day-1) were recorded with variety ‘GPU 67’ followed by ‘RAU 8’ and ‘GPU 28’ and lowest in ‘VL 149’ at 50 % anthesis stage. Similarly, the highest growing degree days (2100 oC day), helio-thermal units (11035.8 oC day hours) were noted with ‘GPU 67’ followed by ‘RAU 8’ and ‘GPU 28’ at maturity. The highest heat use efficiency (0.97 kg ha-1 oC day) and helio-thermal use efficiency (0.19 kg ha-1 oC day hour) were in ‘GPU 67’ followed by ‘VL 315’.

scholarly journals Determining the critical period for weed control in high-yielding cotton using common sunflower as a mimic weed

2019 ◽  
Vol 33 (6) ◽  
pp. 800-807 ◽  
Author(s):  
Graham W. Charles ◽  
Brian M. Sindel ◽  
Annette L. Cowie ◽  
Oliver G. G. Knox
Keyword(s):  
Weed Control ◽  
Critical Period ◽  
Yield Loss ◽  
Field Studies ◽  
Growing Degree Days ◽  
Degree Days ◽  
Weed Density ◽  
High Level ◽  
The Cost ◽  
Planting Season

AbstractField studies were conducted over six seasons to determine the critical period for weed control (CPWC) in high-yielding cotton, using common sunflower as a mimic weed. Common sunflower was planted with or after cotton emergence at densities of 1, 2, 5, 10, 20, and 50 plants m−2. Common sunflower was added and removed at approximately 0, 150, 300, 450, 600, 750, and 900 growing degree days (GDD) after planting. Season-long interference resulted in no harvestable cotton at densities of five or more common sunflower plants m−2. High levels of intraspecific and interspecific competition occurred at the highest weed densities, with increases in weed biomass and reductions in crop yield not proportional to the changes in weed density. Using a 5% yield-loss threshold, the CPWC extended from 43 to 615 GDD, and 20 to 1,512 GDD for one and 50 common sunflower plants m−2, respectively. These results highlight the high level of weed control required in high-yielding cotton to ensure crop losses do not exceed the cost of control.

scholarly journals Growth and Development of Purple Nutsedge Based on Days or Thermal Units

2015 ◽  
Vol 33 (2) ◽  
pp. 165-173 ◽  
Author(s):  
R.S.O. Lima ◽  
E.C.R. Machado ◽  
A.P.P. Silva ◽  
B.S. Marques ◽  
M.F. Gonçalves ◽  
...  
Keyword(s):  
Plant Growth ◽  
Mathematical Models ◽  
Growth And Development ◽  
Dry Matter ◽  
Cyperus Rotundus ◽  
Growing Degree Days ◽  
Plant Growth And Development ◽  
Degree Days ◽  
Purple Nutsedge ◽  
Independent Trials

This work was carried out with the objective of elaborating mathematical models to predict growth and development of purple nutsedge (Cyperus rotundus) based on days or accumulated thermal units (growing degree days). Thus, two independent trials were developed, the first with a decreasing photoperiod (March to July) and the second with an increasing photoperiod (August to November). In each trial, ten assessments of plant growth and development were performed, quantifying total dry matter and the species phenology. After that, phenology was fit to first degree equations, considering individual trials or their grouping. In the same way, the total dry matter was fit to logistic-type models. In all regressions four temporal scales possibilities were assessed for the x axis: accumulated days or growing degree days (GDD) with base temperatures (Tb) of 10, 12 and 15 oC. For both photoperiod conditions, growth and development of purple nutsedge were adequately fit to prediction mathematical models based on accumulated thermal units, highlighting Tb = 12 oC. Considering GDD calculated with Tb = 12 oC, purple nutsedge phenology may be predicted by y = 0.113x, while species growth may be predicted by y = 37.678/(1+(x/509.353)-7.047).

Sign in / Sign up

Export Citation Format

Share Document