The Critical Weed-Free Period in Carrot

Weed Science ◽  
2010 ◽  
Vol 58 (3) ◽  
pp. 229-233 ◽  
Author(s):  
Clarence J. Swanton ◽  
John O'Sullivan ◽  
Darren E. Robinson
Keyword(s):  
Yield Potential ◽  
Growing Degree Days ◽  
Herbicide Application ◽  
Degree Days ◽  
Weed Biomass ◽  
Seeding Date ◽  
Weed Emergence

Seeding date and the duration of weed emergence influenced the duration of the critical weed-free period in carrot. The critical weed-free period extended up to 930 growing degree days (GDD), when carrot was seeded in late April. In contrast, the critical weed-free period was short and lasted 414 to 444 GDD, when seeded in mid to late May and weed biomass was less than 650 g m−2. It is important for growers to scout fields for weeds until 930 GDD to protect the yield potential of the carrot crop in earlier planted crops; however, for carrot planted in mid to late May, weeds emerging after 444 GDD did not reduce yield. A useful strategy to reduce reliance on herbicide application would be to delay planting until late in May.

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’.

CHLOROGENIC ACID CONTENT OF SUNFLOWER SEED FLOUR AS AFFECTED BY SEEDING AND HARVEST DATE

1976 ◽  
Vol 56 (4) ◽  
pp. 901-905 ◽  
Author(s):  
D. G. DORRELL
Keyword(s):  
Chlorogenic Acid ◽  
Acid Content ◽  
Vegetative Growth ◽  
Sunflower Seed ◽  
Growing Season ◽  
Growing Degree Days ◽  
Degree Days ◽  
Normal Field ◽  
Seed Flour ◽  
Seeding Date

The effect of seeding date on the chlorogenic acid content of sunflower seed flour was determined by seeding the cultivars Krasnodarets and Peredovik at seven dates, starting on 14 May, over 3 yr. Sequential plantings were made at increments of approximately 70 growing degree days (base = 5.6 C). Plants were harvested at normal field maturity. The time and rate of deposition of chlorogenic acid was determined by harvesting plants at 7-day intervals from 21 to 49 days after flowering. The seeds were dehulled and defatted before determining the chlorogenic acid content of the flour. Chlorogenic acid content declined steadily from an average of 4.22% for the first seeding to 3.30% for the last seeding. About one-half of the total chlorogenic acid was present 21 days after flowering. Deposition continued rapidly for the next 14 days then the level began to stabilize. Delay in seeding tended to shorten the period of vegetative growth and shift the deposition of chlorogenic acid to a cooler portion of the growing season. It is suggested that a combination of these factors caused the reduction in chlorogenic acid content of sunflower flour.

scholarly journals Growing degree days and cover crop type explain weed biomass in winter cover crops

2018 ◽  
Vol 38 (6) ◽  
Author(s):  
Barbara Baraibar ◽  
David A. Mortensen ◽  
Mitchell C. Hunter ◽  
Mary E. Barbercheck ◽  
Jason P. Kaye ◽  
...  
Keyword(s):  
Cover Crops ◽  
Cover Crop ◽  
Growing Degree Days ◽  
Degree Days ◽  
Weed Biomass ◽  
Crop Type ◽  
Winter Cover ◽  
Winter Cover Crops

Microtopography, Microenvironments, and Weed Populations in Ridge-Tilled Soybean

2006 ◽  
Vol 20 (3) ◽  
pp. 593-604
Author(s):  
Thomas W. Jurik
Keyword(s):  
Seedling Emergence ◽  
Growing Season ◽  
Growing Degree Days ◽  
Degree Days ◽  
Weed Species ◽  
Redroot Pigweed ◽  
Giant Foxtail ◽  
Green Foxtail ◽  
Weed Emergence

The effects of microtopographic position on soil microenvironment and weed populations in ridge-tilled soybean were evaluated on three farms in Iowa in 1989 and 1990. In both years, over all weed species (primarily giant foxtail, green foxtail, yellow foxtail, redroot pigweed, and Pennsylvania smartweed), seedling emergence was highest in late May and early June, with few seedlings emerging after mid-June. Weed populations were highest in May and early June, after which rotary hoeing and cultivation reduced weed numbers in all plots. Microtopographic position (row, shoulder, and furrow) had a large effect on soil microenvironment and weed populations. Furrows were the wettest position through most of the growing season. Rows were the warmest position early in the season and the coolest position late in the season. Cumulative weed emergence early in the season was closely related to growing degree days, which accumulated faster in the row position than the furrow position. Following rotary hoeing and cultivation, the row position had significantly more total weeds than the shoulder and furrow positions on all farms in August of both years.

scholarly journals Field-Scale Crop Seeding Date Estimation from MODIS Data and Growing Degree Days in Manitoba, Canada

2019 ◽  
Vol 11 (15) ◽  
pp. 1760 ◽  
Author(s):  
Taifeng Dong ◽  
Jiali Shang ◽  
Budong Qian ◽  
Jiangui Liu ◽  
Jing M. Chen ◽  
...  
Keyword(s):  
Time Series ◽  
Vegetation Index ◽  
Crop Management ◽  
Remote Sensing Data ◽  
Growing Degree Days ◽  
Degree Days ◽  
Composite Surface ◽  
Modis Data ◽  
Seeding Date ◽  
Moderate Resolution Imaging Spectroradiometer

Information on crop seeding date is required in many applications; such as crop management and yield forecasting. This study presents a novel method to estimate crop seeding date at the field level from time-series 250-m Moderate Resolution Imaging Spectroradiometer (MODIS) data and growing degree days (GDD; base 5 °C; °C-days). The start of growing season (SOS) was first derived from time-series EVI2 (two-band Enhanced Vegetation Index) calculated from a MODIS 8-day composite surface reflectance product (MOD09Q1; Collection 6). Based on GDD; calculated from the Daymet gridded estimates of daily weather parameters; a simple model was developed to establish a linkage between the observed seeding date and the SOS. Calibration and validation of the model was conducted on three major crops; spring wheat; canola and oats; in the Province of Manitoba; Canada. The estimated SOS had a strong linear correlation with the observed seeding date; with a deviation of a few days depending on the year. The seeding date of the three crops can be calculated from the SOS by adjusting the number of days needed to accumulate GDD (AGDD) for emergence. The overall root-mean-square-difference (RMSD) of the estimated seeding date was less than 10 days. Validation showed that the accuracy of the estimated seeding date was crop-type independent. The developed method is useful for estimating the historical crop seeding date from remote sensing data in Canada; to support studies of the interactions among seeding date; crop management and crop yield under climate change. It is anticipated that this method can be adapted to other crops in other locations using the same or different satellite data.

scholarly journals Estimating the yield potential of short-rotation willow in Canada using the 3PG model

2017 ◽  
Vol 47 (5) ◽  
pp. 636-647 ◽  
Author(s):  
Guillaume Jégo ◽  
François Thibodeau ◽  
René Morissette ◽  
Marianne Crépeau ◽  
Annie Claessens ◽  
...  
Keyword(s):  
Large Scale ◽  
Model Performance ◽  
Stem Growth ◽  
Yield Potential ◽  
Growing Degree Days ◽  
Degree Days ◽  
Area Index ◽  
Stem Biomass ◽  
Short Rotation ◽  
Simulation Results

The ability to predict short-rotation coppice (SRC) willow productivity for a given region would be very helpful for large-scale deployment of this crop. The objectives of this study were to calibrate and validate the 3PG model for two commonly used clones (SX64 and SX67) and to provide yield potential estimates for 16 sites across Canada. One dataset for each clone, including leaf area index (LAI) and stem biomass, was used for calibrating parameters controlling leaf and stem growth. All other datasets, coming from eight different willow plantations, were used for model validation. Model performance was good in predicting stem biomass for the SX64 (normalized mean error (NME) = –8%, normalized root mean square error (NRMSE) = 22%) and SX67 (NME = –3%, NRMSE = 16%) clones. Predictions were more scattered for LAI, with NRMSE close to 35% and 33% and NME of 1% and 8% for SX64 and SX67, respectively. The simulation results show that the greatest yields were obtained with the three-year rotation for the SX67 clone, whereas a two-year rotation seemed to be more appropriate for the SX64 clone. The simulation results also show that growing degree-days had a significant impact on yield potential, which varied from 10.5 to 16.5 t DM·ha−1 for SX64 and from 7.5 to 11.5 t DM·ha−1 for SX67.

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).

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