scholarly journals Development of Prediction Growth and Yield Models by Growing Degree Days in Hot Pepper

2018 ◽  
Vol 27 (4) ◽  
pp. 424-430 ◽  
Author(s):  
Sung Kyeom Kim ◽  
성겸 김 ◽  
Jin Hyoung Lee ◽  
Hee Ju Lee ◽  
Sang Gyu Lee ◽  
...  
2021 ◽  
Vol 64 (1) ◽  
pp. 1-12
Author(s):  
R. Louis Baumhardt ◽  
Lucas A. Haag ◽  
Prasanna H. Gowda ◽  
Robert C. Schwartz ◽  
Gary W. Marek ◽  
...  

HighlightsLater planting and greater site elevation or latitude decreased seasonal growing degree days and cotton yield in Kansas.Higher irrigation capacity (rate) usually increased lint yield, which was probably due to increased early boll load.Strategies for splitting land allocations between high irrigation rates and dryland did not increase production.Cotton may reduce irrigation withdrawals from the Ogallala aquifer, but the Kansas growing season limits production.Abstract. Precipitation in the western Great Plains averages about 450 mm, varying little with latitude and providing 40% to 80% of potential crop evapotranspiration (ETc). Supplemental irrigation is required to fully meet crop water demand, but the Ogallala or High Plains aquifer is essentially non-recharging south of Nebraska. Pumping water from this aquifer draws down water tables, leading to reduced water availability and deficit irrigation to produce an alternate crop such as cotton (Gossypium hirsutum L.) with a lower peak water demand than corn (Zea mays L.). Our objective was to compare simulated cotton yield response to emergence date, irrigation capacity, and application period at three western Kansas locations (Colby, Tribune, and Garden City) with varying seasonal energy or cumulative growing degree days (CGDD) and compare split center pivot deficit irrigation strategies with a fixed water supply (i.e., where portions of the center pivot land area are managed with different irrigation strategies). We used actual 1961-2000 location weather records with the GOSSYM simulation model to estimate yields of cotton planted into soil at 50% plant-available water for three emergence dates (DOY 145, 152, and 159) and all combinations of irrigation period (0, 4, 6, 8, and 10 weeks beginning at first square) and capacity (2.5, 3.75, and 5.0 mm d-1). Simulated lint yield and its ratio to ETc, or water use efficiency (WUE), consistently decreased with delayed planting (emergence) as location elevation or latitude increased due to effects on growing season CGDD. Depending on location, simulated cotton lint consistently increased (p = 0.05) for scenarios with increasing irrigation capacity, which promoted greater early season boll load, but not for durations exceeding 4 to 6 weeks, probably because later irrigation and fruiting did not complete maturation during the short growing season. Cotton WUE generally increased, with greater yields resulting from earlier emergence and early high-capacity irrigation. We calculated lower WUE where irrigation promoted vigorous growth with added fruiting forms that delayed maturation and reduced the fraction of open bolls. The irrigation strategy of focusing water at higher capacities on a portion of the center pivot in combination with the dryland balance did not increase net yields significantly at any location because the available seasonal energy limited potential crop growth and yield response to irrigation. However, the overall net lint yield was numerically larger for focused irrigation strategies at the southwest Kansas location (Garden City). Based on lint yields simulated under uniform or split center pivot deficit irrigation, we conclude that cotton is poorly suited as an alternative crop for central western and northwestern Kansas because of limited growing season CGDD. Keywords: Cotton, Crop simulation, Deficit irrigation, Evapotranspiration, Irrigation capacity, Split center pivot irrigation, Water use efficiency, Yield limiting factors.


2020 ◽  
Vol 8 (4) ◽  
pp. 1546-1554
Author(s):  
Ravi Babu M ◽  
KLN Rao ◽  
Ashoka Rani Y ◽  
Martinluther M ◽  
Prasad PRK

2017 ◽  
Vol 4 (03) ◽  
Author(s):  
M. K. Singh ◽  
VINOD KUMAR ◽  
SHAMBHU PRASAD

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’.


2019 ◽  
Vol 33 (6) ◽  
pp. 800-807 ◽  
Author(s):  
Graham W. Charles ◽  
Brian M. Sindel ◽  
Annette L. Cowie ◽  
Oliver G. G. Knox

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.


2008 ◽  
Vol 54 (1) ◽  
pp. 31-35
Author(s):  
Thomas G. Matney ◽  
Emily B. Schultz

Abstract Many growth and yield models have used statistical probability distributions to estimate the diameter distribution of a stand at any age. Equations for approximating individual tree diameter growth and survival probabilities from dbh can be derived from these models. A general procedure for determining the functions is discussed and illustrated using a loblolly pine spacing study. The results from the spacing study show that it is possible to define tree diameter growth and survival probability functions from diameter distributions with an accuracy sufficient to obtain a link between the individual tree and diameter growth and yield models.


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 ◽  
...  

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).


1976 ◽  
Vol 56 (4) ◽  
pp. 901-905 ◽  
Author(s):  
D. G. DORRELL

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.


2007 ◽  
Vol 3 (3) ◽  
pp. 499-512 ◽  
Author(s):  
S. Brewer ◽  
J. Guiot ◽  
F. Torre

Abstract. We present here a comparison between the outputs of 25 General Circulation Models run for the mid-Holocene period (6 ka BP) with a set of palaeoclimate reconstructions based on over 400 fossil pollen sequences distributed across the European continent. Three climate parameters were available (moisture availability, temperature of the coldest month and growing degree days), which were grouped together using cluster analysis to provide regions of homogenous climate change. Each model was then investigated to see if it reproduced 1) similar patterns of change and 2) the correct location of these regions. A fuzzy logic distance was used to compare the output of the model with the data, which allowed uncertainties from both the model and data to be taken into account. The models were compared by the magnitude and direction of climate change within the region as well as the spatial pattern of these changes. The majority of the models are grouped together, suggesting that they are becoming more consistent. A test against a set of zero anomalies (no climate change) shows that, although the models are unable to reproduce the exact patterns of change, they all produce the correct signs of change observed for the mid-Holocene.


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