scholarly journals Improving predictions of leaf appearance in field grown potato

2007 ◽  
Vol 64 (1) ◽  
pp. 12-18 ◽  
Author(s):  
Nereu Augusto Streck ◽  
Isabel Lago ◽  
Fabiana Luiza Matielo de Paula ◽  
Dilson Antônio Bisognin ◽  
Arno Bernardo Heldwein
Keyword(s):  
Field Experiments ◽  
Solanum Tuberosum L ◽  
Model Performance ◽  
Temperature Response ◽  
Simulation Models ◽  
Main Stem ◽  
Planting Dates ◽  
Linear Temperature ◽  
Non Linear ◽  
Leaf Appearance

The calculation of leaf appearance rate (LAR) and number of accumulated or emerged leaves (NL) on the main stem are part of many crop simulation models. The purpose of this study was to adapt and evaluate a model (WE model) for simulating the main stem LAR and NL in potato (Solanum tuberosum L.). The WE model is a non-linear multiplicative model that takes into account the effect of genotype and environmental factors on LAR. A linear model (Phyllochron model) was also used as a comparison with the WE model. A series of field experiments with 14 planting dates over two years (2003 and 2004) was carried out in Santa Maria, RS, Brazil, using the cultivar Asterix. Coefficients of the WE model and the phyllochron model were estimated with data from four planting dates in 2003, and the models were validated with data from the other ten plantings, which are independent data. The statistics used to quantify model performance was the root mean square error (RMSE). The WE model was a better predictor of NL (RMSE=2.0 leaves) than the phyllochron model (RMSE=3.7 leaves). The WE model has coefficients with biological meaning and a non-linear temperature response function, which renders generality and robustness to this LAR model.

Appearance and growth of individual leaves in the canopies of several potato cultivars

1995 ◽  
Vol 125 (3) ◽  
pp. 379-394 ◽  
Author(s):  
D. M. Firman ◽  
P. J. O'Brien ◽  
E. J. Allen
Keyword(s):  
Air Temperature ◽  
Field Experiments ◽  
Strong Dependence ◽  
N Fertilizer ◽  
Potato Cultivars ◽  
Main Stem ◽  
Planting Dates ◽  
Wide Range ◽  
Leaf Appearance ◽  
Rate Of Leaf Appearance

SUMMARYLeaf appearance of contrasting potato cultivars was examined in field experiments at Cambridge, UK, between 1985 and 1990. Three experiments examined the effects of N fertilizer on the appearance and growth of leaves. Four experiments examined leaf appearance over a wide range of planting dates and in two of these experiments different physiological ages of seed were compared.Linear regression of rate of appearance of main-stem leaves on air temperature indicated a strong dependence of rate of leaf appearance on temperature in the cultivar Maris Piper with a phyllochron of c. 31 K d/leaf but in Estima variation in rate of leaf appearance was only partly explained by differences in air temperature. The phyllochron of main-stem leaves in Estima and Home Guard was shorter for old seed than young seed but there was little effect of seed age in four other cultivars. The phyllochron of main-stem leaves was longer without N fertilizer than with N but the difference in the phyllochron between rates of applied N was small. Leaf appearance on sympodial branches was slower and more variable than on the main-stem. Growth of branches differed between cultivars, particularly with no N fertilizer. In the determinate cultivars Estima and Diana there was restricted growth of branches but in the indeterminate cultivar Cara, significant leaf area was contributed by branches. The duration of leaf appearance and longevity of individual leaves is discussed in relation to N, temperature and cultivar.

scholarly journals Impact of elevated temperature scenarios on potato leaf development

2012 ◽  
Vol 32 (4) ◽  
pp. 689-697 ◽  
Author(s):  
Nereu A. Streck ◽  
Lilian O. Uhlmann ◽  
Alencar J. Zanon ◽  
Dilson A. Bisognin
Keyword(s):  
Elevated Temperature ◽  
Leaf Development ◽  
Potato Crop ◽  
Temperature Response ◽  
Potato Leaf ◽  
Linear Temperature ◽  
Growing Seasons ◽  
Randomized Design ◽  
Leaf Appearance ◽  
The Impact

The objective of this study was to simulate the impact of elevated temperature scenarios on leaf development of potato in Santa Maria, RS, Brazil. Leaf appearance was estimated using a multiplicative model that has a non-linear temperature response function which calculates the daily leaf appearance rate (LAR, leaves day-1) and the accumulated number of leaves (LN) from crop emergence to the appearance of the upper last leaf. Leaf appearance was estimated during 100 years in the following scenarios: current climate, +1 °C, +2 °C, +3 °C, +4 °C e +5 °C. The LAR model was estimated with coefficients of the Asterix cultivar in five emergence dates and in two growing seasons (Fall and Spring). Variable of interest was the duration (days) of the crop emergence to the appearance of the final leaf number (EM-FLN) phase. Statistical analysis was performed assuming a three-factorial experiment, with main effects being climate scenarios, growing seasons, and emergence dates in a completely randomized design using years (one hundred) as replications. The results showed that warmer scenarios lead to an increase, in the fall, and a decrease, in the spring growing season, in the duration of the leaf appearance phase, indicating high vulnerability and complexity of the response of potato crop grown in a Subtropical environment to climate change.

scholarly journals Options for calibrating CERES-maize genotype specific parameters under data-scarce environments

2018 ◽  
Author(s):  
A.A Adnan ◽  
J. Diels ◽  
J.M. Jibrin ◽  
A.Y. Kamara ◽  
P. Craufurd ◽  
...  
Keyword(s):  
Field Experiments ◽  
Time Series Data ◽  
Simulation Models ◽  
Coefficient Of Determination ◽  
Series Data ◽  
Planting Dates ◽  
Maize Varieties ◽  
Using Data ◽  
Set Up ◽  
Nitrogen Contents

AbstractMost crop simulation models require the use of Genotype Specific Parameters (GSPs) which provide the Genotype component of G×E×M interactions. Estimation of GSPs is the most difficult aspect of most modelling exercises because it requires expensive and time-consuming field experiments. GSPs could also be estimated using multi-year and multi locational data from breeder evaluation experiments. This research was set up with the following objectives: i) to determine GSPs of 10 newly released maize varieties for the Nigerian Savannas using data from both calibration experiments and by using existing data from breeder varietal evaluation trials; ii) to compare the accuracy of the GSPs generated using experimental and breeder data; and iii) to evaluate CERES-Maize model to simulate grain and tissue nitrogen contents. For experimental evaluation, 8 different experiments were conducted during the rainy and dry seasons of 2016 across the Nigerian Savanna. Breeder evaluation data was also collected for 2 years and 7 locations. The calibrated GSPs were evaluated using data from a 4 year experiment conducted under varying nitrogen rates (0, 60 and 120kg N ha−1). For the model calibration using experimental data, calculated model efficiency (EF) values ranged between 0.86-0.92 and coefficient of determination (d-index) between 0.92-0.98. Calibration of time-series data produced nRMSE below 7% while all prediction deviations were below 10% of the mean. For breeder experiments, EF (0.52-0.81) and d-index (0.46-0.83) ranges were lower. Prediction deviations were below 17% of the means for all measured variables. Model evaluation using both experimental and breeder trials resulted in good agreement (low RMSE, high EF and d-index values) between observed and simulated grain yields, and tissue and grain nitrogen contents. We conclude that higher calibration accuracy of CERES-Maize model is achieved from detailed experiments. If unavailable, data from breeder experimental trials collected from many locations and planting dates can be used with lower but acceptable accuracy.

scholarly journals Advancing phenology in Europe’s last lowland primeval forest: non-linear temperature response

2009 ◽  
Vol 39 ◽  
pp. 221-226 ◽  
Author(s):  
TH Sparks ◽  
B Jaroszewicz ◽  
M Krawczyk ◽  
P Tryjanowski
Keyword(s):  
Temperature Response ◽  
Linear Temperature ◽  
Primeval Forest ◽  
Non Linear

scholarly journals Water and Temperature Parameters Associated with Winter Wheat Diseases Caused by Soilborne Pathogens

Plant Disease ◽  
2009 ◽  
Vol 93 (1) ◽  
pp. 73-80 ◽  
Author(s):  
Richard W. Smiley
Keyword(s):  
Winter Wheat ◽  
Field Experiments ◽  
Disease Incidence ◽  
Simulation Models ◽  
Crown Rot ◽  
Yield Potential ◽  
Planting Dates ◽  
Wheat Diseases ◽  
Rhizoctonia Root Rot ◽  
Take All

Wheat in eastern Oregon is produced mostly as a 2-year rotation of winter wheat and summer fallow. Maximum agronomic yield potential is expected with early September planting dates but actual yields are generally highest for plantings made in mid-October. Field experiments with sequential planting dates from early September to December were performed over 4 years. Associations among yield, disease incidence, and 19 moisture and temperature parameters were evaluated. Incidence of Cephalosporium stripe, crown rot, eyespot, and take-all decreased as planting was delayed. Crown rot and eyespot were negatively correlated more significantly and more frequently with temperature than moisture parameters, and take-all was more associated with moisture than temperature. Rhizoctonia root rot was unrelated to planting date and climatic parameters. Crown rot was identified most frequently (4 of 5 tests) as an important contributor to yield suppression but yield was most closely associated (R2 > 0.96) with effects from a single disease in only two of five location–year tests. Yield was most related to combinations of diseases in three of five tests, complicating development of disease modules for wheat growth-simulation models.

scholarly journals A temperature response function for modeling leaf growth and development of the African violet (Saintpaulia ionantha Wendl.)

2004 ◽  
Vol 34 (1) ◽  
pp. 55-62 ◽  
Author(s):  
Nereu Augusto Streck
Keyword(s):  
Response Function ◽  
Growth And Development ◽  
Leaf Growth ◽  
Temperature Response ◽  
Simulation Models ◽  
African Violet ◽  
Appearance Rate ◽  
Leaf Appearance Rate ◽  
Leaf Appearance ◽  
Cardinal Temperatures

Response functions used in crop simulation models are usually different for different physiological processes and cultivars, resulting in many unknown coefficients in the response functions. This is the case of African violet (Saintpaulia ionantha Wendl.), where a generalized temperature response for leaf growth and development has not been developed yet. The objective of this study was to develop a generalized nonlinear temperature response function for leaf appearance rate and leaf elongation rate in African violet. The nonlinear function has three coefficients, which are the cardinal temperatures (minimum, optimum, and maximum temperatures). These coefficients were defined as 10, 24, and 33ºC, based on the cardinal temperatures of other tropical species. Data of temperature response of leaf appearance rate and leaf elongation rate in African violet, cultivar Utah, at different light levels, which are from published research, were used as independent data for evaluating the performance of the nonlinear temperature response function. The results showed that a generalized nonlinear response function can be used to describe the temperature response of leaf growth and development in African violet. These results imply that a reduction in the number of input data required in African violet simulation models is possible.

scholarly journals Non-linear temperature response of Bragg gratings in doped and un-doped holey polymer optical fibre

2007 ◽  
Author(s):  
K. Kalli ◽  
D. J. Webb ◽  
K. Carroll ◽  
C. Zhang ◽  
Alex Argyros ◽  
...  
Keyword(s):  
Optical Fibre ◽  
Temperature Response ◽  
Bragg Gratings ◽  
Linear Temperature ◽  
Non Linear

Leaf emergence rates of wheat in a mediterranean environment

1987 ◽  
Vol 38 (2) ◽  
pp. 455 ◽  
Author(s):  
EJM Kirby ◽  
MW Perry
Keyword(s):  
Field Experiments ◽  
Sowing Date ◽  
Rate Of Change ◽  
Main Stem ◽  
Thermal Time ◽  
Wheat Varieties ◽  
Leaf Emergence ◽  
Sowing Dates ◽  
Zero Rate ◽  
Leaf Appearance

Rates of leaf appearance on the main stem were measured for various wheat varieties for five to ten sowing dates in three field experiments in Western Australia.Rate of leaf appearance was constant in relation to thermal time for any given variety and sowing date, and ranged from 0.0064 to 0.0132 leaves (�C day)-1. Most of this variation could be accounted for as a response to sowing date or rate of change of daylength, although the response was complicated by interactions with variety and year.Because successive measurements were made on the same plants, it was possible to estimate directly the effects of temperature on the rate of leaf emergence. In the three years, mean rates of leaf emergence were 0.008, 0.008 and 0.011 leaves day-1 �C-1 with base temperatures (temperatures at zero rate) of 0.08, -1.2 and 0.4�C respectively. Contrary to expectation, rate of leaf emergence decreased as temperatures increased in late sowings due probably to depression of leaf emergence as daytime temperatures exceeded 25�C.For Gamenya, the only variety common to the three years, the rate of leaf emergence (RLE) on the main stem was related to the rate of change of daylength (-DL, min day-1 negative when daylength shortening) by the equationRLE = 0.00949 + 0.000988 (-DL).For crops emerging in late June (-DL approximately zero) in southern Australia, this implies a constant thermal time for leaf appearance of 105�C day leaf-1.

Factors affecting the yield of winter cereals in crop margins

2000 ◽  
Vol 135 (4) ◽  
pp. 335-346 ◽  
Author(s):  
A. WILCOX ◽  
N. H. PERRY ◽  
N. D. BOATMAN ◽  
K. CHANEY
Keyword(s):  
Soil Compaction ◽  
Dry Matter ◽  
Field Experiments ◽  
Polynomial Regression ◽  
Negative Relationship ◽  
Fertilizer Application ◽  
Winter Cereal ◽  
Edge Field ◽  
Winter Cereals ◽  
Non Linear

Yields of arable crops are commonly lower on the crop margins or headlands, but the nature of the relationship between yield and distance from the crop edge has not been clearly defined, nor have the reasons for lower marginal yields. Surveys of 40 winter wheat headlands were carried out in 2 years to determine how yield changed with distance, and what factors might influence this relationship. Two field experiments were also conducted over 3 years in winter cereal headlands, in which the effect of distance was measured under conservation headland and conventional (fully sprayed) management.Yields in the headland surveys varied from 0·8 to 10·2 t/ha. An inverse polynomial regression model was fitted to yield and weed data. Best fits were obtained by using separate parameters for each site. Adjusting yields to take account of weed dry matter improved the non-linear fit between yield and distance from crop edge. Field experiments provided similar results but the non-linear relationship was not as apparent.There was a negative relationship between soil compaction, as measured by a cone penetrometer, and yield in one field experiment, where soil density values were relatively constant. No relationship was found between pattern of nitrogen fertilizer application and yield. Conservation headland management resulted in lower yield at one experimental site, especially in the third year, but not at the other site. Where yields were affected, weed dry matter was higher in conservation headland plots than in fully sprayed plots.Although greater weed competition appears to account for at least part of the observed yield reductions on headlands, the role of other factors, particularly soil compaction, needs further study. Increased weed infestation may be an indirect result of reduced crop competition caused by other adverse conditions.

Assessment of nominal data requirements for robust estimation of fractional snow cover in alpine-forested terrain

2021 ◽  
Author(s):  
Elzbieta Wisniewski ◽  
Wit Wisniewski
Keyword(s):  
Snow Cover ◽  
Input Data ◽  
Model Performance ◽  
Slope Aspect ◽  
Ann Model ◽  
Linear Modeling ◽  
Nominal Data ◽  
Fractional Snow Cover ◽  
Non Linear ◽  
Input Variables

<p>The presented research examines what minimum combination of input variables are required to obtain state-of-the-art fractional snow cover (FSC) estimates for heterogeneous alpine-forested terrains. Currently, one of the most accurate FSC estimators for alpine regions is based on training an Artificial Neural Network (ANN) that can deconvolve the relationships among numerous compounded and possibly non-linear bio-geophysical relations encountered in alpine terrain. Under the assumption that the ANN optimally extracts available information from its input data, we can exploit the ANN as a tool to assess the contributions toward FSC estimation of each of the data sources, and combinations thereof. By assessing the quality of the modeled FSC estimates versus ground equivalent data, suitable combinations of input variables can be identified. High spatial resolution IKONOS images are used to estimate snow cover for ANN training and validation, and also for error assessment of the ANN FSC results. Input variables are initially chosen representing information already incorporated into leading snow cover estimators (ex. two multispectral bands for NDSI, etc.). Additional variables such as topographic slope, aspect, and shadow distribution are evaluated to observe the ANN as it accounts for illumination incidence and directional reflectance of surfaces affecting the viewed radiance in complex terrain. Snow usually covers vegetation and underlying geology partially, therefore the ANN also has to resolve spectral mixtures of unobscured surfaces surrounded by snow. Multispectral imagery if therefore acquired in the fall prior to the first snow of the season and are included in the ANN analyses for assessing the baseline reflectance values of the environment that later become modified by the snow. In this study, nine representative scenarios of input data are selected to analyze the FSC performance. Numerous selections of input data combinations produced good results attesting to the powerful ability of ANNs to extract information and utilize redundancy. The best ANN FSC model performance was achieved when all 15 pre-selected inputs were used. The need for non-linear modeling to estimate FSC was verified by forcing the ANN to behave linearly. The linear ANN model exhibited profoundly decreased FSC performance, indicating that non-linear processing more optimally estimates FSC in alpine-forested environments.</p>

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