scholarly journals Spatial Distribution of Calibrated WOFOST Parameters and Their Influence on the Performances of a Regional Yield orecasting System

2013 ◽  
Vol 2 (4) ◽  
pp. 12 ◽  
Author(s):  
Bakary Djaby ◽  
Allard De Wit ◽  
Louis Kouadio ◽  
Moussa El Jarroudi ◽  
Bernard Tychon
Keyword(s):  
Winter Wheat ◽  
Air Temperature ◽  
Western Europe ◽  
Test Site ◽  
Qualitative Assessment ◽  
Growth Monitoring ◽  
Area Index ◽  
Crop Parameters ◽  
Two Parameters ◽  
Crop Variety

We investigate in this study (i) a redefinition of crop variety zonations at a spatial scale of 10x10 km, and (ii) the influence of recalibrated crop parameters on regional yield forecasting of winter wheat and grain maize in western Europe. The baseline zonation and initial crop parameter set was derived from the operational European crop growth monitoring system (CGMS) which involves the agrometeorological model WOFOST. Air temperature data from 325 weather stations over the 1992-2007 period were used to define new zonations in a 300 x 300 km test site. Two parameters which influenced mostly the phenological development stages (i.e. TSUM1 and TSUM2, the effective air temperature sums from emergence to anthesis, and from anthesis to maturity, respectively) were chosen and calibrated. The CGMS was finally run based on these new recalibrated parameters and simulated crop status indicators were compared with official statistics over the 2000-2007 period. Our results showed that the days of anthesis and maturity were simulated with coefficients of determination (R2) ranging from 0.22 to 0.87 for both crops over the study site. A qualitative assessment of maximum leaf area index and harvest index also revealed a more consistent spatial pattern than the initial zonation in the simulation results. Finally, recalibrated TSUM1 and TSUM2 led to improved relationships between official yield and simulated crop indicators (significant R2 in 17 out of 28 and in 14 out of 59 NUTS3 regions with respect to the best predictor for grain maize and winter wheat, respectively).

scholarly journals Growth and clorophyll content dynamics of winter wheat (Triticum aestivum L.) in different cropyear

2013 ◽  
pp. 101-105
Author(s):  
Enikő Vári
Keyword(s):  
Winter Wheat ◽  
Grain Filling ◽  
Triticum Aestivum L ◽  
Area Index ◽  
Rotation System ◽  
Crop Rotation System ◽  
Two Parameters ◽  
The University ◽  
The Relationship

The experiments were carried out at the Látókép experimental station of the University of Debrecen on chernozem soil in a long term winter wheat experiment in the season of 2011 and 2012 in triculture (pea-wheat-maize) and biculture (wheat-maize) at three fertilisation levels (control, N50+P35K40, N150+P105K120). Two different cropyears were compared (2011 and 2012). The research focused on the effects of forecrop and fertilisation on the Leaf Area Index, SPAD values and the amount of yield in two different cropyears. We wanted to find out how the examined parameters were affected by the cropyear and what the relationship was between these two parameters and the changes of the amount of yield. Examining the effects of growing doses of fertilizers applied, results showed that yields increased significantly in both rotations until the N150+PK level in 2011 and 2012. By comparing the two years, results show that in 2011 there was a greater difference in yields between the rotations (7742 kg ha-1 at N150+PK in the biculture and 9830 kg ha-1 at N150+PK in the triculture). Though wheat yields following peas were greater in 2012, results equalized later on at N150+PK levels (8109–8203 kg ha-1). Due to the favorable agrotechnical factors, the leaf and the effects of the treatments grown to a great extent in 2011, while in 2012 the differences between treatments were moderate. Until the N150+PK level, nitrogen fertilisation had a notable effect on the maximum amount of SPAD values (59.1 in the case of the biculture and 54.0 in the triculture). The highest SPAD values were measured at the end of May (during the time of flowering and grain filling) in the biculture. In the triculture, showed high SPAD values from the beginning. The same tendency could be observed in the 2012 cropyear, although increasing doses of fertilizers resulted in higher SPAD values until N150+PK level only from the second measurement. Maximum SPAD values were reached at the end of May in both crop rotation system

scholarly journals How valuable are citizen science data for a space-borne crop growth monitoring? – The reliability of self-appraisals

2020 ◽  
Author(s):  
Sina C. Truckenbrodt ◽  
Friederike Klan ◽  
Erik Borg ◽  
Klaus-Dieter Missling ◽  
Christiane C. Schmullius
Keyword(s):  
Management Practices ◽  
Test Site ◽  
Uncertainty Assessment ◽  
Earth Observation ◽  
Growth Monitoring ◽  
State Variables ◽  
Science Data ◽  
Area Index ◽  
In Situ Data

<p>Space-borne Earth Observation (EO) data depicting vegetation covered land surfaces contain insufficient information for an unambiguous interpretation of the spectral signal in terms of variables that characterize the vegetation state (e.g., leaf area index, leaf chlorophyll content and proportion of senescent material). For the retrieval of vegetation properties from EO data, an optimal estimate of the state variables needs to be found. The uncertainty of such an estimate can be reduced by combining EO data and in situ data. Information provided by citizens represents a valuable and mostly inexpensive source for in situ data. Since the quality of such data can be diverse, the consideration of uncertainties is of great importance.</p><p>In this contribution, we present a concept for the elicitation of local knowledge from citizens with respect to the application of management practices (e.g., sowing and harvesting date, irrigation) and the instantaneous state of crops. The concept includes the acquisition of in situ data as well as an uncertainty assessment (precision and/or accuracy). The latter involves a profiling in which inherent uncertainties are quantified for individual citizens. This concept was tested for agricultural fields of the Durable Environmental Multidisciplinary Monitoring Information Network (DEMMIN) test site in Northeast Germany. Within the frame of several field seminars, students were requested to assess management practices and the instantaneous state of crops. Furthermore, they assessed their own ability to create valid data. They filled in pseudonymized questionnaires from which we created corresponding datasets. At the same day, field data were collected with appropriate equipment and can be used as reference against which student estimates can be compared. The level of compliance between estimated and measured data was determined on an individual basis.</p><p>The results of this analysis will be presented. Conclusions will be drawn regarding the ability of the students to evaluate their own skills. In addition, we will demonstrate an approach for a digital ascertainment of in situ data. In the future, this approach will be used to collect in situ data for the setup of refined prior information within the frame of the Earth Observation Land Data Assimilation System (EO-LDAS).</p>

scholarly journals Joint Retrieval of Winter Wheat Leaf Area Index and Canopy Chlorophyll Density Using Hyperspectral Vegetation Indices

2021 ◽  
Vol 13 (16) ◽  
pp. 3175
Author(s):  
Naichen Xing ◽  
Wenjiang Huang ◽  
Huichun Ye ◽  
Yu Ren ◽  
Qiaoyun Xie
Keyword(s):  
Winter Wheat ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Vegetation Index ◽  
Vegetation Indices ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Growth Stages ◽  
Growth Monitoring ◽  
Area Index

Leaf area index (LAI) and canopy chlorophyll density (CCD) are key biophysical and biochemical parameters utilized in winter wheat growth monitoring. In this study, we would like to exploit the advantages of three canonical types of spectral vegetation indices: indices sensitive to LAI, indices sensitive to chlorophyll content, and indices suitable for both parameters. In addition, two methods for joint retrieval were proposed. The first method is to develop integration-based indices incorporating LAI-sensitive and CCD-sensitive indices. The second method is to create a transformed triangular vegetation index (TTVI2) based on the spectral and physiological characteristics of the parameters. PROSAIL, as a typical radiative transfer model embedded with physical laws, was used to build estimation models between the indices and the relevant parameters. Validation was conducted against a field-measured hyperspectral dataset for four distinct growth stages and pooled data. The results indicate that: (1) the performance of the integrated indices from the first method are various because of the component indices; (2) TTVI2 is an excellent predictor for joint retrieval, with the highest R2 values of 0.76 and 0.59, the RMSE of 0.93 m2/m2 and 104.66 μg/cm2, and the RRMSE (Relative RMSE) of 12.76% and 16.96% for LAI and CCD, respectively.

scholarly journals Optimization of Topdressing for Winter Wheat by Accurate Growth Monitoring and Improved Production Estimation

2021 ◽  
Vol 13 (12) ◽  
pp. 2349
Author(s):  
Jingchun Ji ◽  
Jianli Liu ◽  
Jingjing Chen ◽  
Yujie Niu ◽  
Kefan Xuan ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Crop Production ◽  
Optimization Method ◽  
Growth Potential ◽  
N Use Efficiency ◽  
Growth Monitoring ◽  
Aerial Vehicle ◽  
Use Efficiency ◽  
Improved Model ◽  
N Use

Topdressing accounts for approximately 40% of the total nitrogen (N) application of winter wheat on the Huang-Huai-Hai Plain in China. However, N use efficiency of topdressing is low due to the inadaptable topdressing method used by local farmers. To improve the N use efficiency of winter wheat, an optimization method for topdressing (THP) is proposed that uses unmanned aerial vehicle (UAV)-based remote sensing to accurately acquire the growth status and an improved model for growth potential estimation and optimization of N fertilizer amount for topdressing (NFT). The method was validated and compared with three other methods by a field experiment: the conventional local farmer’s method (TLF), a nitrogen fertilization optimization algorithm (NFOA) proposed by Raun and Lukina (TRL) and a simplification introduced by Li and Zhang (TLZ). It shows that when insufficient basal fertilizer was provided, the proposed method provided as much NFT as the TLF method, i.e., 25.05% or 11.88% more than the TRL and TLZ methods and increased the yields by 4.62% or 2.27%, respectively; and when sufficient basal fertilizer was provided, the THP method followed the TRL and TLZ methods to reduce NFT but maintained as much yield as the TLF method with a decrease of NFT by 4.20%. The results prove that THP could enhance crop production under insufficient N preceding conditions by prescribing more fertilizer and increase nitrogen use efficiency (NUE) by lowering the fertilizer amount when enough basal fertilizer is provided.

Adaptation of winter cereal species to shade and competition in a winter/spring cereal forage mixture

1996 ◽  
Vol 76 (2) ◽  
pp. 251-257 ◽  
Author(s):  
V. S. Baron ◽  
E. A. de St Remy ◽  
D. F. Salmon ◽  
A. C. Dick
Keyword(s):  
Winter Wheat ◽  
Dark Respiration ◽  
Dominant Factor ◽  
Carbon Exchange ◽  
Area Index ◽  
Winter Cereal ◽  
Winter Triticale ◽  
Winter Cereals ◽  
Cereal Species ◽  
Shoot Weight

Spring planted mixtures of spring and winter cereals maximize dry matter yield and provide fall pasture by regrowth of the winter cereal. However, delay of initial harvest may reduce the winter cereal component and therefore subsequent regrowth yield. Research was conducted at Lacombe, Alberta to investigate the effect of time of initial cut (stage), winter cereal species (species) and cropping system (monocrop and mixture) on winter cereal shoot weight, leaf carbon exchange efficiency and shoot morphology. These parameters may be related to adaptation of winter cereals to growth and survival in the mixture. Winter cereal plants were grown in pails embedded in monocrop plots of fall rye (Secale cereale L.), winter triticale (X Triticosecale Wittmack) and winter wheat (Triticum aestivum L.) and in binary mixtures with Leduc barley (Hordeum vulgare L.). The plants were removed when the barley reached the boot (B), heads emerged (H), H + 2, H + 4 and H + 6 wk stages. Shoot weight was generally smaller in the mixture than in the monocrop and wheat was reduced more than fall rye and triticale in the mixture compared to the monocrop. Dark respiration rate (r = −0.54) and carbon exchange (r = 0.36) under low light intensity were correlated (P < 0.05) to shoot size in the mixture. Fall rye and winter triticale had lower dark respiration rates than winter wheat. Leaf area index (LAI) was closely correlated (r = 0.83 and 0.84) with shoot weight in both the mixture and monocrop. While species failed to exhibit clear cut differences for LAI, fall rye and winter triticale were reduced less than winter wheat in the mixture relative to the monocrop. Stage was the dominant factor affecting winter cereal growth in both cropping systems, but fall rye and triticale exhibited superior morphological features, and their carbon exchange responses to light were more efficient than wheat, which should allow them to be sustained longer under the shaded conditions of a mixture. Key words: Delayed harvest, shade, spring and winter cereal mixtures, adaptation, carbon exchange, respiration

scholarly journals Modification and Validation of Priestley–Taylor Model for Estimating Cotton Evapotranspiration under Plastic Mulch Condition

2016 ◽  
Vol 17 (4) ◽  
pp. 1281-1293 ◽  
Author(s):  
Zhipin Ai ◽  
Yonghui Yang
Keyword(s):  
Air Temperature ◽  
Soil Heat Flux ◽  
Taylor Model ◽  
Taylor Coefficient ◽  
Plastic Mulch ◽  
Area Index ◽  
Modified Model ◽  
Growing Seasons ◽  
Balance Analysis ◽  
Evapotranspiration Estimation

Abstract Compared with more comprehensive physical algorithms such as the Penman–Monteith model, the Priestley–Taylor model is widely used in estimating evapotranspiration for its robust ability to capture evapotranspiration and simplicity of use. The key point in successfully using the Priestley–Taylor model is to find a proper Priestley–Taylor coefficient, which is variable under different environmental conditions. Based on evapotranspiration partition and plant physiological limitation, this study developed a new model for estimating the Priestley–Taylor coefficient incorporating the effects of three easily obtainable parameters such as leaf area index (LAI), air temperature, and mulch fraction. Meanwhile, the effects of plastic film on the estimation of net radiation and soil heat flux were fully considered. The reliability of the modified Priestley–Taylor model was testified using observed cotton evapotranspiration from eddy covariance in two growing seasons, with high coefficients of determination of 0.86 and 0.81 in 2013 and 2014, respectively. Then, the modified model was further validated by estimating cotton evapotranspiration under three fractions of mulch cover: 0%, 60%, and 100%. The estimated values agreed well with the measured values via water balance analysis. It can be found that seasonal variation of the modified Priestley–Taylor coefficient showed a more reasonable pattern compared with the original coefficient of 1.26. Sensitivity analysis showed that the modified Priestley–Taylor coefficient was more sensitive to LAI than to air temperature. Overall, the modified model has much higher accuracy and could be used for evapotranspiration estimation under plastic mulch condition.

Differences in warming impacts on wheat productivity among varieties released in different eras in North China

2015 ◽  
Vol 153 (8) ◽  
pp. 1353-1364 ◽  
Author(s):  
C. Y. ZHENG ◽  
J. CHEN ◽  
Z. W. SONG ◽  
A. X. DENG ◽  
L. N. JIANG ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Grain Yield ◽  
Biomass Production ◽  
Air Temperature ◽  
North China ◽  
Growth Period ◽  
Wheat Breeding ◽  
Wheat Growth ◽  
Positive Effects ◽  
Significant Difference

SUMMARYTen leading varieties of winter wheat released during 1950–2009 in North China were tested in a free-air temperature increase (FATI) facility. The FATI facility mimicked the local air temperature pattern well, with an increase of 1·1 °C in the daily mean temperature. For all the tested varieties, warming caused a significant reduction in the total length of wheat growth period by 5 days and especially in the pre-anthesis period, where it was reduced by 9 days. However, warming increased wheat biomass production and grain yield by 8·4 and 11·4%, respectively, on an average of all the tested varieties. There was no significant difference in the warming-led reduction in the entire growth period among the tested varieties. Interestingly, the warming-led increments in biomass production and grain yield increased along with the variety release year. Significantly higher warming-led increases in post-anthesis biomass production and 1000-grain weight were found in the new varieties compared to the old ones. Meanwhile, a significant improvement in plant productivity was noted due to wheat breeding during the past six decades, while no significant difference in the length of entire growth period was found among the varieties released in different eras. The results demonstrate that historical wheat breeding might have enhanced winter wheat productivity and adaptability through exploiting the positive effects rather than mitigating the negative impacts of warming on wheat growth in North China.

scholarly journals Representing winter wheat in the Community Land Model (version 4.5)

2017 ◽  
Vol 10 (5) ◽  
pp. 1873-1888 ◽  
Author(s):  
Yaqiong Lu ◽  
Ian N. Williams ◽  
Justin E. Bagley ◽  
Margaret S. Torn ◽  
Lara M. Kueppers
Keyword(s):  
Heat Flux ◽  
Winter Wheat ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Latent Heat Flux ◽  
Carbon Allocation ◽  
Net Ecosystem Exchange ◽  
Area Index ◽  
Community Land Model ◽  
The Us

Abstract. Winter wheat is a staple crop for global food security, and is the dominant vegetation cover for a significant fraction of Earth's croplands. As such, it plays an important role in carbon cycling and land–atmosphere interactions in these key regions. Accurate simulation of winter wheat growth is not only crucial for future yield prediction under a changing climate, but also for accurately predicting the energy and water cycles for winter wheat dominated regions. We modified the winter wheat model in the Community Land Model (CLM) to better simulate winter wheat leaf area index, latent heat flux, net ecosystem exchange of CO2, and grain yield. These included schemes to represent vernalization as well as frost tolerance and damage. We calibrated three key parameters (minimum planting temperature, maximum crop growth days, and initial value of leaf carbon allocation coefficient) and modified the grain carbon allocation algorithm for simulations at the US Southern Great Plains ARM site (US-ARM), and validated the model performance at eight additional sites across North America. We found that the new winter wheat model improved the prediction of monthly variation in leaf area index, reduced latent heat flux, and net ecosystem exchange root mean square error (RMSE) by 41 and 35 % during the spring growing season. The model accurately simulated the interannual variation in yield at the US-ARM site, but underestimated yield at sites and in regions (northwestern and southeastern US) with historically greater yields by 35 %.

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