Winter Wheat Phenology Research Articles

Phenological trends of winter wheat in response to varietal and temperature changes in the North China Plain

Understanding the confounding impacts of climatic and varietal changes on crop phenology is of importance to help make appropriate adaptation measures and target future directions for crop breeding. This paper investigated the changes in winter wheat phenology and analysed the impact of climatic, varietal and sowing date changes on crop phenology during the last three decades by combining field data with modeling. The APSIM crop model was used to quantify the changes in wheat phenology in terms of vernalization and photoperiod sensitivity as well as the changes in thermal time of pre- and post-flowering stage among wheat varieties at six sites in the North China Plain (NCP). The results showed that APSIM model could capture the phenological changes of winter wheat caused by interannual climatic change. There was a large spatial difference in the response pattern of wheat phenology to climatic and varietal changes across NCP. At most sites the increase in temperature shortened the growth duration of winter wheat mainly by shortening the growth period from sowing to jointing. The delayed sowing of winter wheat further shortened the growth period from sowing to jointing at two northern sites (Tianjin and Huimin). Continuous adoption of new wheat varieties shortened the growth period from sowing to jointing at Huimin, Xinxiang and Zhumadian, from jointing to flowering at Tianjin, but helped increase the length of growth period from jointing to flowering at Huimin, Tangyin and Xinxiang and post-flowering growth period at all the sites except for Tangyin. The findings of the study suggest that past cultivar changes in wheat in the NCP have been varied geographically.

Impact of climate change in 1981—2009 on winter wheat phenology in the North China Plain

A warming climate trend in the last three decades has been well documented around the global and this trend have had a considerable impact on agricultural productivity.Phenology is a plant growth progress that is largely driven by meteorological conditions.Phenological changes are vital indicators for changes in climate and other environmental conditions.In this study,the trends in winter wheat phenology for 1981—2009 were investigated based on phenological dates from 16 agro-experimental stations in the North China Plain(NCP).The study showed that the dates of sowing,emergence and dormancy delayed.On the other hand,the dates of green-up,anthesis and maturity advanced in most of the stations.The advance or delay of winter wheat phenology resulted in corresponding changes in the durations of the different growth stages.In most of the investigated stations,the durations from emergence to dormancy,dormancy to green-up,green-up to anthesis and in the entire period from emergence to maturity of winter wheat shortened during 1981—2009.However,the duration of anthesis to maturity slightly prolonged on the average by 0.9 days per decade.Observed changes in winter wheat phenology were functions of both climate and management practices,especially that of cultivated cultivar shift.The effect of crop cultivar shift was isolated from that of climate change on winter wheat phonological changes by comparing field observed phonological events in four stations with those simulated by the CERES(Crop Environment Resource Synthesis)-Wheat model.The results suggested that climate warming played a dominant role in phenological changes in winter wheat in the NCP.However,the effect of cultivar shift on winter wheat phenological changes was not entirely negligible.Moreover,correlation analysis on the durations of green-up to anthesis and anthesis to maturity against mean temperatures for the growth periods showed that temperature increase by 1 ℃ shortened the durations of green-up to anthesis and anthesis to maturity by 3.8 and 1.2 days,respectively.Understanding the response of crop development and phenology to climate change was critical for not only building in-depth insights into the impacts of climate change on crop development and productivity,but also on food security for the millions of people in the region and beyond.

Simulating Crop Phenological Responses to Water Stress Using the PhenologyMMS Software Program

Abstract. Crop phenology is fundamental for understanding crop growth and development, and increasingly influences many agricultural management practices. Water deficits are one environmental factor that can influence crop phenology through shortening or lengthening the developmental phase, yet the phenological responses to water deficits have rarely been quantified. The objective of this article is to describe the science and general evaluation of a decision support technology software tool, PhenologyMMS (Modular Modeling Software) V1.2. PhenologyMMS was developed to simulate the phenological response of different crops to varying levels of soil water. The program is intended to be simple to use, requires minimal information for calibration, and can be easily incorporated into other crop simulation models. New and revised developmental sequences of the shoot apex correlated with phenological events and the response to soil water availability are provided for proso millet (Panicum milaceum L.), hay/foxtail millet [Setaria italica (L.) P. Beauv.], sunflower (Helianthus annuus L.), and sorghum (Sorghum bicolor L.). Model evaluation consisted of testing algorithms using “generic” default phenology parameters for a crop (i.e., no calibration for specific cultivars was used) for a variety of field experiments to predict developmental events such as seedling emergence, floral initiation, flowering, and physiological maturity. Additionally, an application of the program predicting mean dates of winter wheat (Triticum aestivum L.) phenology across the Central Great Plains based on historical weather records is presented. Results demonstrated that PhenologyMMS has general applicability for predicting crop phenology and offers a simple and easy to use approach to predict and understand how phenology responds to varying water deficits. PhenologyMMS software may be downloaded from http://www.ars.usda.gov/services (select “Software”) or http://arsagsoftware.ars.usda.gov.

Spatial Interrelationships between Wheat Phenology, Thermal Time, and Terrain Attributes

Spatial variation of winter wheat (Triticum aestivum L.) phenology across complex terrain has received little attention despite its importance for assessing overall crop status and making key precision management decisions. Temperature is the environmental factor explaining the greatest variation in phenology, and temperature varies across a landscape. Our primary hypothesis was that variability in thermal time (TT) by landscape position could explain the phenological variation, with a secondary hypothesis that spatial patterns of TT and phenology were related to terrain attributes. Four years of phenology and soil and air temperature data were collected from a 100‐ha field in northeast Colorado. Five developmental stages were monitored at 10 landscape sites each year. Terrain attributes were computed using 5‐m‐grid land surface elevation data. Spatial differences in reaching developmental stages across sites varied from 2 to 12 d within a year. Up to 96% of the phenological variation among years was explained when using a general TT model pooling all data. Refining the TT model, however, by using either air or soil TT at specific sites partially supported the primary hypothesis only for the relatively wetter 2004–2005 and 2006–2007 years (regression relationships explained up to 72% of the variation). Similarly, terrain attributes occasionally explained spatial patterns of phenology in the two wetter years, and attributes with the highest explanatory power varied among years and developmental stages. Further research is needed to better understand the controlling environmental factors and predict spatial patterns of wheat phenology for precision management using terrain attributes.

Observed changes in winter wheat phenology in the North China Plain for 1981–2009

Climate change in the last three decades could have major impacts on crop phenological development and subsequently on crop productivity. In this study, trends in winter wheat phenology are investigated in 36 agro-meteorological stations in the North China Plain (NCP) for the period 1981-2009. The study shows that the dates of sowing (BBCH 00), emergence (BBCH 10) and dormancy (start of dormancy) are delayed on the average by 1.5, 1.7 and 1.5 days/decade, respectively. On the contrary, the dates of greenup (end of dormancy), anthesis (BBCH 61) and maturity (BBCH 89) occur early on the average by 1.1, 2.7 and 1.4 days/decade, respectively. In most of the investigated stations, GP2 (dormancy to greenup), GP3 (greenup to anthesis) and GP0 (entire period from emergence to maturity) of winter wheat shortened during the period 1981-2009. Due, however, to early anthesis, grain-filling stage occurs at lower temperatures than before. This, along with shifts in cultivars, slightly prolongs GP4 (anthesis to maturity). Comparison of field-observed CERES (Crop Environment Resource Synthesis)-wheat model-simulated dates of anthesis and maturity suggests that climate warming is the main driver of the changes in winter wheat phenology in the NCP. The findings of this study further suggest that climate change impact studies should be strengthened to adequately account for the complex responses and adaptations of field crops to this global phenomenon.

Air temperature trend and the impact on winter wheat phenology in Romania

Air temperature variability and trends in Romania were analysed using monthly, seasonal, and annual datasets. Temperature data of winter wheat season were also analysed. The Mann-Kendall test, Sen’s slope estimate, the sequential version of the Mann-Kendall test, the Pettitt test and spatial and temporal hierarchical cluster analyses were used. First, the datasets were checked for changing points. The 106-year period was divided into two long periods of 100 years each to verify the importance of a very short interval in changing of general trends; after that it was divided into three shorter periods of 35–36 years each. The main conclusions are as follows: the 6 years making up the difference between the two long periods are very important in the context of the recent global warming; the three shorter periods analysis indicate some fluctuations rather than continuous warming. The latest short period is the most relevant for global warming. Spatial hierarchical cluster analysis indicated the existence of two distinctive groups. One of them, which includes stations in the south-east part of the country, seems to be influenced by the Black Sea surface temperature. Temporal hierarchical cluster analysis reveals that annual data series have the closest relation with the summer data series. Further, the impact of temperature changes on winter wheat phenology was determined using a phenology simulation performed with the model from the Decision Support System for Agrotechnology Transfer v. 4.0.2.0 platform. Earlier occurrences of anthesis and maturity were noticed for several regions in the country.

Coupling land surface and crop growth models for predicting evapotranspiration and carbon exchange in wheat-maize rotation croplands

Abstract. The North China Plain is one of the key crop-producing regions in China. However, water resources in the area are limited. Accurate modeling of water consumption and crop production in response to the changing environment is important. To describe the two-way interactions among climate, irrigation, and crop growth better, the modified crop phenology and physiology scheme from the SiBcrop model was coupled with the second version of the Simple Biosphere model (SiB2) to simulate crop phenology, crop production, and evapotranspiration of winter wheat and summer maize, which are two of the main crops in the region. In the coupled model, the leaf area index (LAI) produced by the crop phenology and physiology scheme was used in estimating sub-hourly energy and carbon fluxes. Observations obtained from two typical eddy covariance sites located in this region were used to validate the model. The coupled model was able to accurately simulate carbon and energy fluxes, soil water content, biomass carbon, and crop yield, especially for latent heat flux and carbon flux. The LAI was also well simulated by the model. Therefore, the coupled model is capable of assessing the responses of water resources and crop production to the changes of future climate and irrigation schedules of this region.

Growth and phenology of winter wheat and oats in a dual-purpose management system

Dual-purpose cereal cropping is gaining acceptance among growers in mixed farming systems. Success in particular seasons depends on management decisions regarding choice of cereal species, sowing date, timing of grazing, and stocking rate. A more detailed understanding of how these factors influence the growth, phenology, and grain yield of the major cereal forages is needed to model these systems. Wheat (cvv. Whistler and Mackellar) and oats (cv. Blackbutt) were grown under dual-purpose management near Canberra, ACT, over 3 years (2004–06) in 2 crop sequences: wheat-oats-wheat and oats-wheat-wheat. In each year, crops were grazed by sheep at low (20/ha), medium (30–35 /ha), and high (40–52 /ha) grazing intensities. In the pre-grazing periods, measurements of phyllochron interval (PI), tiller development rate (TDR), and stem apex height were made. Post-grazing growth rate was determined from shoot biomass cuts taken at the end of grazing and at grain harvest. Soil moisture changes during each year were monitored to examine the pattern of soil water use under varying grazing intensities. In unusually dry periods in March–April 2004 and 2005, oats established significantly denser plant populations than wheat. In 2004, this initial advantage of oats resulted in greater feed on offer at the start of grazing than wheat, whereas in 2005, higher TDR, lower PI of wheat, and the longer duration of tillering resulted in similar amounts of feed on offer at the start of grazing. Elongation of the stem apex was more rapid in wheat than oats, indicating that wheat would be more at risk of damage during grazing. The post-grazing growth rate of wheat and oats was significantly lower than the ungrazed control in the dry spring years of 2004 and 2006, but significantly higher in the wetter spring year of 2005. While reduction in growth rate at high stocking rate was most likely caused by extreme reduction in leaf area, the causes of increases in growth rate following more lenient grazing require further investigation. In 2004 and 2005, there was no significant difference between crops or between stocking rate treatments in soil water depletion during the post-grazing period. However, in 2006, when soil moisture was not affected by rainfall in the post-grazing period, significantly more water was depleted from soil in the 0.60–1.70 m depth under low and medium stocking rate treatments than under the ungrazed control treatment. A gross margin analysis showed greater economic returns for the dual-purpose compared with a grain-only option in each year, most notably in the very dry season in 2006, when conventional practice would have been to sacrifice the grain crop to grazing or hay production.

Impact of recent climatic change on the yield of winter wheat at low and high altitudes in semi-arid northwestern China

This study analyses data on winter wheat ( Triticum aestivum L.) development and climate from Tongwei County (35°13′N, 105°14′E), Gansu, in the semiarid northwest of China during 1981–2005. Two study sites were chosen: one at Tongwei Meteorological Station, situated at 1798 m above sea level at the foot of LuLu Mountain, and the second on the summit of LuLu Mountain at an altitude of 2351 m. The objective was to investigate whether there were significant trends in the change of climate variables, and whether these changes have significantly affected the development and production of winter wheat at different altitudes above sea level. The results showed that, with changes in temperature and precipitation, there was a significant change in the phenology of winter wheat that crop yields increased at both sites from 1981 to 2005, and that the increase in yields was higher at the high-altitude site. During 1981–1998 the yields at the high-altitude site were lower than at the low altitude site, whereas after 1998 the yields at the high-altitude site were higher than at the low altitude site. In the face of climate change, winter wheat production in this region during 1981–2005 was higher at the higher altitude site than at the lower altitude site. It is expected that, by 2030, the interaction of warming temperature and changed rainfall will have led to a further increase of 3.1% in wheat yields at a low altitude and of 4.0% at a high altitude in the semiarid northwest of China.

Evaluating SHOOTGRO 4.0 as a potential winter wheat management tool in the Czech Republic

Improving current cultural practices often involves more precise timing of the management activity based on crop development. Using crop simulation models to predict crop development and phenology has several problems. First, most existing models do not simulate sufficient developmental and phenological detail required to optimize selected management practices. Second, crop models normally emphasize the cultivars and conditions for the region in which they were developed, and may not generate satisfactory results when applied in new regions. Lastly, when users apply these models to new regions they often lack the specific data and knowledge of the model to adequately determine the crop parameters. Our objective was to assess whether the simulation model SHOOTGRO 4.0, which had the necessary level of developmental and phenological detail required for use as a management decision aid, could be easily and adequately parameterized to simulate winter wheat phenology and grain yield in the Czech Republic. We found that only a few parameters from the generic winter wheat cultivar used for the Central Great Plains in the USA needed to be changed, and the information needed to determine these few parameters were readily obtainable. The result was that the dates of anthesis and physiological maturity and final grain yield were predicted well at sites within the three major crop production regions of the Czech Republic. Sensitivity analysis also showed that the most sensitive management practices and initial conditions in SHOOTGRO are relatively easy to determine (e.g. sowing date, N fertilizer rate and timing, daily temperature), while it is not overly sensitive to those variables more difficult to determine (e.g. initial soil water in the profile). Based on this study, farmers and scientists needing wheat development information to increase the efficacy of their management practices can use SHOOTGRO 4.0 as a tool.

Is Soil Temperature Better than Air Temperature for Predicting Winter Wheat Phenology?

AbstractIn predicting wheat (Triticum aestivum L.) phenology, logic suggests that basing thermal unit accumulation on near‐surface soil temperature should give a better representation of shoot apex thermal unit accumulation than air temperature until internode elongation raises the apex above the soil surface. A study was undertaken to determine if predictions of winter wheat phenology are improved when based on measured near‐surface soil temperature rather than air temperature. Air temperature 1.5 m above the soil surface and soil temperature at crown depth (the position of the shoot apex before stem elongation) were collected for 23 site‐years across the U.S. Central Great Plains representing a range of cultivars, soils, management practices, and climates. Seven site‐years from different sites were randomly selected to calculate the mean thermal units from both seeding and 1 January to specific growth stages based on both air and soil temperature. These means were used to predict occurrence of growth stages for the remaining 16 site‐years. In no instance did soil temperature significantly improve prediction of winter wheat phenology. From these results, we conclude that the additional effort and expense of using soil temperature in predicting winter wheat phenology are not justified.

Wheat Stem Sawfly (Hymenoptera: Cephidae) Adaptation to Winter Wheat

The wheat stem sawfly, Cephus cinctus Norton, originally occurred in North American large-stemmed wild grasses. The pest adapted to spring-planted wheat, Trtiticum aestivum L., within 10 yr after cultivation began. Fall-planted winter wheat originally avoided attack, but was consistently heavily damaged by 1985. We reviewed the factors affecting the recent adaptation of C. cinctus to winter wheat. No changes could be detected in the seasonal phenology of winter wheat. Decreased acreage of spring wheat from 1921 to 1945 : reduced host availability. C. cinctus wasps are now emerging 20 d earlier than previously, and oviposition activity currently closely coincides with susceptible growth stages of winter wheat Larval cannibalism of eggs and younger larvae also provides natural selection for early season activity. Annual emergence of wasps from a population in wild grasses consistently begins later than in wheat.

Calibration and validation of EPIC for crop rotations in southern France

Management of complex crop rotations in southern France requires accurate assessment of the effects of irrigation, nitrogen fertilization, and the previous crop on crop growth and yield. The Erosion-Productivity Impact Calculator (EPIC) Cropping Systems model simulates the effects of weather, soil characteristics, tillage, fertilization, irrigation and other management practices on crops grown in complex rotations. The present study was conducted to evaluate EPIC's ability to simulate growth and yield of corn ( Zea mays L.), grain sorghum ( Sorghum bicolor (L.) Moench), sunflower ( Helianthus annuus L.), soybean ( Glycine max (L.) Merr.) and wheat ( Triticum aestivum L.) when grown in rotations at three levels of management inputs, including three levels each of fertilizer, irrigation and tillage, over a 5-year period. After calibration, the root mean square error of simulated model grain yields ranged from 0.4 Mg ha −1 for sunflower to 1.6 Mg ha −1 for corn. Only in the case of winter wheat were mean simulated yields significantly different from mean measured yields. Simulations were more accurate for summer crops than for winter wheat, primarily because EPIC overestimated the effects of cool spring temperatures on wheat development in 1986. We conclude that EPIC can simulate yields of summer crops grown in complex rotations in southern France with accuracy acceptable for many applications. The model could be improved by more accurate simulation of disease effects, like those suffered by wheat in 1988, and by more accurate simulation of the effects of cool temperatures on winter wheat phenology.

Estimation and evaluation of winter wheat phenology in the central Great Plains

Crop modeling and management requires accurate prediction of crop phenology. Phenology data for winter wheat ( Triticum aestivum L.) were collected from seven sites in the central Great Plains for several years to relate phenological stages to environmental and cultural factors, and to provide needed phenology data for the central Great Plains. Number of calendar days ( ND), growing degree-days ( GDD), and photothermal units ( PTU) were calculated for emergence (E), tiller initiation (TI), dormancy end (DE), jointing (J), heading (H), kernel in milk (KM), kernel in hard dough (KD), and maturity (M) using the Feekes growth scale for the main stem. Nine base temperatures (−2, 0, 1, 2, 3, 4, 5, 7, and 9°C) were used when accumulating GDD and PTU. Mean daily temperatures of 20, 25, and 30°C were used for upper thresholds. Accumulation of GDD, PTU and ND were calculated from planting date (S), E, and 1 January to the growth stage and from one growth stage to the next. Model sensitivity to soil water, cultivar, seeding rates, row spacing, rotation, and fertilizer were examined. The lower the base temperature for a model, the lower the root mean square error ( RMSE) when beginning accumulation from S, E or 1 January, with −2°C the best except for DE, KD, and M where higher base temperatures tended to have lower RMSE. As M was approached, the 25°C upper threshold tended to do better than 20°C. Little difference was found between 25 and 30°C upper thresholds. The best model for predicting a stage varied, with ND the best for E through J. From H through M, PTU models had the lowest RMSE. Normally, GDD and PTU models beginning accumulation from 1 January outperformed models beginning accumulation from S or E. The GDD or PTU related to availability of soil water showed a parabolic relationship (concave downward) beginning at J and becoming more platykurtic as M was approached. Significant sensitivity to cultivar and row spacing/rotation was found, with occasional sensitivity by various model types found to fertilizer and planting date.

Comparison of Crop Phenology Models1

AbstractThree winter wheat (Triticum aestivum L.) phenology models (CERES‐wheat, TAMW, Robertson) were compared for accuracy in estimating jointing, heading, dough, and ripe stage dates for winter wheat at the Crop Reporting District (CRD) level in Kansas. The models' estimates of stage dates were compared to weekly USDA Statistical Reporting Service stage observations for even years during 1952 to 1980. Odd years were reserved for calibration of models. The CERES‐wheat model estimates were consistently more accurate for all stages.