Predicting vegetation phenology in response to climate. Licht, virginia nichols, mitch baum, isaiah huber, rafael martinez. Vaccinium corymbosum, base temperature, growing degreeday, bloom period abstract. Aug 30, 20 recorders may also lose interest in a particular species as a season progresses and have renewed interest in unusual late events. A number of thermal functions are used in crop models, but th. Simulating crop phenological responses to water stress.
Department of atmospheric science colorado state university fort collins, colorado 80523 september, 1978. Pdf can growing degree days and photoperiod predict. Crop science abstract comparison of two phenology models. Predicting flower phenology and viability of highbush. The phenological development of the maize crop from emergence through flowering to maturity, usually expressed as a rate i. Identifying corn and soybeans based on phenological profiles. Samples of farm operators are selected from the march cropsstocks survey small grains and the june cropsstocks survey late season crops and tobacco. The success of weed management based on ecological principles and weed biology will depend on a better understanding of the effect of environment on lift history strategies, growth, and competition of weeds. Predicting winter wheat phenology using temperature and.
The ability to monitor agricultural outcomes is as yet limited in the more complex. Genomics meets remote sensing in global change studies. This is a manuscript of an article published as archontoulis, sotirios v. Recorders may also lose interest in a particular species as a season progresses and have renewed interest in unusual late events. Predicting flower phenology and viability of highbush blueberry anna k. The phenology of a crop will determine its adaptation to a region, its ability to mature and set grain within a growing. Uncertainties in predicting rice yield by current crop models. Based on my former graduate students research kirby wuethrich. Prediction of cotton lint yield from phenology of crop indices using artificial neural networks article in computers and electronics in agriculture 152. A framework for predicting softfruit yields and phenology. Katherine pope, university of california cooperative extension. Accurate prediction of phenological development in maize zea mays l.
Validation of a photothermal phenology model for predicting. A nonlinear poikilotherm rate equation was used to describe development as a function of temperature and a temperatureindependent weibull function was used to distribute development times for the population. In dynamic crop simulation models, three categories of variables recognized are, state, rate and driving variables. Wheat crop phenology for advisors definition of phenology modern phenology is the study of the timing of recurring biological events in the animal and plant world, the causes of their timing with regard to biotic and abiotic forces, and the interrelation among phases of the same or different species. The objective of this study was to evaluate the use of a phenological calendar based on flowering phenology of ornamental plants for predicting emergence phenology of giant foxtail. Prediction of cotton lint yield from phenology of crop. Crop phenology models are needed for forecasting crop production.
The phenological development of the maize crop from emergence through flowering to. Considering the importance of the insect and crop, relatively little work has been done on this species. Crop science abstract comparison of two phenology models for predicting flowering and maturity date of soybean view my binders. Pdf realtime monitoring of crop phenology in the midwestern. This species is the most widespread annual grass weed in corn zea mays l. Kirk1 and rufus isaacs department of entomology, 202 cips, 578 wilson road, michigan state university, east lansing, mi 48824 additional index words. Mathematical models are the basic tools to predict the timing of phenological events. Pdf how well do crop models predict phenology, with. Atkinson remote sensing and spatial analysis group, school of geography, shackleton building, university of southampton, highfield campus, southampton so17 1bj, united kingdom. Spring wheat phenology is driven by both temperature and photoperiod.
This paper reports the status of a model for predicting crop phenology phenology mms that can be used independently to simulate crop development or incorporated into existing crop growth models. A number of thermal functions are used in crop models, but their relative precision in predicting maize development has not been quantified. Predicting insect phenology across space and time hodgson. Maize plant phenological responses vary between varieties and quantifying these responses can help in predicting the timing and duration of critical periods for crop growth that affect the quality and. The assessment of crop progress and condition requires early season identification of crop types. Mapping wheat crop phenology and the yield using machine. These satellitederived crop phenological metrics have been successfully applied to assist forecasting crop yield 5,16, and improving land. This technique of deriving ground truth with crop phenological profiles is useful at times when the cropland data layercdl and the farm service agency fsa common land unit clu data are not available. Prediction of crop phenology a component of parallel.
Qtl analysis and qtlbased prediction of flowering phenology. Crop phenology the growth stages the most important factor in the success of a fungicide application is timing. This provides indication that this approach can be useful for predicting crop phenology under global warming scenarios. Many american universities have ongoing phenology studies underway today. Predicting vegetation phenology in response to climate change using bioclimatic indices in iraq afrah daham, dawei han, w. Mutant screening phenology key delphine moreau and nathalie munierjolain. Often the modeller or practitioner is unfamiliar with the crop or phenology in general, or does not have available data to correctly parameterise the phenology model. The agricultural yield survey is conducted in all states except alaska and hawaii. Because certain crop growth stages are critical for final yield butler and huybers 2015, improved results are often seen when remotely sensed data are used to characterize crop phenology bolton and friedl 20. Predicting rice oryza sativa productivity under future climates is important for global food security. These effects may bias phenology estimates derived from distribution data. Evaluating phenological indicators for predicting giant.
It discusses how these issues have been handled by active crop growth simulation model developers and emphasizes areas such as the. The importance of phenology for crop productivity is well understood. Methodological approach for predicting and mapping the. This study reports the results of a study where the impact of various climate change scenarios has been assessed on grain yields of irrigated rice with two popular. Leaf development is strongly interrelated with phenology in a number of ways. Predicting highmagnitude, lowfrequency crop losses using. Combining crop models and remote sensing for yield prediction. Yields and phenology responses to growing conditions will, of course, vary between crop types and varieties grant et al. The other crop forecasting arena is formed by developing countries, where low staple food production can have disastrous effects. Teasing apart spatial and temporal variation in phenology should allow improved predictions of phenology under climate change. Predicting crop phenology by tom hodges 19901226 on. It discusses how these issues have been handled by active crop growth simulation model developers and emphasizes areas such as the role of modeling in agricultural research and the roles of temperature, length of day, and water stress in plant growth. Research was conducted to formulate a temperaturedependent populationlevel model for rhizome johnsongrass flowering. This new model is intended to synthesize and quantify the entire developmental sequence of the shoot apex of many crops, making this information.
The lifecycle of the common lilac is an oftenused guide in phenology studies and garden planning and planting. These problems are exacerbated when users attempt to parameterise a new model or decision support system or an existing model for a new crop. Validation of a photothermal phenology model for predicting dates of flowering and maturity in legume cover crops using field observations. Predicting vegetation phenology in response to climate change. Interannually, extreme weather and an expectation of shifting phenology may change the activity of biological recorders.
The purpose of this study was to measure the phenology of. Can growing degree days and photoperiod predict spring wheat. Models of effects of weeds and pests are being developed and could be available in new generation of crop simulation models. Qtl analysis and qtlbased prediction of flowering phenology in recombinant inbred lines of barley. Predicting buffelgrass phenology a first step to optimizing resource usage for strategic regional, crossjurisdictional buffelgrass control aaryn olsson phd candidate, arid lands resource sciences. The utility of distribution data in predicting phenology. Raja reddy mississippi state university mississippi state, ms 9effects of multiple environmental factor effects on crop growth and phenology across many important crop species. It discusses how these issues have been handled by active crop growth simulation model developers and emphasizes areas such as the role of modeling in agricultural research and.
The total number of leaves of a given shoot and often of the entire plant is related to the duration of the. Phenology of sweetpotato vine borer is not documented. Request pdf on oct 1, 2017, hua jing and others published prediction of crop phenology a component of parallel agriculture management find, read and cite all the research you need on. Ecophysiological crop models in combination with climate model outputs are commonly used in yield prediction, but uncertainties associated with crop models remain largely unquantified. This study reports the results of a study where the impact of various climate change scenarios has been assessed on grain yields of irrigated rice with two popular crop. Pdf accurate prediction of phenological development in maize zea mays l. Increasing temperatures have a significant effect on wheat crop phenology, biomass production, grain yield, and harvest index. Predicting winter wheat phenology using temperature and photoperiod by george r.
Can growing degree days and photoperiod predict spring wheat phenology. Realtime monitoring of crop phenology in the midwestern. Estimates of impact of climate change on crop production could be biased depending upon the uncertainties in climate change scenarios, region of study, crop models used for impact assessment and the level of management. Pdf predicting phenological development in winter wheat. 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. Sep 25, 2017 this provides indication that this approach can be useful for predicting crop phenology under global warming scenarios. Apr 14, 2014 accurate prediction of phenological development in maize zea mays l. Pdf realtime monitoring of crop phenology is critical for assisting farmers. Ort predicting flower phenology and viability of highbush. Simulating crop phenological responses to water stress using. The phenology of a crop will determine its adaptation to.
Predicting white peach scale phenology on kiwifruit in sichuan. Matt jolly, miguel ricoramirez and anke marsh abstract although most phenology models can predict vegetation response to climatic variations, these models often perform poorly in precipitationlimited regions. From a practical perspective, applications of pesticides and fertilizers are carried out at specific phenological stages. Crop phenology is fundamental for understanding crop growth and development, and increasingly influences. Developmental sequences for simulating crop phenology for. Predicting flower phenology and viability of highbush blueberry. Vegetable crop planting and phenology harvest to table. Th us, evaluation of crop phenology models to date has mainly concerne d situations 99 that would tend to make prediction difficult, because of small amounts of data for calibration. Predicting flowering of rhizome johnsongrass sorghum. The eggs of sweetpotato vine borer are elliptical with a flat base, measuring about 0. Predicting crop phenology focuses on an analysis of the issues faced in predicting the phenology of crop plants and weeds. Benci this research has been supported by usdaseaar by wru560220760.