Forum for Science, Industry and Business

Sponsored by:     3M 
Search our Site:

 

Corn Yield Prediction Model Uses Simple Measurements at a Specific Growth Stage

04.07.2013
The ability to predict corn yields would benefit farmers as they plan the sale of their crops and biofuel industries as they plan their operations.

A new study published in the July-August issue of Agronomy Journal describes a robust model that uses easily obtained measurements, such as plant morphology and precipitation, collected specifically at the silking growth stage of the plant. The new model could help both growers and industry maximize their profits and efficiency.


Photo courtesy of Spyridon Mourtzinis.
Measuring the stem diameter of corn crops.

Forecasting crop yield can be extremely useful for farmers. If they have an idea of the amount of yield they can expect, they can contract their corn prior to harvest, often securing a more competitive price than if they were to wait until after harvest. Likewise, industry can benefit from yield predictions by better planning the logistics of their business. But dependable forecasts can be difficult to find.

Several methods of predicting and modeling crop yields have been used in the past with varying success. Statistical models often don’t take into account characteristics of the plants, the weather, or the management practices limiting their usefulness. Some models are based on information from just a single year or location.

“When you develop a model using single location or year data, it will have limited practical applications,” explains Spyridon Mourtzinis, lead author of the study. “You don’t include variability from multiple environments.”

The new study from Mourtzinis and his co-authors from Auburn University found a more robust model for predicting both corn grain and stover yield. The model uses equations calculated with information about nitrogen fertilization rates, precipitation, and plant morphology, such as plant height, stem diameter, height of the first ear, number of forming ears, and plant population.

“Previous attempts were mainly looking at weather factors,” says Francisco Arriaga, co-author of the study and now an assistant professor at the University of Wisconsin-Madison. “This approach has other factors included in the model, and that is an important strength.”

The timing of the measurements is also an important aspect of the model. Mourtzinis took weekly measurements from over 100 plots throughout the growing season to find the best window during which to collect data to be used in the equations. The time-consuming work paid off.

“We looked at all the vegetative states to see which one was best, and it turned out to be the R1 growth stage,” explains Arriaga. “Other models tried to take measurements earlier, but that may be why they had poor results. Things change as the season goes by, and the stage we found was the critical one.”

The R1 or silking growth stage, when silks are first visible outside the husks, is about two to two and half months before harvest. This model, then, would provide predictions early enough to affect crop prices and to allow industries to plan their operations. While even earlier predictions might be possible, they would depend on better forecasting of weather, which can greatly affect yields. Weather changes significantly throughout the growing season, and current forecasts are not dependable.

Another reason that the new model is robust is because data was collected at two different sites in Alabama over three years. The equations used in the current model, then, translated over six sets of data suggesting that it could be used in a variety of environments. Whether that is true is a goal of future experiments.

“It would be interesting to test the equations across a lot more environments now that we know which growth stage to target,” says Arriaga.

Future studies will also test the model with other corn hybrids and management practices. As more data is collected from a variety of environments and growing conditions, the authors are hopeful that the model will continue to be an accurate predictor of corn yield.

“We need to be open-minded,” says Mourtzinis. “The equations might change a bit when we get more data from more environments, but I think we can build on the current model.”

View the abstract at http://dx.doi.org/doi:10.2134/agronj2012.0393

To obtain a copy of the complete article, please contact Madeline Fisher at 608-268-3973, mfisher@sciencesocieties.org or Caroline Schneider at 608-268-3976, cschneider@sciencesocieties.org.

Spyridon Mourtzinis
szm0020@tigermail.auburn.edu
The full article is available for no charge for 30 days following the date of this summary. View the abstract at http://dx.doi.org/doi:10.2134/agronj2012.0393.

A peer-reviewed international journal of agriculture and natural resource sciences, Agronomy Journal is published six times a year by the American Society of Agronomy, with articles relating to original research in soil science, crop science, agroclimatology and agronomic modeling, production agriculture, and software. For more information visit: www.agronomy.org/publications/aj

The American Society of Agronomy (ASA) www.agronomy.org, is a scientific society helping its 8,000+ members advance the disciplines and practices of agronomy by supporting professional growth and science policy initiatives, and by providing quality, research-based publications and a variety of member services.

Madeline Fisher | Newswise
Further information:
http://www.agronomy.org

Further reports about: Agronomy Stage Acting biofuel industries crop yield growing season

More articles from Agricultural and Forestry Science:

nachricht Fighting a destructive crop disease with mathematics
21.06.2017 | University of Cambridge

nachricht Unusual soybean coloration sheds a light on gene silencing
20.06.2017 | University of Illinois College of Agricultural, Consumer and Environmental Sciences

All articles from Agricultural and Forestry Science >>>

The most recent press releases about innovation >>>

Die letzten 5 Focus-News des innovations-reports im Überblick:

Im Focus: Can we see monkeys from space? Emerging technologies to map biodiversity

An international team of scientists has proposed a new multi-disciplinary approach in which an array of new technologies will allow us to map biodiversity and the risks that wildlife is facing at the scale of whole landscapes. The findings are published in Nature Ecology and Evolution. This international research is led by the Kunming Institute of Zoology from China, University of East Anglia, University of Leicester and the Leibniz Institute for Zoo and Wildlife Research.

Using a combination of satellite and ground data, the team proposes that it is now possible to map biodiversity with an accuracy that has not been previously...

Im Focus: Climate satellite: Tracking methane with robust laser technology

Heatwaves in the Arctic, longer periods of vegetation in Europe, severe floods in West Africa – starting in 2021, scientists want to explore the emissions of the greenhouse gas methane with the German-French satellite MERLIN. This is made possible by a new robust laser system of the Fraunhofer Institute for Laser Technology ILT in Aachen, which achieves unprecedented measurement accuracy.

Methane is primarily the result of the decomposition of organic matter. The gas has a 25 times greater warming potential than carbon dioxide, but is not as...

Im Focus: How protons move through a fuel cell

Hydrogen is regarded as the energy source of the future: It is produced with solar power and can be used to generate heat and electricity in fuel cells. Empa researchers have now succeeded in decoding the movement of hydrogen ions in crystals – a key step towards more efficient energy conversion in the hydrogen industry of tomorrow.

As charge carriers, electrons and ions play the leading role in electrochemical energy storage devices and converters such as batteries and fuel cells. Proton...

Im Focus: A unique data centre for cosmological simulations

Scientists from the Excellence Cluster Universe at the Ludwig-Maximilians-Universität Munich have establised "Cosmowebportal", a unique data centre for cosmological simulations located at the Leibniz Supercomputing Centre (LRZ) of the Bavarian Academy of Sciences. The complete results of a series of large hydrodynamical cosmological simulations are available, with data volumes typically exceeding several hundred terabytes. Scientists worldwide can interactively explore these complex simulations via a web interface and directly access the results.

With current telescopes, scientists can observe our Universe’s galaxies and galaxy clusters and their distribution along an invisible cosmic web. From the...

Im Focus: Scientists develop molecular thermometer for contactless measurement using infrared light

Temperature measurements possible even on the smallest scale / Molecular ruby for use in material sciences, biology, and medicine

Chemists at Johannes Gutenberg University Mainz (JGU) in cooperation with researchers of the German Federal Institute for Materials Research and Testing (BAM)...

All Focus news of the innovation-report >>>

Anzeige

Anzeige

Event News

Plants are networkers

19.06.2017 | Event News

Digital Survival Training for Executives

13.06.2017 | Event News

Global Learning Council Summit 2017

13.06.2017 | Event News

 
Latest News

Quantum thermometer or optical refrigerator?

23.06.2017 | Physics and Astronomy

A 100-year-old physics problem has been solved at EPFL

23.06.2017 | Physics and Astronomy

Equipping form with function

23.06.2017 | Information Technology

VideoLinks
B2B-VideoLinks
More VideoLinks >>>