Corn yield prediction model uses simple measurements at a specific growth stage

Public release date: 2-Jul-2013
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Contact: Spyridon Mourtzinis
szm0020@tigermail.auburn.edu
American Society of Agronomy

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.

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.

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: http://www.agronomy.org/publications/aj

The American Society of Agronomy (ASA) http://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.

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AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert! system.

Public release date: 2-Jul-2013
[ | E-mail | Share ]

Contact: Spyridon Mourtzinis
szm0020@tigermail.auburn.edu
American Society of Agronomy

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.

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.

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: http://www.agronomy.org/publications/aj

The American Society of Agronomy (ASA) http://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.

---

[ | E-mail | Share ]

?

AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert! system.

Source: http://www.eurekalert.org/pub_releases/2013-07/asoa-cyp070213.php

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Breakthrough in El Nino forecasting

July 1, 2013 ? In order to extend forecasting from six months to one year or even more, scientists have now proposed a novel approach based on advanced connectivity analysis applied to the climate system. The scheme builds on high-quality data of air temperatures and clearly outperforms existing methods. The study will be published this week in the Proceedings of the National Academy of Sciences.

"Enhancing the preparedness of people in the affected regions by providing more early-warning time is key to avoiding some of the worst effects of El Ni?o," says Hans Joachim Schellnhuber, director of the Potsdam Institute for Climate Impact Research and co-author of the study by Josef Ludescher et al (Justus-Liebig Universit?t Giessen). The new approach employs network analysis which is a cutting-edge methodology at the crossroads of physics and mathematics. Data from more than 200 measurement points in the Pacific, available from the 1950s on, were crucial for studying the interactions between distant sites that cooperate in bringing about the warming.

Extending the forecasting time but also enhancing the reliability

According to Schellnhuber a new algorithm was developed and tested which does not only extend the forecasting time but also enhances the reliability. In fact, the novel method correctly predicted the absence of an El Ni?o-event in the last year. This forecast was made in 2011 already, whereas conventional approaches kept on predicting a significant warming far into 2012.

El Ni?o is part of a more general oscillation of the Pacific ocean-atmosphere system called ENSO, which also embraces anomalous cold episodes dubbed La Ni?a which can inflict severe damages as well. The present study focuses on the warming events only. However, an El Ni?o-year is followed by a La Ni?a-year, as a rough rule.

Climate change: a factor for ENSO changes?

"It is still unclear to which extent global warming caused by humankind's emissions of greenhouse gases will influence the ENSO pattern," says Schellnhuber. "Yet the latter is often counted among the so-called tipping elements in the Earth system, meaning that at some level of climate change it might experience a relatively abrupt transformation." Certain data from the Earth's past suggest that higher mean global temperatures could increase the amplitude of the oscillation, so correct forecasting would become even more important.

Source: http://feeds.sciencedaily.com/~r/sciencedaily/most_popular/~3/Ec_koDwQJvU/130701151822.htm

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The Wanted and Backstreet Boys perform at G-A-Y in London - Pics

Backstreet's back, alright?

As you may have noticed, there's nothing we love more here at Sugarscape than a good boyband. There's just something about those silky smooth tones, perfectly-quiffed bouffants and bulging biceps that do funny things to us. So you can imagine our delight when, last night, The Wanted boys performed at London's Heaven nightclub...WITH THE BACKSTREET BOYS *yelp*.

Yup, Backstreet's officially back - and our fave fivesome off of the 90s took to the stage alongside five of our current faves in a massive boyband sandwich. And it was beautiful.

To celebrate London Pride, the lads stormed the stage as loads of excitable peeps went a bit cray cray over what was happening in front of them. Like...it's not every day you get to see Max George making out with Jay McGuiness, is it?

Or Max being actually mauled, for that matter.

And OBVIOUSLY carnage ensued when Nathan Sykes got his rocket out and was well unapologetic about it...

OOF. Now let's just have a little perv over them all again, shall we? Warning: includes quite frankly RIDICULOUS Siva cheekbone action.

Amazing.

What d'ya reckon? Do you want it that way? We'd have it any way, to be honest. We're not fussy. Comments please. GO.

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This Decaying, Futuristic Lego City Is Neotokyo Reborn

Most Lego cities are well-planned models of urban order. But at Brickworld this year, a team of six builders led by Carter Baldwin created this intricate model of urban disorder. Their unique version of Neotokyo borrows from a handful of great cyberpunk novels and movies, from Akira to Neuromancer.

Baldwin worked with Nate Brill, Kyle Vreze, Forest King, Ignacio Bernaldez, Sam Wormuth, Alex Valentino, and Chris Edwards on the project, which includes rare or obscure pieces from Lego's Scala collection. It shows us a snippet of a futuristic city, where decaying high-rises leave fetid canals in constant shadows on the ground level. The level of detail is incredible, and including tangled wires, hanging laundry, and cyberpunk minifigs. The Japanese signage, meanwhile, is made from electroluminescent wire, and includes billboards for "foreign girls."

It's cool to see a physical model of a fictional city, especially one that's been described by so many different authors over the past three decades. There's a bit of the real-life Kowloon Walled City here, too?the now-razed urban experiment that, arguably supplied the precedent for many fictional cyber-cities, which William Gibson famously described as "vast, multilayered engines of choice." Check out more images on Flickr, or see the model yourself at BrickFair on August 3. [Fred Scharmen via Archinect]

Images by Nathaniel Brill.

Source: http://lego.gizmodo.com/this-decaying-futuristic-lego-city-is-neotokyo-reborn-634853762

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Diamond catalyst shows promise in breaching age-old barrier

June 30, 2013 ? In the world, there are a lot of small molecules people would like to get rid of, or at least convert to something useful, according to University of Wisconsin-Madison chemist Robert J. Hamers.

Think carbon dioxide, the greenhouse gas most responsible for far-reaching effects on global climate. Nitrogen is another ubiquitous small-molecule gas that can be transformed into the valuable agricultural fertilizer ammonia. Plants perform the chemical reduction of atmospheric nitrogen to ammonia as a matter of course, but for humans to do that in an industrial setting, a necessity for modern agriculture, requires subjecting nitrogen to massive amounts of energy under high pressure.

"The current process for reducing nitrogen to ammonia is done under extreme conditions," explains Hamers, a UW-Madison professor of chemistry. "There is an enormous barrier you have to overcome to get your final product."

Breaching that barrier more efficiently and reducing the huge amounts of energy used to convert nitrogen to ammonia -- by some estimates 2 percent of the world's electrical output -- has been a grail for the agricultural chemical industry. Now, that goal may be on the horizon, thanks to a technique devised by Hamers and his colleagues and published June 30, 2013 in the journal Nature Methods.

Like many chemical reactions, reducing nitrogen to ammonia is a product of catalysis, where the catalytic agent used in the traditional energy-intensive reduction process is iron. The iron, combined with high temperature and high pressure, accelerates the reaction rate for converting nitrogen to ammonia by lowering the activation barrier that otherwise keeps nitrogen, one of the most ubiquitous gases on the planet, intact.

"The nitrogen molecule is one of the happiest molecules around," notes Hamers. "It is incredibly stable. It doesn't do anything."

One of the big obstacles, according to Hamers, is that nitrogen binds poorly to catalytic materials like iron.

Hamers and his team, including Di Zhu, Linghong Zhang and Rose E. Ruther, all of UW-Madison, turned to synthetic industrial diamond -- a cheap, gritty, versatile material -- as a potential new catalyst for the reduction process. Diamond, the Wisconsin team found, can facilitate the reduction of nitrogen to ammonia under ambient temperatures and pressures.

Like all chemical reactions, the reduction of nitrogen to ammonia involves moving electrons from one molecule to another. Using hydrogen-coated diamond illuminated by deep ultraviolet light, the Wisconsin team was able to induce a ready stream of electrons into water, which served as a reactant liquid that reduced nitrogen to ammonia under temperature and pressure conditions far more efficient than those required by traditional industrial methods.

"From a chemist's standpoint, nothing is more efficient than electrons in water," says Hamers, whose work is funded by the National Science Foundation. With the diamond catalyst, "the electrons are unconfined. They flow like lemmings to the sea."

While the method was demonstrated in the context of reducing nitrogen to a valuable agricultural product, the new diamond-centric approach is exciting, Hamers argues, because it can potentially fit a wide range of processes that require catalysis. "This is truly a different way of thinking about inducing reactions that may have more efficiency and applicability. We're doing this with diamond grit. It is infinitely reusable."

The technique devised by Hamers and his colleagues, he notes, still has kinks that need to be worked out to make it a viable alternative to traditional methods. The use of deep ultraviolet light, for example, is a limiting factor. Inducing reactions with visible light is a goal that would enhance the promise of the new technique for applications such as antipollution technology.

Source: http://feeds.sciencedaily.com/~r/sciencedaily/most_popular/~3/zbzxBs1Pjuc/130630144449.htm

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Peace Light Memorial to be rededicated by Sons of Union Veterans? Camp 43

By Tom Mitchell

Published: Saturday, June 29, 2013, 2:16?a.m.
Updated 7 hours ago

KITTANNING ? Members of the Sons of Union Veterans of the Civil War, John T. Crawford Camp 43 will be doing their part to honor the memory of veterans who fought in the various battles of Gettysburg 150 years ago.

Richard Essenwein, state department commander and Camp 43 graves registration officer, said Camp 43 members will join with other Sons units at Gettysburg this weekend for the SUVCW's annual department encampment, a business session, and a re-dedication of the Peace Light Memorial. Various Sons groups will stay at the Eisenhower Inn and Conference Center.

?On Saturday we will be on the battlefield to rededicate the Peace Light Memorial,? Essenwein said. ?It was first dedicated by President Franklin Roosevelt 75 years ago as a memorial to all the brothers and sisters we lost in the Battle of Gettysburg, to a nation reunited, and to eternal peace. It will be a very somber and moving ceremony.?

Essenwein said that during such annual gatherings, the Sons make donations to charitable organizations in the towns in which they meet ? this year, in Gettysburg. One charity is selected by the state department's patriotic instructor and a second is selected by the ladies' auxiliary.

?Originally the charitable donations were presented at a campfire ceremony,? he said. ?But the parks department has regulations prohibiting fires on the battlefield, so the presentations will be made at the Conference Center. Camp 43 is proud and honored to play a role in this historic and solemn event.?

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