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Integrating two types of crop models to predict the effect of climate change on crop yields

Published January 3, 2018
corn

URBANA, Ill. – Scientists now have a new tool to predict the future effects of climate change on crop yields. Researchers from University of Illinois are attempting to bridge two types of computational crop models to become more reliable predictors of crop production in the U.S. Corn Belt.

“One class of crop models is agronomy-based and the other is embedded in climate models or earth system models. They are developed for different purposes and applied at different scales,” says Kaiyu Guan, an environmental scientist at the University of Illinois and the principal investigator on the research. “Because each has its own strengths and weaknesses, our simple idea is to combine the strengths of both types of models to make a new crop model with improved prediction performance.”

Guan and his research team implemented and evaluated a new maize growth model, represented as the CLM-APSIM model, by combining superior features in both Community Land Model (CLM) and Agricultural Production Systems sIMulator (APSIM).

“The original maize model in CLM only has three phenological stages, or life cycles. Some important developmental stages such as flowering are missing, making it impossible to apply some critical stresses, such as water stress or high temperature at these specific developmental stages,” says Bin Peng, a postdoctoral researcher in Guan’s lab and also the lead author. “Our solution is incorporating the life cycle development scheme of APSIM, which has 12 stages, into the CLM model. Through this integration, stresses induced by high temperature, soil water and nitrogen deficits, can be taken into account in the new model.”

Peng says they chose CLM as the hosting framework to implement the new model because it is more process-based and can be coupled with climate models. “This is important as the new tool can be used to investigate the two-way feedback between an agroecosystem and a climate system in our future studies.”

In addition to replacing the original maize phenology model in CLM with that from the APSIM model, the researchers have made several other innovative improvements in the new model. A new carbon allocation scheme and a grain number simulation scheme were added, as well as a refinement to the original canopy structure scheme.

“The most alluring improvement is that our new model is closer to getting the right yield with the right mechanism,” says Guan. “The original CLM model underestimates above-ground biomass but overestimates the harvest index of maize, leading to apparent right-yield simulation with the wrong mechanism. Our new model corrected this deficiency in the original CLM model.”

Peng adds that the phenology scheme of APSIM is quite generic. “We can easily extend our new model to simulate the growth processes of other staple crops, such as soybeans and wheat. This is definitely in our plan and we are already working on it.

“All the work was conducted on Blue Waters, a powerful petascale supercomputer at the National Center for Supercomputing Applications (NCSA) on the University of Illinois campus,” says Peng. “We are currently working on parameter sensitivity analysis and Bayesian calibration of this new model and also on a high resolution regional simulation over the U.S. Corn Belt, all of which would not be possible without the precious computational resources provided by Blue Waters.”

The study, “Improving maize growth processes in the community land model: Implementation and evaluation,” is published in Agricultural and Forest Meteorology. The work was initiated and designed by Kaiyu Guan and Bin Peng from the University of Illinois and Min Chen from the Joint Global Change Research Institute of Pacific Northwest National Laboratory at Maryland. It is co-authored by a multi-institute team of David M. Lawrence and Yaqiong Lu, both from the National Center for Atmospheric Research; Yadu Pokhrel from Michigan State University; and Andrew Suyker and Timothy Arkebauer from the University of Nebraska-Lincoln.

Funding was provided by the NASA New Investigator Award (NNX16AI56G), USDA National Institute of Food and Agriculture (NIFA) Foundational Program award (2017-67013-26253), and Blue Waters Professorship (National Center for Supercomputing Applications at the University of Illinois) awarded to Kaiyu Guan, and USDA NIFA award (2015-67003-23489) to David M. Lawrence.

This research is part of the Blue Waters sustained-petascale computing project, which is supported by the National Science Foundation (awards OCI-0725070 and ACI-1238993) and the state of Illinois.

In addition to being an assistant professor in ecohydrology and geoinformatics in the Department of Natural Resources and Environmental Sciences in the College of Agricultural, Consumer and Environmental Sciences at the U of I, Guan has a joint appointment as a Blue Waters professor affiliated with NCSA.  Peng has a postdoctoral appointment with NCSA and also affiliated with NRES.

 

News Sources:


Kaiyu Guan
Bin Peng

Project helps Marching Illini recycle on game day

Published December 22, 2017
recycling sign

URBANA, Ill. – During every University of Illinois home football game the Marching Illini band entertains the crowd from the stands and performs at halftime. On game day, the band’s 400 musicians plus supporting staff also eat a boxed lunch together. That’s over 400 sandwiches, cookies, and bottles of water. U of I senior Matthew Moy, who has played tenor sax in the Marching Illini for three years, noticed something else about the lunches -- the 400 sandwich wrappers, boxes, and empty water bottles going into the trash. He saw a substantial opportunity to recycle.

Moy and four other students—Matt Aronoff, Herman Chacon, Gabrielle Levato, and Cora Wessman—are all members of Ming Kuo’s NRES 472 on environmental psychology. Although the class is in the Department of Natural Resources and Environmental Sciences in the College of Agricultural, Consumer and Environmental Sciences, it is a popular class with students from other disciplines. Aronoff and Chacon are NRES students. Moy and Wessman are in Earth, Society and Environmental Sustainability, and Levato is in Environmental Engineering. But they all share a desire for more “green” living. They decided to make game day recycling behavior of the marching band their final class project. Director of Athletic Bands Barry Houser was supportive of the project that would monitor and encourage the MI band members to recycle the paper and plastic leftovers from the game day boxed lunches.

The team of students set parameters of the behavioral study for the five home football game days of the 2017 fall season.

Week one: they distributed a survey asking students about their recycling habits.

Week two: seven plastic bins were provided for plastic water bottles and cardboard boxes near the trash receptacle. One large sign was placed above the bins that read “Recycle Here.” In week two 125 water bottles were recycled and 136 boxes.

Week three: the recycling containers were in place again, this time with smaller signs over each bin to encourage the band members to recycle boxes and water bottles separately. They also received oral instructions from Director Houser. This strategy garnered the most participation, with 137 water bottles recycled and 176 boxes (34.25% and 44% respectively).

“During week four, we hit a real-world road bump,” says Moy. “In order to save time, we set up the recycle bins the night before and they were taken, so we didn’t collect any data from that week.”

Week five: the project was back on track with the recycle bins and prompts in place but participation was down. Only 107 water bottles and 152 boxes were recycled. The group attributes the lower numbers to the unfortunate interruption of the study in week four.

The student team reported that changing the behavior of a large group like the Marching Illini can be difficult to do quickly. Convenient locations of recycle bins and plenty of them so that the wait to crush boxes and place them in the bins could be kept short were important lessons learned.

Moy says if he would do it again, he’d start by giving the band a presentation about the goals of the project. It would also be good to share the statistics with the band to encourage them to push for improvement the following week and feel like they are making a difference.

Kuo says this project is particularly interesting because it involves changing behavior within a specific group that already has a strong sense of community. “I could see the Marching Illini being proud as a group of their commitment to recycle on game day.” She says students in this particular environmental class say that through these class projects, they’ve not only learned about sustainability in organizations, but left a legacy in their time here, “making the U of I just a little bit better than when they first arrived on campus.”

Ming Kuo is the director of the Landscape and Human Health Laboratory in the Department of Natural Resources and Environmental Sciences in the College of Agricultural, Consumer and Environmental Sciences at U of I. Her research focuses on green space and health. She also teaches NRES 472 on environmental psychology.

 

 

What makes a community feel more tolerant or supportive for lesbian, gay, and bisexual parents?

Published December 21, 2017
Ramona Oswald, professor, Human Development and Family Studies

URBANA, Ill. - Community factors and social connection may determine whether sexual minority parents view their community as tolerant versus supportive, according to a new study from the University of Illinois.

The study, published in the journal Family Relations, is led by Ramona Oswald, professor in the Department of Human Development and Family Studies at U of I. Findings show that lesbian, gay, and bisexual parents in nonmetropolitan communities feel more positive about where they live when that place is more legally, politically, and religiously supportive of LGB people; when there are more LGB-friendly employers; and when there are other LGB-headed households.

For the study, data were collected from 55 LGB parents about their residential communities. The communities included university/college towns, as well as agriculture, industrial, government oriented, and small towns or villages. Parents reported on residential community climate (tolerant versus supportive) and community involvement.

Community characteristics alone, however, did not determine perceived climate, as LGB parents living in the same communities rated them differently. The differences seemed to hinge on whether parents experienced a fit between themselves and their communities.

Those parents perceiving a supportive climate felt comfortable being open about their identity, and were able to access support without barriers. Any stigma that they experienced was an exception to their overall positive experience. Those reporting tolerant communities described numerous barriers to social involvement and connection such as stigma, harassment, or apathy of institutions towards bullying and discrimination. For these parents, feeling support was the exception, and they found support in specific locations such as religiously affirming congregations.

Overall, community structural factors were necessary for a community to be considered tolerant, but were not sufficient for a community to be perceived as supportive.

“These findings show that legal protections, employer support, and religious affirmation are important for sexual minority families,” Oswald says. “These features should not, however, be taken for granted. Even within communities that look supportive at the level of community factors, not all LGB parents are able to find support.

“That is why, in addition to instituting inclusive and protective policies, we encourage community leaders to identify and remedy barriers that may be preventing LGB parents and their children from fully accessing what the community has to offer.”

The study, “Tolerance versus support: Perceptions of residential community climate among LGB parents,” is published in Family Relations. Co-authors include Ramona Faith Oswald and Jasmine M. Routon, both of the University of Illinois at Urbana Champaign, Jenifer K. McGuire, University of Minnesota, and Elizabeth Grace Holman, Bowling Green State University.

Oswald is a professor in the Department of Human Development and Family Studies in the College of Agricultural, Consumer and Environmental Sciences at U of I.

Funding for the study was provided by a UIUC Research Board grant for data collection.

News Source:

Ramona Oswald, 217-333-2547

Anticipating Dec.1 corn stocks

Published December 18, 2017

URBANA, Ill. – The USDA releases the estimate of corn stocks held in the United States on Jan. 12. On the same date, the final estimate of the size of the 2017 corn crop is revealed. The estimates show the level of corn consumption during the first quarter of the 2017-18 marketing year. According to University of Illinois agricultural economist Todd Hubbs, these estimates allow for an updated projection of the level of stocks likely to be on hand at the end of the marketing year and will provide an indication of the direction for corn prices through the spring.

“Anticipating the Dec.1 corn inventories is difficult because the final estimate of the size of the 2017 crop and the scale of consumption during the first quarter of the marketing year are unknown,” Hubbs says. “Given the November forecast for corn production is correct at 14.58 billion bushels and the consumption level for feed and residual use is on pace to meet the USDA’s current projection during the 2017-18 marketing year, a Dec.1 stocks estimate can be calculated using currently known consumption data. A Dec.1 stocks estimate near the calculated value can be considered neutral for corn prices. An estimate substantially different from the calculated value may result in price movements.”

Export totals are readily available during the first quarter of the marketing year, Hubbs says.  Official Census Bureau export estimates are available for September and October. USDA cumulative weekly export inspection estimates are available through the week ended Dec.10.  Cumulative export inspections for September, October, and November totaled 246 million bushels. Census Bureau estimates through October exceeded cumulative export inspections by 32.5 million bushels.

“Assuming the same difference continued through November, corn exports during the first quarter of the marketing year were likely very close to 342 million bushels,” Hubbs says. “This level of exports would be about 206 million bushels less than during the first quarter last year.”

Based on estimates in the USDA Grain Crushings and Co-Products Production reports, 915.6 million bushels of corn were used for ethanol and co-product production in September and October of 2017. Use of corn for the production of those products during November can be estimated based on the U.S. Energy Information Administration (EIA) ethanol production estimate for November.

“The production estimate for November is based on weekly EIA estimates which sometimes differ from the subsequent monthly estimates,” Hubbs says. “Weekly estimates pointed to November 2017 ethanol production of 1.352 billion gallons, 6 percent larger than production in November 2016 when 451.9 million bushels of corn were used for ethanol and co-product production. A 6 percent increase would put November 2017 corn use at 479 million bushels and use during the first quarter of the marketing year at 1.395 billion bushels. Thus far this marketing year, less sorghum has been used for ethanol production and this appears to have continued into November. Corn use during the quarter is estimated at 1.4 billion bushels.”

For the 2017-18 marketing year, the USDA projects domestic corn consumption for the production of food, seed, and industrial products other than ethanol at 1.46 billion bushels. Hubbs says the projection is 0.5 percent larger than consumption during the previous year.   Quarterly consumption for those products is relatively consistent in most marketing years. “A 0.5 percent year-over-year increase in the first quarter this year would have resulted in a use level of about 350 million bushels.”

The Dec.1 stocks estimate reveals the size of the feed and residual use category for the first quarter of the marketing year. For the year, the USDA has projected feed and residual use of corn at 5.575 billion bushels, up substantially from the estimate of 5.463 billion bushels used in the 2016-17 marketing year. An estimate of 2.274 billion bushels of corn was used in the feed and residual category during the first quarter of the marketing year last year.

“Given the growth in the livestock sector over the last year, feed and residual use should be proceeding more rapidly than last year,” Hubbs says. “If the USDA projection is correct, feed and residual use in the first quarter is projected at 2.342 billion bushels.”

Corn consumption during the first quarter of the marketing year is estimated to be near 4.64 billion bushels. Stocks of corn at the beginning the marketing year totaled 2.295 billion bushels and imports during the quarter were likely near 4 million bushels. With a crop of 14.578 billion bushels, the corn supply totaled 16.877 billion bushels. The calculation for the Dec.1 stocks estimate is 12.223 billion bushels, around 163 million bushels lower than last year.

“Because the current supply is quite large, a substantial deviation from this estimate may be necessary to generate a price reaction this marketing year,” Hubbs says.

 

Researcher aims to improve post-harvest processing in Bangladesh beginning with mangos

Published December 18, 2017
mango sorting in Bangladesh
Photo courtesy of Dr. Sorof Uddin

URBANA, Ill. – Bangladesh produces a substantial number of agricultural products, such as mango, and although most other developing countries have adopted modern technologies, post-harvest processing in Bangladesh is still predominantly being done manually. Grading, sorting, and processing is slow going. Add to that poor storage and packaging, inefficient handling and transportation, and other issues. As a result, post-harvest losses, of especially perishable products, can reach 40 to 50 percent.

A University of Illinois researcher, who is originally from Bangladesh, is working to develop inexpensive technologies to help mango growers in his country reduce the time and tedium in at least one aspect of post-harvest processing—sorting and grading.

“There aren’t any computer-based technologies in Bangladesh. Mangoes are hand-picked from the trees and brought by truck to the plant,” says Md Abdul Momin who led the research. “The post-harvest process includes picking up each piece of fruit, weighing it, and sorting it for quality, such as disease or blemishes, and size. A mango weighing 300 grams goes in this pile, 200 gram fruit goes in that pile over there.”

Momin says grading the produce is important as it ensures high-value products that can be sold at premium prices. There is a critical need to quickly, accurately, and efficiently assess agricultural products without the use of human labor.

“Automatic grading and sorting systems that use machine vision to determine size, shape, color, ripeness, weight, bruising, disease, rot, etc., are already being used in many countries,” Momin says. “When I began working with image processing, I thought it might be something that I could adapt to help make mango production in Bangladesh more efficient.”

Momin worked with a student and a mango farm manager. The goal was to develop something inexpensive that could help sort and grade mangoes, particularly during the peak season in the summer when Bangladesh is very hot, labor is scarce, and the volume of harvested fruit becomes overwhelming.

“We used a camera for about $400, a lamp for $50, and tin plate to create a simple way to collect images,” Momin says. “We designed the system using parts that aren’t fancy or expensive. You can even use a web camera that costs about $50 to $100.”

The mangoes are first weighed. Then the camera and light box are used to determine its area.

“The camera takes an image showing that the mango is 30,000 pixels so it belongs in the grade A category with the highest-quality, 300-gram mangoes. Using this technology, we can separate the harvest into large, medium, and small size mangoes,” Momin says.

According to Momin, there is also a consumer preference for roundness. “If they don’t like the shape of the mango, they don’t want to buy it. So we used another parameter called roundness. For this technology, the shape parameter does not translate well to a weight, so that’s an aspect that we need to do further work on.”

In this initial phase, the imaging is done in a box. “When scaled up to a system large enough to operate in the processing plant, it will need to incorporate a moving conveyor belt or some other method to transport the fruit through the imaging area,” says Tony Grift who is a co-author on the research paper.

Momin adds that in Bangladesh, there are banana, tomato and potato crops. And, although this particular research was done on mango, it can be adapted to other fruits and vegetable crops.

The study, “Geometry-based mas grading of mango fruits using image processing,” is published in Information Processing in Agriculture. The research was conducted by Md Abdul Momin, M.T. Rahman, M.S. Sultana, C. Igathinathane, A.T.M. Ziauddin, and Tony Grift.

This work has been partially supported by The World Academy of Sciences (Ref.: 13-311 RG/ITC/AS_C); and MoICT, Bangladesh (code: 3-0001-2801-5965).

Md Abdul Momin is postdoctoral research associate in the Institute for Genomic Biology at U of I. Tony Grift is an associate professor in the Department of Agricultural and Biological Engineering in the College of Agricultural, Consumer and Environmental Sciences at the University of Illinois.

 

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