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Bruno Basso - Michigan State University. East Lansing, MI, US

Bruno Basso Bruno Basso

Ecosystems Scientist | Michigan State University

East Lansing, MI, UNITED STATES

Research deals mainly with water, carbon, nitrogen cycling & modeling in agro-ecosystems.

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Biography

Bruno Basso's research deals mainly with water, carbon, nitrogen cycling and modeling in agro-ecosystems for sustainable intensification and long-term sustainability. He uses geospatial analysis and tools linked to crop modeling.

During his carrier, Dr. Basso has participated as PI and Co-PI in several international projects. He is the author of more than 150 publications (Books written (2); chapters of books (6); technical refereed papers (47); Technical papers non refereed (98); invited keynote lectures (30).

Areas of Expertise (5)

Sustainabile Intensification Nitrogren Water Carbon Agro-Ecosystems

Accomplishments (6)

Innovation of the Year, Michigan State University Technology (professional)

2016

Fellow of the Soil Science Society of America (professional)

2015

Fellow of the American Society of Agronomy (professional)

2013

Pierre Robert Precision Agriculture Award” ICPA (professional)

2010

L.Frederick Lloyd Soil Teaching Award” ASA-SSSA-CSSA (professional)

2008

L.R. Ahuja Agricultural System Modeling Award” ASA-SSSA-CSSA (professional)

2007

Education (1)

Michigan State University: PhD, Crop and Soil Sciences 2000

News (3)

Warming Planet Could Mean Bigger Corn Crops for U.S.

Bloomberg  online

2018-05-17

While hotter weather generally threatens to sap crops of needed moisture, data from Midwest corn-growing states suggests the region will see warmer summers with more humidity, which would aid plant growth and yields, according to a study by Michigan State University researchers Bruno Basso and Joe Ritchie.

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What Satellites Can't See

AG Web  online

2018-04-12

For decades, government satellites have been taking detailed photographs of crops around the world that are now being tapped by traders like Cargill Inc. to gain an edge in global grain markets.

But the U.S. Department of Agriculture -- the benchmark in forecasting domestic crops -- says the images by themselves still can’t be relied upon to predict annual corn, wheat or soybean harvests. Instead, the government’s main source of information remains farmer surveys and random field samples.

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Faculty Voice: Bruno Basso – Digital Agriculture

United States Department of Agriculture National Institute of Food and Agriculture  online

2017-07-12

Extreme weather events provide challenges for agriculture. Big data can help farmers improve management strategies for water, nutrients and evaluate the economics of smart agriculture technologies and practices. There is a limit to the amount of land we can use to grow food and, as the world’s population continues to grow, farmers will need to produce more food without increasing the amount of land they cultivate.

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Journal Articles (4)

N2O and CO2 emissions following repeated application of organic and mineral N fertiliser from a vegetable crop rotation Science of The Total Environment

Daniele De Rosa, David W Rowlings, Johannes Biala, Clemens Scheer, Bruno Basso, Peter R Grace

2018

Accounting for nitrogen (N) release from organic amendments (OA) can reduce the use of synthetic N-fertiliser, sustain crop production, and potentially reduce soil borne greenhouse gases (GHG) emissions.

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Soil organic carbon and nitrogen feedbacks on crop yields under climate change Agricultural & Environmental Letters

B Basso, et al.

2018

Soil organic carbon and nitrogen feedbacks on crop yields under climate change.

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Multi-model ensembles improve predictions of crop-environment-management interactions Global Change Biology

B Basso, et al.

2018

Multi-model ensembles improve predictions of crop-environment-management interactions

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The Hot Serial Cereal Experiment for modeling wheat response to temperature: field experiments and AgMIP-Wheat multi-model simulations Open Data Journal for Agricultural Research

Bruno Basso, et al.

2018

The data set reported here includes the part of a Hot Serial Cereal Experiment (HSC) experiment recently used in the AgMIP-Wheat project to analyze the uncertainty of 30 wheat models and quantify their response to temperature. The HSC experiment was conducted in an open-field in a semiarid environment in the southwest USA.

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