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Thursday / January 30. 2025
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Soybean growers across the globe face a silent but devastating threat under the soybean cyst nematode (SCN). This microscopic pathogen attacks soybean roots, jeopardizing crop yields and causing more than $1.5 billion in annual losses in the United States alone. Despite decades of effort, effective solutions to protect soybeans from SCN remain elusive, as the pathogen is often detected only in later stages because its early symptoms are subtle. However, new research offers hope for a sustainable solution to this agricultural challenge

A recent study published in the journal Molecular Plant-Microbe Interactions (MPMI), led by the graduate student Alexandra Margets and other researchers from the Roger Innes Laboratory at Indiana University Bloomington, in collaboration with the Baum Lab at Iowa State University, has identified and characterized a key protein behind SCN infection. Their findings could revolutionize how farmers protect their crops from this pervasive threat.

The team of researchers identified an effector protein called CPR1 (″cysteine protease 1″), which SCN secretes into soybean roots during infection. CPR1 disrupts the plant’s immune system, paving the way for the pathogen to establish itself. Using a cutting-edge technique called ″proximity labeling,” the team identified a soybean protein, GmBCAT1 (branched-chain amino acid aminotransferase), as a target of CPR1. Further experiments revealed that CPR1 prevents the accumulation of GmBCAT1, suggesting cleavage. This discovery could enable the team to engineer ″decoy” proteins that trick SCN effectors into cleaving them, thereby triggering a robust plant immune response that prevents further infection.

″This work has broad impacts on our understanding of SCN parasitism and the development of a novel resistance strategy. If shown to be successful, we can develop plants that are resistant to SCN and deliver a new solution for soybean farmers to use in their fields,” said Roger Innes, head of the Innes Lab. ″If this technology works for SCN resistance in soybeans, it will almost certainly work for other crop plants and respective plant diseases.”

These insights could have far-reaching implications for global agriculture. By developing SCN-resistant soybeans, this research aims to reduce the reliance on chemical pesticides, lowering agriculture’s environmental impact while increasing crop yields. The complementary expertise of the Innes Lab in decoy protein engineering and the Baum Lab in soybean and nematode biology underscores the potential for transformative advancements in sustainable farming. Both labs hope this research will benefit farmers and promote sustainable agriculture by developing a new generation of SCN-resistant soybeans.

Soybean growers across the globe face a

For the first time, signals produced by a plant’s physiological response to infection will be linked to optimised crop treatments delivered with John Deere See & Spray technology. 

InnerPlant, the seed technology company enabling the earliest possible detection of stress in crops to make farming universally more efficient and sustainable, Syngenta, a global leader in agricultural innovation and crop protection and John Deere, a global leader in the delivery of agricultural, and construction, and forestry equipment, announce a joint effort to develop an integrated solution to fight fungus in soybeans. The first-of-its-kind solution will link together plants that give off early and specific signals when under attack by fungus with optimised crop protection treatments that are delivered with See & Spray technology.

“Fungal diseases are a massive and growing problem facing farmers who already face a great deal of risk in their operations,” explains Shely Aronov, CEO and co-founder of InnerPlant. “A solution that links signals directly from plants’ physiological responses to the individualised, precise delivery of optimised inputs will make farmers’ lives easier by delivering both improved efficacy and efficiency.”

Globally, crops are attacked by fungal diseases that result in substantial yield losses. And the problem is getting worse, according to experts who cite climate change and rising resistance to common fungicides as contributing to fast-rising fungal attacks that threaten the world’s food supply and a “global health catastrophe.”

“The technology from InnerPlant allows the detection of plant diseases at the earliest possible stage identifying plant diseases that otherwise often go undetected or untreated,” says Feroz Sheikh, Syngenta’s Chief Information and Digital Officer. “We are happy to engage in these initial trials with our partners. Integrated, innovative solutions are a critical path forward for managing the growing impact of soybean diseases and ensuring that farmers have the tools they need to feed the world.”

For the first time, signals produced by

SC Solutions’ I-SAT platform provides advanced satellite imagery and analytics, supporting Hunnicutt’s mission to be at the forefront of sustainable and precision agriculture practices

Hunnicutt Farms, a leading grower of corn, popcorn, soybeans, and feed corn, is advancing with its use of earth observation analytics by signing a contract with SC Solutions, Inc. SC Solutions’ I-SAT platform provides advanced satellite imagery and analytics, supporting Hunnicutt’s mission to be at the forefront of sustainable and precision agriculture practices.

“Our platform [I-SAT] takes high-resolution data to analyse key factors influencing corn growth, including soil health, moisture levels, and vegetation indices,” said Cliff Beek, CEO of SC Solutions. The differentiating output factor, according to Beek; “is the fusion of machine learning and space technology to progress agricultural practices.” 

Operating for over a century, Hunnicutt Farms has demonstrated an affinity for embracing innovative solutions. “Earth Observation technology aligns with our commitment to sustainability and precision farming,” expressed Brandon Hunnicutt, Owner Partner at Hunnicutt Farms, and a 5th generation Nebraska farmer. Hunnicutt added, “We’re excited about the potential to elevate our corn cultivation practices and contribute to a more sustainable future.”

Transforming vast swaths of raw data into actionable insights by leveraging advanced machine learning techniques, including deep learning and neural networks, I-SAT’s Precision Analytics offer an unparalleled deep dive into Earth’s observational data. The platform’s state-of-the-art AI analytics, hyperspectral capabilities, and intuitive visualisation techniques make complex earth observation data comprehensible, accessible, and actionable.

SC Solutions' I-SAT platform provides advanced satellite