CLAAS captures two farm machine innovation awards – High Plains Journal

Nov 27, 2025 - 01:00
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CLAAS captures two farm machine innovation awards – High Plains Journal

 

CLAAS Innovations at Agritechnica: A Report on Contributions to Sustainable Development Goals

CLAAS has received two awards at the Agritechnica trade show for the Jaguar 1200 forage harvester and the CEMOS Auto Chopping system. These innovations demonstrate a significant alignment with several United Nations Sustainable Development Goals (SDGs) by enhancing agricultural productivity, resource efficiency, and sustainable practices.

Jaguar 1200 Forage Harvester: Advancing Productivity and Sustainability

Contribution to SDG 2 (Zero Hunger) and SDG 8 (Decent Work and Economic Growth)

The Jaguar 1200’s design directly supports the goal of ending hunger by substantially increasing agricultural productivity. Its record-breaking performance underscores its capacity to improve food supply chains and promote economic growth through enhanced efficiency.

  • Enhanced Throughput: Achieves up to 1,110 horsepower, enabling throughput rates of up to 500 tons per hour.
  • Superior Chop Quality: Features fully hydraulic pre-compression and a 310-mm Corncracker to ensure consistent, high-quality animal feed, which is fundamental to a secure food system.
  • Record-Setting Productivity: A new Guinness World Record was set by harvesting 4,515 tons of wheatlage in 12 hours, more than doubling the previous record and showcasing a leap in operational efficiency that drives economic productivity.

Alignment with SDG 12 (Responsible Consumption and Production) and SDG 8 (Decent Work)

The machine incorporates features that promote sustainable land use and improve working conditions for operators, aligning with responsible production and the promotion of decent work.

  • Soil Protection: A high-traction, soil-friendly chassis minimizes soil compaction, contributing to sustainable land management and responsible production.
  • Operator Welfare: An upgraded quiet cab, swivel seat, and optional joystick steering reduce operator fatigue and enhance safety, promoting decent and safe work environments.
  • Digital Integration: Advanced tools in CLAAS connect and the CEMOS operator assistance system optimize machine performance, reducing resource consumption per ton harvested.

CEMOS Auto Chopping: AI-Driven Efficiency for Sustainable Feed Production

Contribution to SDG 12 (Responsible Consumption and Production) and SDG 2 (Zero Hunger)

The CEMOS Auto Chopping system utilizes artificial intelligence to optimize forage processing quality in real-time, directly impacting resource efficiency and the nutritional value of feed, which contributes to reducing food loss along production chains.

  1. Real-Time Analysis: An AI-powered CMOS-sensor camera continuously analyzes the chopped material and grain processing in the discharge spout.
  2. Automated Adjustment: The system automatically adjusts the cracker gap, ground speed, and engine power if the measured value deviates from the target corn silage processing score.
  3. Quality Assurance: This process ensures optimal feed quality, which is crucial for livestock health and productivity, thereby reducing feed waste and supporting sustainable production patterns.

Alignment with SDG 9 (Industry, Innovation, and Infrastructure)

This technology exemplifies the integration of advanced digital infrastructure into agriculture to build resilient and innovative systems that support sustainable development.

  • Cloud-Based Data Management: Data collected by the system is transferred to the CLAAS connect farm management platform, fostering innovation in agricultural data analysis.
  • Informed Decision-Making: This data can be documented and utilized for comprehensive quality assurance evaluations and transparent billing, fostering a more technologically advanced and accountable agricultural sector.

Analysis of Sustainable Development Goals in the Article

  1. Which SDGs are addressed or connected to the issues highlighted in the article?

    The article on CLAAS’s innovative agricultural machinery connects to several Sustainable Development Goals (SDGs) by focusing on advancements in agricultural productivity, efficiency, technology, and sustainability.

    • SDG 2: Zero Hunger

      This goal is central to the article, which discusses technology designed to significantly increase the productivity and efficiency of harvesting operations. By improving the rate and quality of forage harvesting, this technology directly contributes to securing a stable and high-quality food supply for livestock, which in turn supports food production systems.

    • SDG 9: Industry, Innovation and Infrastructure

      The article highlights cutting-edge innovation in the agricultural industry. The development of the Jaguar 1200 and the CEMOS Auto Chopping system, which incorporates artificial intelligence and cloud-based data management, exemplifies the push towards upgrading technological capabilities and fostering innovation within an essential industrial sector.

    • SDG 12: Responsible Consumption and Production

      The technology described promotes more sustainable and efficient production patterns. By optimizing chop quality, engine power, and ground speed, the systems ensure the efficient use of resources like fuel and the harvested crop itself, minimizing waste and maximizing the value of agricultural output.

  2. What specific targets under those SDGs can be identified based on the article’s content?

    The article’s content points to several specific targets within the identified SDGs.

    • Under SDG 2 (Zero Hunger):

      • Target 2.3: “By 2030, double the agricultural productivity and incomes of small-scale food producers…” The Jaguar 1200’s record-breaking performance, harvesting 4,515 tons in 12 hours and achieving throughput rates of up to 500 tons per hour, directly addresses the goal of increasing agricultural productivity.
      • Target 2.4: “By 2030, ensure sustainable food production systems and implement resilient agricultural practices that increase productivity and production… and that progressively improve land and soil quality.” The mention of a “high-traction, soil-friendly chassis” on the Jaguar 1200 directly relates to implementing practices that improve soil quality and ensure the sustainability of food production.
    • Under SDG 9 (Industry, Innovation and Infrastructure):

      • Target 9.4: “By 2030, upgrade infrastructure and retrofit industries to make them sustainable, with increased resource-use efficiency and greater adoption of clean and environmentally sound technologies…” The CEMOS system, which automatically adjusts machine settings for efficiency, and the overall focus on “cost-effectiveness” represent the adoption of advanced, resource-efficient technologies in the agricultural industry.
      • Target 9.5: “Enhance scientific research, upgrade the technological capabilities of industrial sectors… encouraging innovation…” The entire article is a showcase of this target, celebrating award-winning innovations like AI-supported analysis and cloud-based farm management systems developed through dedicated research and development.
    • Under SDG 12 (Responsible Consumption and Production):

      • Target 12.2: “By 2030, achieve the sustainable management and efficient use of natural resources.” The CEMOS system’s ability to automatically adjust “engine power” implies optimized fuel consumption. Furthermore, by ensuring “consistent chop quality” and monitoring the “corn silage processing score,” the technology maximizes the nutritional value of the feed, ensuring the efficient use of the harvested crop.
  3. Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?

    Yes, the article mentions several quantitative and qualitative indicators that can be used to measure progress.

    • For SDG 2 Targets:

      • Productivity Rate: The article explicitly states a “throughput rates of up to 500 tons per hour” and a world record of “4,515 tons of wheatlage in 12 hours.” These figures are direct indicators of agricultural productivity (Target 2.3).
      • Sustainable Farming Practice Adoption: The feature of a “soil-friendly chassis” serves as a qualitative indicator for the adoption of practices that improve soil quality (Target 2.4).
    • For SDG 9 Targets:

      • Adoption of Advanced Technology: The use of an “AI-powered CMOS-sensor camera,” “cloud-based farm management system CLAAS connect,” and the “CEMOS Auto Chopping” system are clear indicators of technological upgrading and innovation within the agricultural sector (Targets 9.4 and 9.5).
    • For SDG 12 Targets:

      • Feed Quality Score: The “corn silage processing score value” is mentioned as a “standard indicator of feed quality.” This metric can be used to measure the efficiency of production, as higher quality feed reduces waste and maximizes resource use (Target 12.2).
      • Resource Optimization: The system’s function to automatically adjust “engine power” implies a measurable indicator for resource efficiency, specifically fuel consumption (Target 12.2).
  4. Table of SDGs, Targets, and Indicators

    SDGs Targets Indicators
    SDG 2: Zero Hunger
    • 2.3: Double agricultural productivity.
    • 2.4: Ensure sustainable food production systems and improve soil quality.
    • Harvest throughput rate (up to 500 tons per hour).
    • Total harvest volume over time (4,515 tons in 12 hours).
    • Adoption of soil-friendly technology (“soil-friendly chassis”).
    SDG 9: Industry, Innovation and Infrastructure
    • 9.4: Upgrade industries with increased resource-use efficiency and adoption of sound technologies.
    • 9.5: Enhance scientific research and upgrade technological capabilities.
    • Implementation of AI-powered systems (CEMOS Auto Chopping).
    • Use of cloud-based data management (CLAAS connect).
    • Development of award-winning innovative machinery.
    SDG 12: Responsible Consumption and Production
    • 12.2: Achieve the sustainable management and efficient use of natural resources.
    • Feed quality measurement (“corn silage processing score value”).
    • Automatic optimization of resource inputs (engine power adjustment).
    • Focus on “efficiency” and “cost-effectiveness” in machine design.

Source: hpj.com

 

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