<?xml version="1.0" encoding="UTF-8"?><article>
  <title>Is the current version of model ORYZA2000 able to encounter the multi-level stakeholders&#8217; demand for on-farm decision making?</title>

      <doi>https://doi.org/10.21276/AATCCReview.2024.12.04.471</doi>
  
  <authors>
      </authors>

      <abstract><![CDATA[<p>The ORYZA2000 model, developed by the International Rice Research Institute (IRRI) and<br />
Wageningen University, is a sophisticated tool for accurately predicting rice growth cycles and<br />
development under varying conditions. It excels in replicating field-level crop growth through<br />
meticulous calibration and validation across different agroecological settings worldwide.<br />
Operating on a daily time step, the model computes plant organ dynamics at different<br />
phenological stages by calculating rate variables for each time step and integrating state variables<br />
over the entire crop-growing period. ORYZA2000&#39;s applications extend to simulating agronomic<br />
management practices such as optimal fertilizer application, water management, and crop<br />
planning without the need for extensive field data. While it is commonly used to evaluate the<br />
impact of changing climate factors on rice yields, such as future rainfall patterns, temperature<br />
shifts, and elevated CO 2 levels, the model currently lacks flexibility in assessing factors like pest<br />
and disease damage, remote sensing applications, extreme weather events, and diverse crop<br />
varieties within a single simulation run. Despite these limitations, the ORYZA 2000 model<br />
remains a valuable tool for assessing management practices and forecasting rice production under<br />
evolving climatic conditions based on the latest CMIP6 climate model projections. Efforts to<br />
enhance the model&#39;s versatility in handling a broader range of factors are essential for its<br />
continued relevance and utility in rice crop research and planning.</p>
]]></abstract>
  
  <body><![CDATA[<div class="aatcc-article-container"><div class="aatcc-category-label">Original Research Article</div><div class="aatcc-meta-box"><div class="aatcc-doi-wrap">
            <a class="aatcc-doi-btn" href="https://doi.org/10.21276/AATCCReview.2024.12.04.471" target="_blank">https://doi.org/10.21276/AATCCReview.2024.12.04.471</a>
        </div><div class="aatcc-abstract-section">
                <h3>Abstract</h3>
                <div class="aatcc-abstract-text"><p>The ORYZA2000 model, developed by the International Rice Research Institute (IRRI) and<br />
Wageningen University, is a sophisticated tool for accurately predicting rice growth cycles and<br />
development under varying conditions. It excels in replicating field-level crop growth through<br />
meticulous calibration and validation across different agroecological settings worldwide.<br />
Operating on a daily time step, the model computes plant organ dynamics at different<br />
phenological stages by calculating rate variables for each time step and integrating state variables<br />
over the entire crop-growing period. ORYZA2000&#39;s applications extend to simulating agronomic<br />
management practices such as optimal fertilizer application, water management, and crop<br />
planning without the need for extensive field data. While it is commonly used to evaluate the<br />
impact of changing climate factors on rice yields, such as future rainfall patterns, temperature<br />
shifts, and elevated CO 2 levels, the model currently lacks flexibility in assessing factors like pest<br />
and disease damage, remote sensing applications, extreme weather events, and diverse crop<br />
varieties within a single simulation run. Despite these limitations, the ORYZA 2000 model<br />
remains a valuable tool for assessing management practices and forecasting rice production under<br />
evolving climatic conditions based on the latest CMIP6 climate model projections. Efforts to<br />
enhance the model&#39;s versatility in handling a broader range of factors are essential for its<br />
continued relevance and utility in rice crop research and planning.</p>
</div>
            </div></div></div>]]></body>
</article>
