Posts Tagged ‘digital agriculture’

Maize Ear Digital Imaging for Yield Components Assessment

Posted on , April 8, 2019

In Sub-Saharan Africa, many food security programs aim to increase crop yields by developing and disseminating better seeds and agronomy to millions of smallholder farmers. In the case of maize, research and development organizations use key indicators like grain yield, or maize cob number and size to understand the performance of the maize plant under different environmental conditions. But these indicators are still labor-intensive and expensive to measure. CIMMYT has developed a digital imaging tool called Maize Ear Analyzer that collects maize cob and grain parameters 90% faster than traditional methods (Makanza et al, 2018). This imaging tool can be adapted to other crops.

Digital imaging tools make maize breeding much more efficient

Posted on Media&Stories, News, Research News, March 14, 2019

To accelerate annual genetic gains under various stress conditions, maize breeders are looking at cost-effective ways to assess a larger number of maize plants and to collect more accurate data related to key plant characteristics like kernel number and size per ear, leaf angles or ear heights.


Measuring maize attributes such as ear size, kernel number and kernel weight is becoming faster and simpler through digital imaging technologies.

Recent innovations in digital imagery and sensors, packaged in what plant scientists call high-throughput phenotyping platforms, save money and time by replacing lengthy paper-based visual observations of crop trials with real-time big data collection and management.

Authors of a recent review study on high-throughput phenotyping tools observe that obtaining accurate and inexpensive estimates of genetic value of individuals is central to breeding. Under the Stress Tolerant Maize for Africa project, researchers like Mainassara Zaman-Allah use drone and create new digital tools, like the ear analyzer, for cheaper and faster plant selection. Drone cuts data collection costs by 25 to 75 percent compared to conventional methods.  The ear analyzer allows to collect maize ear and kernel trait data 90 percent faster. This mobile app has been used by CIMMYT and the GOAL NGO to assess the extent of fall armyworm impact on maize crops yield in eastern Zimbabwe.

Read more about how STMA makes maize breeding faster and cheaper here

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