CAMO Software


In order to meet the needs of a rapidly growing population, agricultural companies today are having to cope with high energy prices, climate change, and concerns about the environment, while at the same time managing traditional factors such as improving crop yields and minimizing the damage from pests and disease.

Despite more advanced agricultural methods, high commodity prices are putting strains on both agricultural producers and consumers in the form of high food prices. Applying scientific knowledge to the agricultural sector can give industry players a competitive advantage and help optimize their production.

CAMO Software can improve efficiency and yield in every step of agricultural production – from analysis of planting and seed conditions, through real-time monitoring of crop development to optimized processing and distribution of the final product. Our intuitive software suite, the Unscrambler® X, is designed for both industrial-quality scientific accuracy as well as an intuitive and visual interface. Our clients so far have proven that it is therefore just as applicable for the single user as it is for a global enterprise.

In addition to the improvements in productivity, multivariate analysis is an important tool in the battle against climate change and environmental damage. Considering the increasingly strict legislation on the topic, CAMO’s software is ideal for controlling both contaminant output and toxicity.

Multivariate analysis can be used for a wide range of applications, including:

  • Prediction of soil content using near-infrared spectroscopy (NIR)
  • Precision agriculture: using PLS quantification of NIR of soil to tailor fertilization of crops
  • Determining ripeness of fruit to optimize harvesting from transmittance NIR
  • Assessing agronomic and environmental effects of different types of compost using PCA
  • Morphological characterization of food products using cluster analysis
  • Analysis of toxicological and environmental properties of soil nematicides
  • Applying PLS regression to predict sensory qualities of food products or performance of different hybrids
  • Using NIR to assess bio-fuel feedstock composition and quality

As pioneers in MVA, our software and solutions have been tried and tested for over 25 years by agricultural producers. Contact us to find out how we can help or to arrange a free demonstration.