PlantDiTech’s SPAC (Soil-Plant-Atmosphere-Continuum) Analytics is cloud-based software that performs real-time statistics, analysis and productivity prediction. 
SPAC-Analytics enables agro-researchers to process input from multiple sensors and sources, and provide a statistical and graphic representation of any correlations from various growth and productivity traits, together with environmental parameters (stress included). The output is a detailed performance analysis based on advanced statistical tools of the plant population and the treatment responses. The data is retrieved automatically and continuously from large arrays of plant samples over any period of a growth cycle.

The software allows you to run real-time multiple analysis during and following the experiment, using huge amounts of real-time data that are impossible to process manually.

The SPAC-Analytics software is a complementary product to the high throughput plant phenotyping equipment

• Real-time statistical analysis - multi-factorial ANOVA or paired T-test, for reliable and fast results
• Reach your goal - optimize experimental parameters during the experiment to make sure of the effectiveness of the treatment when it matters
• Fast quantitative selection - produces a performance-based profile for rating and scoring plant physiological response to different environmental needs
• Simple graphical presentation of complex experiments - spatial and temporal relationships between measured physiological variables and ambient conditions, showing tendencies, anomalies and ratios

The system processes and presents correlations, both numerically and graphically, between values, tendencies, anomalies and ratios in the relationship between the following measures and imposed conditions:

1. Smoothed time series of the measured parameters (weight, soil water content, atmospheric water demand, etc.).
2. The rate of change of the above-mentioned parameters over time.
3. Plants biomass gain along different time intervals (days, weeks, and season).
4. The pattern of daily transpiration.
5. The water use efficiency (WUE) along different time intervals (days, weeks, and season).
6. Soil water content (either by mass balance calculation or direct measurement by a specific sensor).
7. Stomatal conduction variation along the hours of the day.
8. Influx from the soil to the roots (when soil sensors are installed).
9. The variation of the plant's relative water content during the day hours.