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Plantarray is an automated sensor-based phenotyping platform. It enables scientists, breeders, and researchers to conduct simultaneous performance analysis of plants under various environmental conditions.

This scalable platform accurately measures physiology traits that are excellent indicators for yield potential with a proven correlation to field yield results. It's a quick and effortless way to evaluate new plant varieties or chemical and biological input materials.

Why use Plantarray?

Plantarray is a fully automated sensor-based phenotyping platform that enables scientists, breeders and researchers to rapidly and easily conduct simultaneous performance analyses of whole plants. It continuously measures and analyzes several key aspects of plant performance such as biomass accumulation, water and nutrients use efficiency, key physiological traits activity, environmental effects and more – all in real-time!

Research using this technology spans a number of fields, such as abiotic stress tolerance, nutrient and bio-stimulant development, root and soil investigation, etc. Additionally, it can be utilized to screen new plant varieties or assess agronomic management practices.

The Plantarray system is a non-invasive platform that enables researchers to conduct phenotyping experiments on plants without harming them or the experiment. It features a high throughput gravimetric and multisensors-based screening platform which continuously measures multiple shoot and root physiological traits as well as soil conditions for each plant in its greenhouse environment.

Plantarray 3.0 is a scalable system that enables scientists to simultaneously screen for abiotic stress tolerance in large numbers of plants and genotypes – such as excessive heat or cold, drought, salt or other environmental stresses common among farmers today. It provides continuous real-time information about each plant's physiological status which is crucial for optimizing agronomy management practices.

What is the importance of Plantarray?

Plantarray is an innovative high-throughput phenotyping system that measures plant physiological response to changing environmental conditions in real time and without invasive sampling. The collected data can be used for various purposes such as selecting chemical and biological input materials, optimizing agronomic management practices and characterizing new plant varieties.

Plantarray 3.0 was utilized to monitor the growth and water use of quinoa varieties Pasto and selRiobamba under salinity (0-300 mM NaCl). At 200 mM NaCl, salinity reduced cumulative transpiration by 60% for both varieties, while at 300 mM NaCl it only affected them by 75 and 82%, respectively (Figure 3A).

Stomatal conductance was also negatively impacted by salt stress, but at 200 mM NaCl concentration the reduction was smaller (15%) for Pasto than selRiobamba (34%), along with a decrease in specific leaf area. Furthermore, whole-plant agronomic water use efficiency (WUE) was higher at 200 mM NaCl than at the control at various time points during the experiment; however this effect of salt treatment decreased over the growing period.

How can Plantarray help you?

The Plantarray platform provides scientists, breeders and researchers with a dependable sensor-based phenotyping system that allows for simultaneous performance analysis of the entire plant. It measures water movement (plant transpiration), biomass accumulation, nutrient use efficiency and key plant physiological traits activity – including stomatal conductance – rapidly and precisely. This information allows precise predictions of growth and productivity at all stages in agriculture such as product development or management optimization. It's an indispensable asset in agronomic research, product development or optimization activities.

Plantarray was developed through over 10 years of research using weighing lysimeters to measure plant responses under various environmental conditions. Its unique, fully automated technology platform integrates various sensors with VPD (volume plant production) and environmental sensing to deliver fast, accurate data regarding plants' productivity in real-time, thus expediting research.

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