Dry Matter (DM)

Dry Matter (DM) is the mass remaining in plant tissue after complete water removal, typically by oven drying; it provides a moisture-independent measure of crop growth and tissue or substrate composition in greenhouse diagnostics and models.

Measurement of DM hinges on oven-drying plant material to a constant weight, yielding the dry matter content used to quantify growth and nutrient status independent of water content. In greenhouse climate control and crop modelling, DM acts as both a state variable (dry matter content or mass fraction) and a flux (dry matter production rate, ∆W/dt) linked to photosynthesis and respiration. The dry basis standardizes tissue analyses, substrate specifications, and nutrient reporting across varying water contents and plant stages. Reporting DM supports stoichiometric conversions such as translating CO2 inputs to dry matter and comparing tissue data across harvests. Synonyms and abbreviations: dry weight, dry mass, DM, dry-matter content, dry matter production, dry weight basis, mass fraction dry matter.

Dry matter is a central denominator in greenhouse decision making because water content fluctuations can mask underlying biomass changes. DM tracking informs how climate drivers such as light, CO2, temperature, and vapor pressure deficit translate into biomass accumulation and allocation patterns. Operators use DM-based indicators to tune irrigation scheduling, substrate management, and nutrient supply, reducing the risk of waterlogging or under-watering and helping optimize energy use for heating and dehumidification. DM content interacts with canopy traits and climate metrics such as leaf area index, canopy temperature, and stomatal conductance, influencing model-based setpoints for lighting and ventilation. Because most crop models express growth as DM production, accurate DM measurement and consistent reporting are essential for reliable forecasts and automation that align with real crop responses. In practice, DM is obtained through plant sampling and oven-drying to stable weight, which introduces measurement lag relative to real-time climate control but is still required for model calibration and cross-sample comparability. Growers translate DM-based tissue analyses to actionable insights by expressing nutrients on a DM basis, providing consistent interpretation regardless of irrigation status or plant water content. DM formation reflects the balance between photosynthesis and respiration, so DM budgets support carbon balance calculations and CO2 enrichment planning when integrated with climate control strategies. In substrate and fertilizer programs, reporting constituents on a DM basis avoids water-content bias and supports mass-balance calculations for mixing and application. Finally, DM concepts underpin CO2 budgeting, where a defined g CO2 per g DM formed feeds into growth respiration and energy-use estimates that guide HVAC and lighting strategies.

Examples include: In a cucumber greenhouse, DM production rate ∆W/dt is used in crop growth models to forecast harvest timing and evaluate the impact of fruit load on biomass; In tomato cropping, DM partitioning among leaves, stems, and fruit informs sink/source balance under different light regimes and plant densities; Tissue analyses in lettuce or strawberry reported on a DM basis enable comparisons of nutrient status when leaf water content fluctuates; Substrate management uses DM basis to express compost or manure contents for correct mixing and fertilizer planning; Gas exchange and respiration linking DM formation to CO2 efflux helps balance greenhouse carbon budgets and informs CO2 enrichment strategies; Converting measured nutrient concentrations from fresh weight to mmol kg−1 DM standardizes interpretations across growth stages; In practice, DM-based reporting supports irrigation scheduling by flagging changes in dry matter content that accompany water stress; Crop-model calibration uses DM production data to adjust photosynthesis and respiration parameters; For substrate testing, g DM per kg substrate is used to compare material quality across suppliers.

Dry matter concepts underpin both theory and practical greenhouse operations by anchoring growth assessments to biomass accumulation rather than raw water content. They inform psychrometric relationships, climate setpoints, and control algorithms because DM responds to light, CO2, temperature, and humidity through photosynthesis and respiration, linking canopy physiology to model outputs. Using DM as a reporting denominator reduces biases from fluctuating moisture and enables consistent tissue and substrate comparisons across crops and growth stages. The timing and storage nature of DM mean that decisions based on DM data must account for lag, sampling costs, and standardization of oven-drying methods, but when integrated with real-time sensors and models, DM improves forecasting, scheduling, and resource use. In practice, DM-based reporting supports decision support tools, feed-forward control elements, and CO2 budgeting in conjunction with HVAC and lighting strategies, improving energy efficiency and crop outcome predictability. The concept also underpins nutrient diagnosis and substrate specification by expressing concentrations on a DM basis, enabling apples-to-apples comparisons across harvests and media. Sources — Online: https://extension.psu.edu/psychrometric-chart-use/; https://ceac.arizona.edu/sites/default/files/asae_-_heating_ventilating_and_cooling_greenhouses.pdf; https://www.controlledenvironments.org/wp-content/uploads/sites/6/2017/05/Greenhouse-Guidelines.pdf; https://msu-prod.dotcmscloud.com/floriculture/uploads/files/Section%20_3.pdf.