What Should You Measure? A Practical Monitoring Guide for Home Growers

A plant can look unhealthy for several reasons. Wilting may reflect a dry growing medium, poor root function or a temporary mismatch between water uptake and water loss. Yellowing may involve nutrition, ageing, environmental damage or disease. A photograph or a single meter reading rarely identifies the cause on its own.

The most useful approach is to observe the plant, record the conditions around it and measure only the variables that can answer a specific question. For many home growers, a thermometer, a record of watering and consistent photographs are a better starting point than a collection of expensive sensors. Growers working with concentrated nutrient solutions or recirculating hydroponics will need additional measurements. For the broader diagnostic sequence, see Before You Add Anything, Learn to Read the Plant.

Featured image: LOCOMOS stations in an irrigated corn field in Manchester, Michigan (left), and an irrigated blueberry field in West Olive, Michigan (right). Figure 4 from Dong, Werling, Cao and Li (2024), Frontiers in Water, reproduced without alteration under CC BY 4.0. These are professional field installations, not a suggested equipment list for home growers.

Start with a question and a baseline

Before measuring, identify what has changed or what you want to improve. Is the plant drying out faster than before? Is new growth slower? Does the growing medium remain wet unexpectedly long? Record the species or cultivar, development stage, pot size, growing medium and location. These details influence how a measurement should be interpreted.

Take photographs of the whole plant and affected parts from similar positions and at comparable times. Note the progression of symptoms rather than only their presence. For growth monitoring, choose an indicator that actually reflects the question: new leaf development, stem extension, flower or fruit number, or harvestable mass. Plant height alone does not describe biomass production or plant health. If using weight, distinguish fresh mass from dry mass; a difference in water content can change fresh weight without an equivalent change in dry matter.

A baseline is not one perfect measurement. It is a short, consistent record that shows what conditions and plant responses looked like before an intervention. Record the date, place, method and units. Otherwise, a later value may be impossible to compare fairly.

Temperature and humidity: measure where the plant is

Air temperature and relative humidity are accessible and useful for most indoor growers. A thermometer and hygrometer with minimum–maximum memory can expose warm afternoons or cool nights that a single daytime reading misses. Place the instrument near canopy height, away from direct lamp radiation, heaters, windows and strong drafts as far as practical. The position of the sensor may matter as much as its advertised precision.

Temperature and relative humidity interact. Air vapour pressure deficit (VPD) is the difference between saturation vapour pressure at the air temperature and the actual water vapour pressure. It provides a useful framework for thinking about atmospheric demand for water, but it does not measure transpiration or prove the plant is under water stress. Leaf temperature may differ from air temperature, so air VPD is not necessarily the same as the leaf-to-air vapour pressure difference.

Commercial greenhouse climate computers often record temperature, humidity and radiation continuously, sometimes alongside CO₂ and outside weather. That does not mean a home grower needs to follow a single prescribed VPD value or purchase a CO₂ meter. Start by locating unusually hot, cold, dry or humid periods and relating them to actual plant responses. Both and colleagues’ greenhouse measurement guidelines explain why sensor position, measurement method and reporting context matter.

Light: duration is not intensity

Record where the plant stands, whether the light source is natural or artificial, and how long supplemental lighting operates. Those observations help explain seasonal changes and the effects of moving a plant, but the lighting schedule says nothing about the intensity reaching its leaves.

A suitable quantum or PAR sensor measures photosynthetic photon flux density (PPFD), usually in micromoles of photons per square metre per second (µmol m⁻² s⁻¹). The daily light integral (DLI), in mol m⁻² day⁻¹, represents the total photosynthetic photon exposure over a day. Light distribution, measurement height and changing sunlight also matter. A lux meter is weighted to human vision and cannot automatically be treated as a PAR meter; conversions require information about the spectrum and device.

When plants already grow well in a window, a detailed light map may add little. For growers comparing lamps, light heights or plant positions, repeatable PPFD measurements can be useful. Avoid adopting a universal target detached from crop, growth stage, temperature and the rest of the growing environment.

Watering: the amount and the drying pattern

For a plant in a container, recording water supplied and the interval between waterings is often more informative than an inexpensive moisture probe. Note approximately how much is added, whether the pot drains freely and how rapidly it becomes lighter. Pot weight can provide an indirect record of water loss when pot and watering method are consistent. It does not distinguish water loss by evaporation from transpiration and is not a direct measurement of oxygen availability at the roots.

Water retention and air-filled porosity differ among compost, peat-based mixes, coir, rockwool and mineral soils. A moisture sensor calibrated for one medium may not read another reliably. Probe position and local wet or dry patches can also distort the interpretation. If a container remains wet while a plant declines, inspect drainage and root condition rather than immediately assuming that one nutrient is missing. The Root System: The Foundation of Plant Performance explains why these root-zone conditions influence what happens above ground.

Professional substrate systems commonly compare irrigation supply with collected drain, sometimes using sensors for substrate water content and EC. Drain volume indicates how much solution left the sampled root environment; drain EC and pH describe that collected sample, not the full nutrient composition or every location around the roots. For ordinary pot culture, measuring a runoff percentage after every watering is rarely the first priority.

pH, EC and water composition: know the sample

A pH meter measures acidity or basicity of the tested solution. An EC meter measures its electrical conductivity, which responds to the dissolved ions collectively. It cannot distinguish calcium, nitrate or potassium from sodium and chloride, nor can it tell whether the plant has absorbed a particular nutrient. Neither measurement identifies a root disease. This distinction between supply and acquisition is explored in More Fertilizer, Less Uptake? The Roots Decide.

Always label the sample: plain source water, freshly prepared feed, reservoir solution, collected drain or a standardised extract of the growing medium. The methods and values are not interchangeable. In particular, pouring water through a pot and reading its runoff does not automatically reproduce a laboratory substrate test. Use calibrated instruments, appropriate standards, clean containers and consistent sampling conditions. For EC, mS/cm and dS/m are numerically equivalent; displayed ‘ppm’ or ‘TDS’ estimates depend on the meter’s conversion factor.

A source-water report may supply alkalinity, calcium, magnesium, sodium and chloride information that pH and EC meters cannot provide. Alkalinity and hardness are different properties; high source-water pH alone does not show how irrigation will influence substrate pH over time. If problems persist, checking alkalinity, hardness and individual ions is more useful than repeatedly adjusting pH without knowing the water composition. See Water Quality for Plants: More Than pH and EC for the source, storage and hygiene questions behind these measurements.

What professional greenhouses measure, and what is still specialised

Commercial practice depends on the crop and production system. In controlled greenhouse crops, regular crop walks and observations remain important alongside climate readings. In many higher-technology operations, air temperature, relative humidity and radiation are monitored by climate computers. CO₂ is relevant where enrichment and ventilation are actively managed. In soilless crops, feed and drain volume, pH and EC can form part of routine irrigation and nutrient monitoring. Substrate water content, root-zone temperature and growth measurements may also be used, depending on the business.

The 2025 paper by Maree and colleagues describes a particularly intensive Wageningen University & Research dwarf-tomato experiment. Six greenhouse compartments were monitored using climate, radiation, CO₂, irrigation, drain, substrate and crop-image data. The authors reported that some additional sensor signals were difficult to interpret or use in control algorithms, and that crop-status assessment remained challenging. This was an autonomous-cultivation research trial in one specific system, not a survey proving that every commercial greenhouse uses every sensor.

Dissolved oxygen, leaf temperature, chlorophyll fluorescence, individual nutrient ions and detailed microbial testing can be valuable in research or specialised production. They are not standard purchases for a houseplant grower. For example, measuring dissolved oxygen in a recirculating reservoir may answer a precise technical question; it cannot establish the oxygen status inside every pot. Root health, drainage, reservoir temperature and aeration are usually more accessible first checks.

Professional greenhouse work also illustrates why water and nutrient readings are interpreted together with crop performance rather than in isolation. Fine adjustments have little value if the underlying problem has been misidentified. The transferable lesson is disciplined observation, not recreating a commercial control room at home.

A practical monitoring plan for three growing systems

The useful routine depends strongly on how the roots receive water and nutrients. The following is a starting framework rather than a universal schedule.

For a small hydroponic reservoir, daily or near-daily checks may be justified because water level and solution chemistry can change rapidly. A healthy plant in a buffered growing mix usually needs much less chemical monitoring. A measured value is useful only when its meaning, sampling method and appropriate action are understood.

Change one controllable factor, then check again

Consider a container plant that stays wet longer than expected and develops slower new growth. Begin with the visible evidence: record its water input, drying pattern, temperature and light conditions; check whether the pot drains and whether roots show damage. These observations may suggest several possible explanations. They do not by themselves prove which is responsible.

If there is no urgent disease or safety issue and drainage is adequate, choose one justified change to investigate, for example, modifying the watering interval while keeping the medium, light and feeding programme as consistent as possible. Record the date and the intended effect. Continue comparing the same indicators at similar times. Then ask whether the measured condition changed, whether new growth subsequently changed and whether temperature, season or plant development might explain part of the difference.

A before-and-after observation in one plant can guide a practical decision, but it does not prove causation. Oregon State University’s 2023 experimental-design guide explains why a comparison group, replication and random assignment strengthen inference. In a 2024 sensor-guided irrigation study by Dong and colleagues, tomato plots received approximately 30% less irrigation water with the sensor-based schedule, while marketable tomato number and weight were not statistically different from the existing grower schedule. Those results came from a specific field comparison with four replications and eight plants per replication; they show that a better management outcome need not appear as increased yield and cannot be generalised into an expected saving for every grower. A non-significant yield difference is not proof that the two methods are equivalent.

Changing one factor is a useful investigative rule, not an excuse to ignore serious deterioration. Suspected spreading disease, failing irrigation, dangerously hot equipment or severe root damage may require prompt action on more than one front. Document the intervention and acknowledge that its individual effects may then be impossible to separate.

Keep a small measurement log

A notebook or simple spreadsheet is sufficient. Record the date, plant identifier, development stage, the question, the measurement with unit and sample location, and what was changed. Add follow-up observations using the same method. Empty fields are preferable to measurements taken without a purpose.

It is often more useful to track a small number of consistent measurements than to collect many disconnected values. Start with what you can observe reliably, add instruments when they answer a question, and judge any change against the plant’s response as well as the meter readings.

References

• Both, A. J., Benjamin, L., Franklin, J., Holroyd, G., Incoll, L. D., Lefsrud, M. G., & Pitkin, G. (2015). Guidelines for measuring and reporting environmental parameters for experiments in greenhouses. Plant Methods, 11, 43. https://doi.org/10.1186/s13007-015-0083-5
• Dong, Y., Werling, B., Cao, Z., & Li, G. (2024). Implementation of an in-field IoT system for precision irrigation management. Frontiers in Water, 6, 1353597. https://doi.org/10.3389/frwa.2024.1353597
• Maree, S. C., Zhang, P., van Marrewijk, B. M., de Zwart, F., Bijlaard, M., & Hemming, S. (2025). Autonomous Greenhouse Cultivation of Dwarf Tomato: Performance Evaluation of Intelligent Algorithms for Multiple-Sensor Feedback. Sensors, 25(14), 4321. https://doi.org/10.3390/s25144321
• Tanner, C., Jones, G. B., & Verhoeven, B. (2023). Experimenting on the Farm: Introduction to Experimental Design. Oregon State University Extension. Publication EM 9381.
• Pennisi, B. V., & Thomas, P. A. (2022). Diagnostics System for Crop History and Disorders in Greenhouses and Nurseries. University of Georgia Extension. Bulletin 1273.
• Ebba, J. (2023). Hydroponics at Home. University of New Hampshire Extension. https://extension.unh.edu/resource/hydroponics-home.
• Papworth, H., & Tea, B. (NIAB / AHDB). How to Monitor Nutrient Management in Glasshouse Crops. https://archive.ahdb.org.uk/knowledge-library/how-to-monitor-nutrient-management-in-glasshouse-crops.