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Measuring crop growth

Measuring tape/Graduated pole

Crop height is measured at every visit. Measuring tape or graduated pole is used depending on the crop species and the developmental stage. For example, certain sorghum species in West Africa can grow up to 6 m at maturity stage. At this stage it may be necessary to use a graduated pole. On the other hand, a measuring tape can be used at the early developmental stage or for crops such as rice or cotton.


Figure 6.3. Left: measuring tape (source: Right: graduated rod for measuring crop height (source: STARS ISABELA team)

Plant height is recorded by holding the pole close to the stem of the crop. The height should be measured from the ground level or from the collar (point on the stem where roots start to grow), to the leave base of the highest fully expanded leaf. For cotton and peanuts, only the main stem is considered. For cereals, after ear/panicle emergence (just before the start of the reproductive stage), plant height corresponds to the height of the highest panicle (at the basis of the panicle), instead of the height of the highest fully expanded leaf. Plant height should be recorded until full flowering, when plant height no longer changes.

AccuPAR LP 80 Ceptometer

The AccuPAR LP-80 (Decagon Devices Inc.) is a portable sensor for deriving leaf area index (LAI) of plant or forest canopy (Francone et al., 2014; Mathews and Jensen, 2013). The device measures canopy photo-synthetically active radiation (PAR) interception and calculates leaf area index (LAI) non-destructively at any location within the canopy (see here). The device has an external sensor which enables simultaneous above and below canopy PAR measurements. Usage of the external sensor together with the AccuPAR produces accurate PAR and LAI data in a variety of sky conditions (e.g., clear, partly cloudy or overcast).

PAR represents the acceptable wavelength range of solar radiation (400 to 700 nanometres) that photosynthetic organisms are able to use in the process of photosynthesis. PAR can, thus, be considered as the amount of light available for photosynthesis. PAR is lowest at night and peaks at mid-day. Since a very dense canopy will absorb more light than one which is sparse, a relationship between light interception and LAI can be assumed (note that leaves are the medium through which light is attenuated). The calculation of LAI from PAR is based on this relationship.


Figure 6.4. Left: an AccuPAR device (source: Right: use of the AccuPAR device on a millet field in Mali (source: STARS ISABELA team).

Within the STARS project, LAI measurements using the AccuPAR were carried out in selected quadrats (see Figure 6.4). For each selected quadrat, 3 measurements are taken with the sensor orientation perpendicular to the rows at the centre of the quadrat and two at about 75 cm from its borders in different rows. Each measurement is stored in the AccuPAR data logger and records:

  • incoming radiation from the external sensor
  • light interception fraction for 5 separate segments on the AccuPAR stick
  • estimated LAI for 5 separate segments on the AccuPAR stick.

This estimated LAI is sensitive to the amount of diffuse light received by the sensor (e.g. under cloud cover) and differs per crop type. Therefore, to derive more robust LAI estimates, separate calibration lines needs to be developed to convert these light interception measures.
More details about the use of the AccuPAR for LAI measurements can be found here.

Smartphone Pocket LAI

The PocketLAI is a smartphone app developed for measuring LAI in a simple and less cumbersome manner (Confalonieri et al., 2014). In terms of cost, the use of PocketLAI is less expensive compared to AccuPAR, although it may give less robust and less consistent readings.

The app is based on the implementation of a simplified model for light transmittance into the canopy, based on the estimation of the gap fraction (i.e., fraction of sky seen from below the canopy) (Confalonieri et al., 2014). Images below the canopy are acquired by the smartphone camera and the accelerometer at a view angle of 57.5° while the user is rotating the device along its main axes. This configuration allows acquiring information independently from leaf angle distribution and less affected by the clumping effect in case of row crops (Weiss et al., 2004; Baret et al., 2010).

  • Figure 6.5. PocketLAI graphical user interface: home screen (a), setting options (b), specifying the name of the measure (c), measuring mode (d). (Source: Confalonieri et al., 2014) Figure 6.5. PocketLAI graphical user interface: home screen (a), setting options (b), specifying the name of the measure (c), measuring mode (d). (Source: Confalonieri et al., 2014)

Experiences obtained in the use of PocketLAI in the STARS project are:

  1. Accuracy of readings degrades in cloudy sky conditions
  2. Sometimes Mobile App crashes in high temperature. The app must be restarted if it crashes several times
  3. It is difficult to make the proper angle for the second vibration in PocketLAI app. After the first vibration, it is advisable to wait for two seconds when the smartphone is in a vertical position.
  4. Due to some technical difficulties sometimes this app does not give LAI value at the first instance.
  5. The app must be kept updated in order to receive new features

Figure 6.6. Measuring leaf area index with the Pocket LAI software installed on a smartphone (source: STARS CIMMYT team).

Figure 6.7: Comparison of leaf area index (LAI) measured with a SunScan canopy analysis system  and the Pocket LAI. Data were measured for a maize crop in 2015 (source: STARS CIMMYT team).

More details about the PocketLAI can be found here, while a useful video tutorial can be found here.

 SPAD 502 Plus Chlorophyll Meter (Spectrum® Technologies Inc.)

This device is used to measure the amount of chlorophyll content in a plant leaf. Chlorophyll content is indicative of the level of greenness of a plant leaf (Francone et al., 2014; Shang et al., 2015). Measuring and monitoring this in different parts of a field over time may reveal variations in plant conditions (e.g. plant stress) across a FMU.

Chlorophyll content is recorded with the SPAD 502 plus by simply clamping the meter over leafy tissue. The device returns an indexed chlorophyll content reading (-9.9 to 199.9) in less than 2 seconds (figure 6.8).

Figure 6.8. Demonstration of how the SPAD 502 was used in the field to measure chlorophyll content (source: STARS ISABELA team)

The measurement of chlorophyll content is performed together with the plant height. A number of plants (e.g. 5) should be selected within each quadrat and consistently measured/monitored throughout the season. The very same number of leaves needs to be measured on all selected plants in each quadrat to enable comparisons between quadrats. In case of plant disease/plant death, a new replacement plant should be identified close to the centre of the quadrat.

SPAD readings could vary according to sampling position on a single leaf. Therefore, it is advisable to take three recordings per leaf: one towards the base of the leaf, one in the centre of leaf (in between nerves), and one towards the tip of the leaf. Moreover, within a plant, a clear vertical profile in chlorophyll content may exist. This vertical variation profile is affected by nutrient availability. Therefore, you may also collect chlorophyll content to characterize this profile across 3 leaves per plant, as follows:

  1. the oldest, but not yet deceased leaf (lowest leaf not yet dried up)
  2. a leaf in the middle of the plant (mid-height)
  3. the newest fully expanded leaf (on top of the plant)

SPAD values are recorded as an average value per leaf. This should be recorded on an electronic (e.g. smartphone) or hardcopy form. Make sure that the corresponding plot number, quadrat number etc. are recorded as well. For each leaf measured, the leaf number on the plant, counting from the bottom up should also be recorded on the form.

More information about the device, including manuals and other literature can be found here.

Digital camera

A digital camera can be used in numerous ways to derive information on canopy developmental stages during the cropping season.

First, a digital camera is traditionally used to take pictures of a field during each field visit. In this case, the camera is held in a horizontal position prior to picture taking. These pictures (acquired on different dates) can be visually analysed to gain knowledge of crop growth and status as well as any evidence of stress.

Another use of a digital camera is to take vertical pictures of a field in order to estimate crop ground cover or fCover. Ground cover is the percentage of soil surface covered by plant material. Measuring and monitoring crop ground cover can assist in reducing the susceptibility of soils to erosion. It is also an important parameter in irrigation scheduling. 

Vertical pictures are taken by mounting a digital camera on an L-shaped pole to  approximate a nadir view from above the crop canopy (Figure 6.9). The length of the pole depends on type of crops being surveyed.

Figure 6.9. Left: camera mounted on an L-shaped pole. Right: demonstration of how fcover is measured with the camera mounted on an L-shaped pole (source: STARS ISABELA team)

Pictures of the crop canopy from above (i.e. downwards) are recorded by holding the pole in a near-vertical position. If measurements are being made in quadrats, then pictures should be taken in a systematic sequence (e.g. clockwise direction). As much as possible, pictures that are taken should have no shadows in the picture area. Vertical colour photographs of the crops (top-down view) have to be taken over the same area throughout the growing season. An additional picture should be taken in case the previous one fails (e.g. due to blurred image, misalignment, etc.). If measurements are being done in quadrats, then the image number/name per quadrat should be recorded for tracking purposes.

Vertical images that are taken are analysed by image processing software to derive ground cover measures. CAN-EYE, a freeware, is a popular application for processing vertical pictures into ground cover measures. Details about this application can be found here.

IR-712 Infrared Thermometer

Canopy temperature was measured in the field using a handheld IR-712 Infrared Thermometer (radiometer). When pointing the thermometer at the plant, it is important to ensure that there is soil surface visible in the background as the soil typically has a much higher temperature than the plant surface, introducing a bias to the measurement. In cases of sparse vegetation cover the thermometer has to be held close to the leave surface at an oblique angle, so that the field of view of the radiometer is entirely covered by leaves. Data measured temperature was read from the display of the thermometer and entered into an electronic field data collection form installed on an Android tablet.

Figure 6.10. Comparison of canopy temperature measured with a heat gun on the ground vs data acquired with a thermal camera mounted on a UAV, measured from 65 m above ground at a ground sampling distance of 0.2 m (source: STARS CIMMYT team).

Weather stations

Weather stations record meteorological variables that are important for planning (i.e. when to plant) and agricultural management. They also feed into UAV flight planning and biophysical models (e.g. crop water requirement). Synoptic (automatic) weather stations measure a comprehensive set of variables such as temperature, relative humidity, wind speed, total incoming solar radiation and rainfall in a study region. Data loggers are often attached to synoptic stations, which automatically record data with no need for manual recording. However, these may be too expensive for smallholder farmers who may want to monitor key meteorological variables in their region.

In rainfed agricultural areas, and in fact in most regions dominated by smallholder farmers, rainfall is often the most important meteorological variable. In such cases, a simple rain gauge, which measures only rainfall, can be installed in a farmer’s field for monitoring (Figure 6.11). These devices basically require manual reading and recording.


Figure 6.11. Left: example of an automatic weather station. Right: installed rain gauge in a farmer’s field (source: STARS ISABELA team)

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