6.2.2. Measuring crop growth

Measuring tape/Graduated pole

Crop height is measured at every visit. Depending on the crop and its development stage, one uses either a measuring tape or graduated pole. For example, certain sorghum species in West Africa mature to up to 6 m height. At such stage, a graduated pole may be needed. Earlier in the plant development, or for low crops such as rice and cotton, a measuring tape is more appropriate.

Figure 6.3. Left: measuring tape (source: www.bunnings.co.nz). Right: graduated rod for measuring crop height (source: ISABELA)
 

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 (that point on the stem where roots start to grow), to the leave base of the highest fully expanded leaf. For cotton and peanut, the main stem is measured only. For cereals, after ear/panicle emergence (so just before the start of the reproductive stage), plant height corresponds to the height of the highest panicle (measured at its basis), instead of the height of the highest fully expanded leaf. Plant height should be recorded until full flowering, when plants no longer grow in height.

AccuPAR LP 80 Ceptometer

The AccuPAR LP-80 (from Decagon Devices Inc.) is a portable sensor to determine leaf area index (LAI) of plant or forest canopy (Francone et al., 2014; Mathews and Jensen, 2013). The device measures the canopy’s photo-synthetically active radiation (PAR) interception and calculates leaf area index (LAI) non-destructively at any location within the canopy (for details, see here). The device has an external sensor that measures simultaneously above- and below-canopy PAR. The use of the external sensor with the AccuPAR produces accurate PAR and LAI data in a variety of sky conditions.

PAR represents the acceptable wavelength range of solar radiation (400–700 nm) that photosynthetic organisms 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 a sparse one, 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. Top an AccuPAR device (source: http://eolab.es/page/3). Bottom: use of the AccuPAR device in a millet field in Mali (source: ICRISAT).
 

One can choose to carry out LAI measurements using the AccuPAR in selected quadrats only (see Figure 6.4). For each selected quadrat, three measurements are then taken with 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 to be stored in the AccuPAR data logger and records:

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

The estimated LAI is sensitive to the amount of diffuse light received by the sensor (as happens under cloud cover) and this differs per crop type. Therefore, to derive more robust LAI estimates, separate calibration lines need 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 smartphone application was developed to measure LAI in a simple and user-friendly manner (Confalonieri et al., 2014). In terms of cost, the use of PocketLAI is more economical than that of the AccuPAR, but 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 (the fraction of sky seen from below the canopy) (Confalonieri et al., 2014). Images below the canopy are taken with the phone’s camera and with the accelerometer at a view angle of 57.5° while the user is rotating the device along its main axis. This configuration allows acquiring information independently from leaf angle distribution and is 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)
 

Our experiences obtained in the use of PocketLAI can be summarized as follows.

  1. Accuracy of readings degrades in cloudy sky conditions.
  2. Sometimes the app crashes in high temperature. It must then be restarted.
  3. It is difficult to make the proper angle for the second vibration in the app. After the first vibration, the user is advised to wait for two seconds when the smartphone is in a vertical position.
  4. Due to some technical difficulties sometimes this app does not provide a decent LAI value at first.
  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: CIMMYT).
 

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

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 the plant (Francone et al., 2014; Shang et al., 2015). Measuring and monitoring this in different parts of a field over time reveals variation in plant conditions (and may detect plant stress) across an FMU.

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

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

The measurement of chlorophyll content is performed at same time as plant height measurements. A number of plants (think five) is selected within each quadrat and consistently measured/monitored throughout the season. The same number of leaves is measured on all selected plants in each quadrat to enable comparisons between quadrats. In case of plant disease/death, a replacement plant should be identified close to the centre of the quadrat.

SPAD readings may vary with sampling position on the leaf. Therefore, one is advised to take three readings per leaf: one towards its base, one in its centre (in between nerves), and one towards its tip. Within a plant, a clear vertical profile in chlorophyll content may exist. This profile is caused by nutrient availability. Therefore, one may also collect chlorophyll content to characterize this profile across three leaves per plant, as follows:

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

SPAD values are recorded as an average value per leaf. This is done in electronic (e.g. smartphone) or hardcopy form. Corresponding plot number, quadrat number must be explicitly recorded as well. For each leaf measured, the leaf number on the plant, counting from the bottom up should also be recorded.

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 camera is traditionally used to take pictures of a field during each field visit. To that end, it is held in a horizontal position. Such pictures (acquired on different dates) can be visually analysed to understand crop growth and status, as well as any evidence of stress.

Another use of a digital camera is to take downwards looking, vertical pictures of a field to estimate crop ground cover (fCover). Measuring and monitoring crop ground cover assists in reducing the soil susceptibility to erosion. It is also an important parameter in irrigation scheduling. 

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

Figure 6.9. Top: camera mounted on an L-shaped pole. Bottom: demonstration of fCover measurement  (source: ICRISAT)
 

Pictures from above the crop canopy  (i.e. downwards) are recorded by holding the pole in a near-vertical position. If measurements are made in quadrats, then these should follow a systematic sequence (e.g., in clockwise direction). As much as possible, they should have no shadows, and have to be taken over the same area throughout the season. Pictures should be taken in double-up mode, in case one has failed due to incorrect focus, incorrect exposure or image misalignment. If measurements are being done in quadrats, then the image number/name per quadrat should be recorded.

Vertical images are analysed by image processing software to derive ground cover measures. CAN-EYE, a free software package, is a popular application to derive from the pictures ground cover measures. Details about this application can be found here.

IR-712 Infrared Thermometer

Canopy temperature can be measured in the field using a handheld IR-712 Infrared Thermometer (radiometer). When pointing it at the plant, soil surface should remain visible in the background as the soil typically has a much higher temperature, and this may introduce bias in the measurement. With sparse vegetation cover the thermometer has to be held close to the leave surface at an oblique angle, so that leaves entirely cover the field of view of the radiometer. Measured temperature is read from the thermometer display and entered into an electronic field data collection form.

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: CIMMYT).
 

Weather stations

Weather stations record meteorological variables important for planning (i.e. when to plant) and pther agricultural management activities. They also feed into UAV flight planning and biophysical models (such as crop water requirements). Synoptic (automatic) weather stations measure a comprehensive set of variables: temperature, relative humidity, wind speed, total incoming solar radiation and rainfall. Data loggers are often attached to such stations, and automatically record the data. They may be too expensive for smallholder farmers that want to monitor key meteorological variables in their region.

In rainfed agricultural areas, and in fact in most regions where smallholder farming takes place, rainfall is often the most important meteorological variable. A simple rain gauge, which measures only rainfall, can then be installed in a field (Figure 6.11). These devices require manual reading and recording.

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: CIMMYT).