Practical Field Guide Functional Crop Monitoring for Early Stress Detection: Stomatal Conductance and Infrared Thermography as Key Measurement Tools © International Potato Center 2021 ISBN: 978-92-9060-625-3 DOI: 10.4160/9789290606253 CIP publications contribute important development information to the public arena. Readers are encouraged to quote or reproduce material from them in their own publications. As copyright holder CIP requests acknowledgement and a copy of the publication where the citation or material appears. Please send a copy to the Communications Department at the address below. International Potato Center: P. O. Box 1558, Lima 12, Peru cip@cgiar.org • www.cipotato.org Citation: Rinza, J.; Ramírez, D.A.; Ninanya, J. (2021). Practical Field Guide. Functional Crop Monitoring for Early Stress Detection: Stomatal Conductance and Infrared Thermography as Key Measurement Tools. Lima, Peru: International Potato Center. Design and Layout: Communications Department December 2021 CIP also thanks all donors and organizations that globally support its work through their contributions to the CGIAR Trust Fund: www.cgiar.org/funders © 2021. This publication is copyrighted by the International Potato Center (CIP). It is licensed for use under the Creative Commons Attribution 4.0 International License Practical Field Guide 1 Content 1 Introduction ................................................................................................................................................................... 3 2 Ackowledgements ......................................................................................................................................................... 4 3 Measurement of plant cover using digital cameras ....................................................................................................... 5 I. Objectives ................................................................................................................................................................ 5 II. Theoretical foundation ............................................................................................................................................ 5 III. Equipment and materials ........................................................................................................................................ 5 IV. Procedure ................................................................................................................................................................ 5 V. Results and discussions ........................................................................................................................................... 8 VI. Literature ................................................................................................................................................................. 8 4 Evaluation of maximum light saturated stomatal conductance and chlorophyll concentration ................................... 9 I. Objectives ................................................................................................................................................................ 9 II. Theoretical foundation ............................................................................................................................................ 9 III. Equipment and materials ...................................................................................................................................... 11 IV. Procedure .............................................................................................................................................................. 12 V. Results and discussion ........................................................................................................................................... 13 VI. Literature ............................................................................................................................................................... 14 5 Crop water stress index (CWSI) evaluation using thermal imaging and infrared thermometers ................................ 15 I. Objectives .............................................................................................................................................................. 15 II. Theoretical foundation .......................................................................................................................................... 15 III. Equipment and materials ...................................................................................................................................... 16 IV. Procedure .............................................................................................................................................................. 17 V. Result and discussion ............................................................................................................................................. 21 VI. Literature ............................................................................................................................................................... 22 6 Evaluation of gravimetric soil moisture and irrigation time in a plot under drip irrigation ......................................... 23 I. Objectives .............................................................................................................................................................. 23 II. Theoretical foundation .......................................................................................................................................... 23 III. Equipment and materials ...................................................................................................................................... 24 IV. Procedure .............................................................................................................................................................. 25 V. Results and discussion ........................................................................................................................................... 26 VI. Literature ............................................................................................................................................................... 26 2 Practical Field Guide 1 Introduction Determining the right time for crop irrigation is critical to optimizing water use, and being a fundamental part of a management decision support system. It is important to identify the time (when?) when we must irrigate to save water and do not significantly reduce crop yield, as reported in research carried out at the International Potato Center (CIP). This manual has been prepared for use by students, lecturers/faculties, and researchers interested in early identifying crop stress and seeks to provide a set of tools. CIP recently published those tools with funding from the National Program for Agricultural Innovation (PNIA) and the CGIAR Research Program on Roots, Tubers, and Bananas (RTB). Our scopes have been based on the measurement of the maximum light-saturated stomatal conductance, considered the main indicator of plants’ water status, and its relationship with foliage temperature obtained from thermal images processed using open-access software "TIPCIP" (Thermal Image Processor). We can thus compute the crop's water stress index (CWSI), a variable pointing to the degree of crop water stress and the right time for irrigation. This manual provides a handy summary of procedures recently published in international journals that can be applied practically to other crops and foster research on "Water Saving Agriculture" through ecophysiological tools. Practical Field Guide 3 2 Ackowledgements Publication of this guide was made possible through financing granted by the National Program for Agrarian Innovation (PNIA) through its project for “Effective use of water in potato cultivation in arid zones: improving irrigation management by monitoring the water status to face climate change” contract N ° 016-2015-INIA / UPMSI / IE, and the CGIAR Research Program on Roots, Tubers and Bananas (RTB). Contributors: Javier I. Rinza Díaz David A. Ramírez Collantes Johan L. Ninanya Tantavilca 4 Practical Field Guide 3 Measurement of plant cover using digital cameras I. Objectives • Photographing of potato crop using a digital camera • Estimating the crop’s area and foliage cover II. Theoretical foundation Optimizing the capture of light photons for photosynthesis depends on the leaves’ size, inclination angles, and density. Foliage cover is an easily measured variable that relates aerial growth to efficiency in the light interception. Recent digital photography applications facilitate this variable’s temporal and spatial measuring that, when combined with standardized monitoring protocols and image processing techniques, permit rapid sampling yielding ideal quantitative values for crop modeling. CIP’s Image Canopy v.3.6 [1] open-access software, together with a standardized protocol [2], allows quick and easy assessment of foliage cover without requiring rigorous training and offers users a simplified process. This software uses a simple segmentation algorithm based on a vegetation index in the visible region of the electromagnetic spectrum and a threshold value applied to discriminate the green leaf cover from other image elements. III. Equipment and materials • Digital camera with movable screen • Bubble level. • Ruler or tape measure. • Image Canopy v.3.6 software IV. Procedure 4.1. Set the camera to automatic mode considering the following characteristics: a. No focus. b. No flash c. Maximum image resolution d. Use the close-up dial mode ( ). 4.2. Estimate the covered field with the digital camera at different heights, such that it spans the furrow’s width. 4.3. Select the appropriate height above the crop’s foliage (this height can be the average height of the crop). For potatoes, it is advisable to include two plants in each photo. 4.4. Direct the digital camera’s lens towards the plant’s leaf cover, at a pre-determined height (for potatoes, at 0.8 m height) with the camera’s wide side in the direction of the furrows and the narrow side along with the distance between crop plants (see Figure 1). Place the ruler or measuring tape on the first photo as a scale reference. 4.5. Use a bubble level to horizontally position the digital camera. 4.6. Use the previous settings to take a photo of the crop from a known distance. Practical Field Guide 5 4.7. The desirable number of photos should be based on the plant population (6 plants per plot). Photograph at least 15% of all plants as a rule of thumbs. If this is not feasible, the photos to be taken should give an idea of the experiment’s heterogeneity. a) b) Figure 1: Place tape measure (a) and photograph the plans from above (b). 4.8. Transfer the photos from the camera memory to a folder on the laptop. 4.9. Run the Image Canopy v.3.6 software to estimate the area and percentage of foliage coverage. 4.10. Import the folder containing all saved photos (or choose the individual photo option). 4.11. Enter the input parameters (see Figure 2), scale the number of pixels in 10 cm with the first image in the list, and apply the “run software” icon ( ) for final output (Figure 3). 4.12. After computing the area and coverage percentage, the results table shows the software-calculated area. Save the file in csv format using the floppy icon ( ) appearing at the bottom of the screen. 6 Practical Field Guide Button to select by preferred folder Button to select by preferred photo Brightness threshold value (0.05) Number of pixels at the distance selected in ruler Distance selected on ruler (10 cm recommended) Distance between plants in the same row (30 cm) Distance between grooves (90 cm) Number of plants taken per photo (2) Results output directory Figure 2: Main options and input of parameters in Image Canopy software. Figure 3: Input of parameters, photo scale (ruler) and Image Canopy software display window. Practical Field Guide 7 V. Results and discussions Prepare a coverage image (or area) for days after planting (DAP) of each of the plots and discuss results. VI. Literature 1. Production Systems and the Environment (PSE). International Potato Center (CIP). 2013. Protocol for Designing and Conducting Potato Field Experiments for Modeling Purposes.CIP. Lima, Peru. 16 p. http://www.cipotato.org/publications/pdf/006092.pdf 2. Software to estimate the percentage of canopy cover User guide. International potato center (CIP).2017. http://dx.doi.org/10.21223/P3/50TASS 8 Practical Field Guide 4 Evaluation of maximum light saturated stomatal conductance and chlorophyll concentration I. Objectives • Evaluate maximum light saturated stomatal conductance • Evaluate chlorophyll concentration II. Theoretical foundation Although there are several methods to determine the water status of plants, a fundamental basis for determining the ideal time for irrigation, studies carried out by researchers from the University of the Balearic Islands [1,2,3] proposed maximum light-saturated stomatal conductance (gs_max) as the main indicator of this state in plants. The gs_max is determined at mid-morning (when stomatal conductance is maximum) and is acquired by setting the light saturation point of the crop or species to be evaluated. It is important to keep the crops between 0.10 - 0.15 mol H2O m-2 s-1 of gs_max to guarantee the proper functioning of the photosynthetic apparatus and prevent this variable from falling below 0.05 mol H2O m- 2 s-1 where irreversible oxidative damage can occur. These ranges have been proven for potatoes [4] to assure optimal irrigation under different irrigation systems [5]. The recommended time (from 8 to 10 am) to measure this variable is immediately before temperature, and atmospheric humidity environmental conditions intensify, increasing the sensitivity to stomatal closure [6]. The LI-6400 XT portable photosynthesis meter is an open system that bases the measurement of photosynthesis and transpiration on the differential flow of CO2 and H2O vapor. It improves over traditional open systems by integrating gas analyzers in the sensor head, allowing better control of the responses to changes in leaves [7]. Figure 4: Diagram of an open system and the formulas to calculate photosynthesis and transpiration, through differences in CO2 and H2O between the conditions inside the chamber and the conditions prior to entering the chamber (taken from [7]). The formulas to estimate stomatal conductance and net photosynthesis, initially proposed by von Caemmerer & Farquhar [8], are described below: Practical Field Guide 9 • Transpiration rate (E, mol m-2s-1) obtained from the water vapor balance in an open system resulting in the following equation: F(Ws-WE= r) (1) 100S(1000-Ws) Where F is the air flow rate in µmol s-1, Ws and Wr are samples and references respectively of molar fractions of water in mmol H2O (mol air)-1 and S is the leaf area in cm2. • Total water vapor conductance: (gtw, mol H2Om-2s-1) E(1000- Wl+Ws g 2 ) tw= (2) (Wl-Ws) Where Wl is the molar concentration of water vapor inside the leaf in mmol H2O (mol air-1). • Stomatal conductance of water vapor (gs, mol H2Om-2s-1): obtained from total conductance (gtw) eliminating the contribution of the conductance of the boundary layer with the following equation: 1 gs= 1 g - k (3) f tw gbw Where kf is the factor based on the fraction of the stomatal conductance on one side of the leaf, gbw is the conductance of the water vapor boundary layer on one side of the leaf in mol H2Om-2s-1. The saturated light conductance or maximum (gs_max) is obtained by setting 1 500 µmol m-2s-1 of photosynthetically active radiation (PAR) of saturation light for potato crop [5]. • Net photosynthesis (A, µmol CO2m-2s-1) F (Cr − Cs( 1000 − Wr A = 1000 − W )) s (4) 100 S Where Cr and Cs are samples and references respectively of CO2, concentration, F is the air flow rate in µmol s-1, and S is leaf area in cm2. Leaf chlorophyll concentration is one of the rapid measurement traits for tolerance to water stress in potato crops [9]. Plants under stress show smaller leaves and less growth with a high concentration of chlorophylls concerning the leaves of plants in good hydric condition [10]. Equipment such as the portable chlorophyll meter (SPAD-502) allows a rapid evaluation of this variable. However, it is recommended to carry out a previous calibration between conventional chlorophyll extraction methods (such as acetone) and SPAD-502 measurements on leaves with contrasting greenness intensity. 10 Practical Field Guide Figure 5: Chlorophyll concentration is higher in treatments under water stress compared to well-watered plants (taken from [9]). III. Equipment and materials • Portable photosynthesis meter (LI-6400 XT, LI-COR, Nebraska, USA) • Various accessories for the LI-6400 XT (CO2 bottle, desiccant, others) • Chlorophyll concentration meter (SPAD-502, Konica Minolta, Osaka, Japan) CO2 cartridge Console holder Mounting cable Fluorimeter Chamber Sensor Head / (optional) IRGA Figure 6: LI-6400 XT portable photosynthesis measuring device Practical Field Guide 11 IV. Procedure 4.1. The following describes the steps to operate the LI-6400 XT portable photosynthesis meter (more details in manual [7]).  CO2 and moisture filters must be FULL SCRUB.  Connect charged batteries Preliminary  Install a new CO2 cartridge considerations  Adjust the clamps to prevent air from entering the IRGAS chamber (Infrared Gas Analyzer).  Press POWER SWITCH  Select option: FACTORY DEFAULT and press ENTER. If the equipment includes a built-in fluorescence meter, select the LCF option instead of FACTORY DEFAULT Powering up  Connection to IRGAS: press the Y key (yes)  Press F4 (NEW MEASUREMENT)  Relative humidity (RH) must be close to 50%: Press the F key to display RH_R and RH_S  Leave the humidity filter in BYPASS until the desired value is achieved and adjust it gradually until it stabilizes.  Press button 2 and adjust the CO2 cartridge  Press F1 (LEAF FUN) and press key 5 (FAST)  Press F2 (FLOW RATE), press the T (target) key, type: 500umol-1 and press ENTER  Press F3 (MIXER), select REFERENCE CO2  Press F5 (set at 400ppm), press again F5 (KEEP) and press ENTER. Setting  Press F5 (LAMP), select PAR and press again F5 (OK) parameters  Press the T (target) key to set 1 500 µmol m-2s-1 for PAR at desired photosynthesis measuring (light saturation point for UNICA), and press ENTER  Press Key 1 to open a file (record data)  Press F1: OPEN LOG FILE: OPTION FILE (type the name of the file to save data) and again press F5 (SELECT)  Enter the name of the first data item (example: plot 1-floor 1 "P1-1") and then press ENTER  Once PHOTO and COND reach values close to zero, the device is ready.  Select the plants for measuring, excluding those on the edges to avoid possible external impacts (mechanical damage, competition between plants, etc.).  Select a leaflet in good condition, from the third youngest leaf exposed to the sun.  “Bite” the leaflet and check the PHOTO and COND data until they are stable and then press MATCH. Data gathering  When the CO2R µml and CO2S µml values are similar and close to 400 ppm, press EXIT.  Again, check the PHOTO and COND data until they become stable and press LOG.  To record new data, press F4 (ADD REMARK), enter a new name for the next selected plant to be measured, and then ENTER.  Always check RH_R (%) and RH_S (%) values are close to 50%. 12 Practical Field Guide  Press F3 (CLOSE FILE)  Press key 2 to turn off parameters  Press F1, then press the O (OFF) key  Press F2, then press the O (OFF) key and finally, the Y (yes) key  Press F3: then press the O (OFF) key File and  Press F5: press the O (OFF) key computer  Press ESCAPE shutdown  Press F1 (HOME-MENU), select QUIT / OPEN and ENTER  Finally press the Y key (yes)  Press SWITCH (OFF) button  Loosen the clamps and remove the CO2 cartridge  Leave the desiccant loose and remove the batteries (charging batteries is recommended) 4.2. For potato measuring, choose a terminal leaflet located on the third youngest leaf exposed to the sun from a plant located at the plot’s center. For other crops, measure a young leaf exposed to the sun (use the same criteria when evaluating another plant). 4.3. Repeat at least 3 times (plants) per plot. Measurement should not be taken from plants on the plot’s edges which avoids possible external influences (mechanical damage, uneven competition between plants, etc.). 4.4. Next, the chlorophyll concentration is measured in the same plants where gs_max (5 repetitions per plant) was evaluated. V. Results and discussion 5.1. Determine the differences between the average values of gs_max for each plot (control, water stress, etc.). Discuss using the threshold values reported for potato irrigation. 5.2. Discuss the differences in average chlorophyll concentration found for each plot. Tabla 1.-Resultados de la evaluación de la conductancia estomática de luz saturada o máxima (gs_max), fotosíntesis neta (A) y concentración de clorofila (SPAD) por muestra. A gs_max Sample Time SPAD Remarks (µmol CO 2 2m- s-1) (mol H -1 2Om-2s ) 1 2 3 4 Practical Field Guide 13 VI. Literature 1. Medrano, H., Escalona, J.M., Bota, J., Gulías, J., Flexas, J., 2002. Regulation of Photosynthesis of C3 Plants in Response to Progressive Drought: Stomatal Conductance as a Reference Parameter. Ann. Bot. 89, 895–905. 2. Flexas, J., Bota, J., Cifre, J., Mariano Escalona, J., Galmés, J., Gulías, J., Lefi, E.-K., Florinda Martínez- Cañellas, S., Teresa Moreno, M., Ribas-Carbó, M., 2004. Understanding down-regulation of photosynthesis under water stress: future prospects and searching for physiological tools for irrigation management. Ann. Appl Biol. 144, 273–283. 3. Flexas, J., Bota, J., Galmés, J., Medrano, H., Ribas-Carbó, M., 2006. Keeping a positive carbonbalance under adverse conditions: responses of photosynthesis and respiration to water stress. Physiol. Plant. 127, 343–352. 4. Ramírez D.A., Yactayo W, Rens LB, Rolando JL, Palacios S, De Mendiburu F, Mares V, Barreda C, Loayza H, Monneveux H, Zotarelli L, Khan A, Quiroz R (2016) Defining biological thresholds associated to plant water status for monitoring water restriction effects: stomatal conductance and photosynthesis recovery as key indicators in potato. Agric Water Manag 177:369–378. https://doi.org/10.1016/j.agwat.2016.08.028 5. Silva-Díaz, C., Ramírez, D.A., Rodríguez-Delfín, A., De Mendiburu, F., Rinza, J., Ninanya, J., Loayza, H., Quiroz., R., 2020. Unraveling ecophysiological mechanisms in potato under different irrigation methods: A preliminary field evaluation. Agronomy 10(6): 827. https://doi.org/10.3390/agronomy10060827 6. Rinza, J., Ramírez, D.A., García, J., de Mendiburu, F., Yactayo, W., Barreda, C., Velasquez, T., Mejía, A., Quiroz, R., 2019. Infrared Radiometry as a Tool for Early Water Deficit Detection: Insights into Its Use for Establishing Irrigation Calendars for Potatoes Under Humid Conditions. Potato Res. 62(2): 109-122. https://doi.org/10.1007/s11540-018-9400-5 7. LI-COR. (2012). Using the LI-COR 6400/LI-COR6400XT. Lincoln, Nebraska: LI-COR Biosciences Inc. 8. von Caemmerer, S., Farquhar, G.D. ,1981. Some relationships between the biochemistry of photosynthesis and the gas exchange of leaves. Planta 153:376-387 9. Ramírez, D.A., Yactayo, W., Gutiérrez, R., Mares, V., De Mendiburu, F., Posadas, A., Quiroz, R., 2014. Chlorophyll concentration in leaves is an indicator of potato tuber yield in water-shortage conditions. Sci. Hortic. 168, 202–209. https://doi.org/10.1016/j.scienta.2014.01.036 10. Rolando, J.L., Ramírez, D.A., Yactayo, W., Monneveux, P., Quiroz, R. 2015. Leaf greenness as a drought tolerance related trait in potato (Solanum tuberosum L.). Environ. Exp. Bot. 110, 27–35. http://dx.doi.org/10.1016/j.envexpbot.2014.09.006 14 Practical Field Guide 5 Crop water stress index (CWSI) evaluation using thermal imaging and infrared thermometers I. Objectives • Process thermal images taken in the field • Evaluate crop water stress index crop using foliage temperature obtained from the thermal images and by infrared thermometers. II. Theoretical foundation The Crop Water Stress Index (CWSI) is a normalized index under environmental conditions proposed by Idso et al. [1]. This index is based on the radiometric temperature of the foliage (Tf), which is based on the principle of energy conservation at the leaf´s surface or foliage. The radiometric temperature of the foliage is influenced by different factors such as the characteristics of the plants, the environment, and energy sources (see Figure 7). This index ranges from 0 to 1 and indicates the crop’s degree of water stress. In plants under water stress, the stomata close, transpiration decreases, and leaf (foliage) temperature rises. Under these conditions, the index takes values close to one. The CWSI is used as a criterion to determine the time of irrigation in crops of high importance. Our recently published studies concerning potato cultivation [2,3,4] propose CWSI values lower than 0.4 as an optimal irrigation threshold (which allows saving water without significantly reducing yield), with evaluations carried out under clear sky conditions and around 2:00 pm [3]. The CWSI can be calculated using the reference surface methodology applied to potato [2], represented by the following formula: 𝑇𝑇 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 = 𝑓𝑓 − 𝑇𝑇𝑠𝑠ℎ (5) 𝑇𝑇𝑠𝑠 − 𝑇𝑇𝑠𝑠ℎ Where Tf is the foliage temperature, 𝑇𝑇𝑠𝑠ℎ is the reference wet surface temperature (SHR) and 𝑇𝑇𝑠𝑠 is the reference dry surface temperature. 𝑇𝑇𝑓𝑓 can be measured directly using an infrared thermometer or determined from thermal image processing using TIPCIP software [5]. 𝑇𝑇𝑠𝑠 is the temperature of a plant under severe water stress, where transpiration is 0. In environments with high atmospheric humidity, such as the central Peruvian coast, 13° C can be used (in summer, Rinza et al. [3]) or 7 ° C in winter (Cucho-Padin et al. [4]) above air temperature. The use of thermal cameras compares favorably to infrared thermometers, allowing covering a larger crop area. The FLIR thermal camera covers a spectral range of 7.5 - 13µm and additionally features a built-in digital camera. The TIPCIP software [4,5] is an automated image alignment program developed at the International Potato Center (CIP). Through an optimization process, it fixes the thermal image and “moves” the visible image until it finds a similar image (mask) and coordinates of common origin. The aligned image is converted to a binary image with the logical threshold of 1 (black) for foliage and 0 (white) for the rest. The Tf of each image is obtained from the binary image. Practical Field Guide 15 Figure 7: Schematic representation of the main factors to measure foliage temperature (Tf) with a thermal camera (or infrared thermometer). 1: Environment (hot bodies), 2: Plant, 3: Atmosphere and 4: Thermal camera, where Tref is the reflected apparent temperature (determined by a cardboard surface), 𝜺𝜺 is crop emissivity, Ta is air temperature, Tf is foliage temperature and τ is atmospherical transmissivity. (Taken from [6]). III. Equipment and materials • Thermal camera (model E60, FLIR Systems Inc., Wilsonville, USA) • Infrared thermometer (model DT-882, CEM, China) • Cardboard, 1.5 × 1 m2, smooth surface • Reference wet surface (RWS) (5 cm thick expanded polystyrene sheet covered with a 5 mm thick white cloth dipped in a 0.32 × 0.22 × 0.10 m3 plastic tray half filled with water) • Portable automatic weather station (HOBO U12 Outdoor Industrial model, Onset Computer Corporation, Bourne, MA, USA) • TIPCIP software (version v1.3, CIP, 2018) • FLIR Tools Software (Version 6.3, FLIR Systems, 2015) • Step ladder • Laptop or computer 16 Practical Field Guide 1. Shutter button 2. Tripod support 3. Focus ring 4. Infrared lens Figure 8: FLIR thermal camera model E60. Outside view IV. Procedure 4.1. Next, the steps to follow before and during the taking of thermal images and later in their processing are described 1. 4.1.1. Before taking thermal images  Start the portable automatic weather station (PAWS) to record air temperature (Ta), relative humidity (RH), solar radiation (Rs), and wind speed at 5-minute intervals.  Prepare the reference wet surface (RWS). Changing the container water for each evaluation is recommended. Preliminary considerations  Expose the cardboard surface to the sun without contact with the ground, so it absorbs radiation. This will provide the reflected temperature (Tref), a configuration parameter for the thermal camera.  Determine the plot area to be evaluated. The area planted to 6 central plants, or approximately 1 m2, is recommended for potatoes. For this area, keep a distance of 3 m between the thermal camera lens and the cop foliage. Determine the  Take a thermal image of a homogeneous cardboard surface at a distance of 1 m reflected as shown in Figure 9. The value of the reflected temperature (Tref) will appear on temperature the thermal camera’s screen or seen using the FLIR Tool. In this latter case, the emissivity (ε=1) and reflected temperature (Tref =0) must be adjusted. 1 View procedure tutorial at https://www.youtube.com/watch?v=U7jrUiWdvSs Practical Field Guide 17  Turn on the thermal imager ( ) and wait five minutes before using the thermal camera.  Go to main menu (middle button) ˃ settings ˃ measurement parameters. Then set the following parameters: Thermal camera - Emissivity = 0.96 1. LCD touch screen setting - Reflected temperature (Tref) 2. Navigation command - Distance (3m) 3. Image viewing - Relative humidity (from 4.p oLratasebrl ep owinetaetrh er station) 5. Turn on/off - Air temperature (from 6.p oRrteatubrlen weather station) cardboard Figure 9: Determining cardboard reflected temperature. 4.1.2. Taking thermal photos a. Place the reference wet surface at the center of the evaluation area (6 plants). Figure 10: Location of the reference wet Surface. 18 Practical Field Guide b. Stand (with the ladder) against the light source (sun) and at approximately 30º inclination. Figure 11: Taking the thermal image. c. Adjust focus until the thermal image shows the highest possible contrast (Figure 11). d. To take the thermal photo, press the shutter button. In case of strong wind, it is important to wait until it calms. After a few seconds, a touch keyboard will appear on the screen (set the camera to assign a name after shooting). Name the image and save it. NOTE: When many plots will be evaluated (requiring more time for measurement) and/or the significantly varying weather conditions, the thermal camera must be reconfigured to the new values of the measurement parameters. 4.1.3. Thermal image processing  Download the data from the weather station and select data for times of measurement (less than 1 hour recommended).  Transfer the images (thermal and visible) from the memory of the FLIR camera to a computer folder.  Open the FLIR Tools software and view the cardboard thermal image.  Enter the cardboard reflected temperature in an Excel spreadsheet (average of Entering data a rectangular region), the emissivity and the number of the visible image (+1 of the number of the cardboard photo). Repeat for each image on the cardboard if necessary. Example 9990, 0.96, 27.0 for the first cardboard image  Save the data in a comma delimited file in csv format. Practical Field Guide 19  Open the FLIR Tools software to view the thermal image.  Select an area of the wet surface (from an inner rectangle).  In an Excel spreadsheet, enter the average temperature (𝑇𝑇𝑠𝑠ℎ) and the time the Determine the image was taken. temperature of the wet and dry  From the weather station data, select the air temperature data for the same surfaces time when the thermal image was taken.  Calculate the dry surface temperature (𝑇𝑇𝑠𝑠) as 13 °C above the air temperature.  It is also advisable to select the relative humidity, solar radiation, and wind speed data, and calculate the vapor pressure deficit, as they are important analysis variables.  Install and open the TIPCIP v1.3 software. (Figure 13)  Add the images taken in the field by clicking Add image(s). Each image can be selected individually or an entire directory. The images will be loaded in the Input images selected by user box. Process thermal images  Add the .csv file by clicking Add reflected temperature.  Select an output folder for the results by clicking Select output directory.  Finally, with the Generate results option, execute the program. A file in .csv format will appear in the output folder with results for the foliage temperature (𝑇𝑇𝑓𝑓) and the processed images. Figure 12: FLIR Tools v6.3 software interface and data required to create the csv file. 4.2. For potato, measure using an infrared thermometer at leaflet level (third leaf and exposed to the sun), or on a young, exposed leaf for the same plants previously evaluated with the thermal camera (at a distance of approximately 10 cm), under the same conditions for thermal imaging measurements (environmental factors) and CWSI evaluation. 20 Practical Field Guide Figure 13: TIPCIP v1.3 software interface [5]. Figure 14: Procedure to determine foliage temperature from field thermal images (1). Data is acquired for both RGB and infrared (IR) bands (2 and 3). The IR image is filtered to avoid false plant detection (4). RGB and IR images are aligned to determine plant temperature in a specific crop area. V. Result and discussion • Determine if the plots need irrigation (control, water stress, etc.) according to the average CWSI value obtained from the thermal images per plot (complete Table 2, consider 4 photos per plot). Discuss based on the threshold values for irrigation reported for potatoes. • With the average CWSI results obtained with an infrared thermometer, determine if the plots need irrigation. Conduct your discussions regarding the reported threshold values and identified benefits of using this equipment. Practical Field Guide 21 Table 2.- Results of the Crop Water Stress Index (CWSI) for the evaluated plot. Tf Tsh VPD Rs Data Time Ta (°C) CWSI Remarks (°C) (°C) (kPa) (W m-2) 1 2 3 4 Tf = foliage temperature, Tsh = reflected reference wet temperature, Ta = atmospheric temperature. VI. Literature 1. Idso, S.B., Jackson, R.D., Pinter, P.J., Reginato, R.J., Hatfield, J.L., 1981. Normalizing the stress-degree- day parameter for environmental variability. Agric Meteorol 24:45–55. 2. Ramírez, D.A., Yactayo, W., Rens, L.B., Rolando, J.L., Palacios, S., De Mendiburu, F., Mares, V., Barreda, C., Loayza, H., Monneveux, P., Zotarelli, L., Khan, A., Quiroz, R., 2016. Defining biological thresholds associated to plant water status for monitoring water restriction effects: stomatal conductance and photosynthesis recovery as key indicators in potato. Agric. Water Manag 177:369–378. https://doi.org/10.1016/j.agwat.2016.08.028 3. Rinza, J., Ramírez, D.A., García, J., De Mendiburu, F., Yactayo, W., Barreda, C., Velasquez, T., Mejía, A., Quiroz, R., 2019. Infrared Radiometry as a Tool for Early Water Deficit Detection: Insights into Its Use for Establishing Irrigation Calendars for Potatoes Under Humid Conditions. Potato Res. 62, 109-122. https://doi.org/10.1007/s11540-018-9400-5 4. Cucho-Padin, G., Rinza, J., Ninanya, J., Loayza, H., Quiroz., R., Ramírez, D.A., 2020. Development of an open-source thermal image processing software for improving irrigation management in potato crops (Solanum tuberosum L.). Sensors 20, 472. https://www.mdpi.com/1424-8220/20/2/472 5. Cucho, G., Palacios, S., Loayza, H., Rinza, J., Ramírez, D., 2018. Thermal Images Processor (TIPCIP), International Potato Center, V1. https://doi.org/10.21223/P3/8WR5J9 6. FLIR. 2016. User’s manual FLIR Exx series, 178p. 22 Practical Field Guide 6 Evaluation of gravimetric soil moisture and irrigation time in a plot under drip irrigation I. Objectives • Evaluate the gravimetric moisture of the soil • Determine the irrigation time in a drip irrigation plot II. Theoretical foundation Soil physical parameters, including volumetric humidity at field capacity (θcc) and an apparent density (ρ) are fundamental in defining the amount of irrigation water. Estimating these parameters two weeks before sowing is therefore recommended. From 2 lateral profile 1x1.2 m2 pits, previously saturated with water and covered with plastic for 7 days (in sandy loam soils), extract soil samples at a depth of 0 (surface), 0.1, 0.25 and 0.40 m depths, using sample cylinders of known volume. The soil from each sample cylinder must be weighed immediately to obtain the fresh weight and before drying at 105ºC for 72 hours, to bring them to constant weight following the procedure outlined in García [1]. Soil samplings are best carried out in the mornings. Sampleswill be obtained at the crop’s dominant root zone (0 - 0.35 for potato). Soil samples are weighed fresh (Wsh) and subsequently dried in a microwave oven to obtain dry weight (Wss) [2]. The determination of the gravimetric soil moisture (u) is calculated using the following formula: (𝑊𝑊 𝑢𝑢 = 𝑠𝑠ℎ −𝑊𝑊𝑠𝑠𝑠𝑠) 𝑥𝑥100 (6) 𝑊𝑊𝑠𝑠𝑠𝑠 Determine the soil’s volumetric moisture (θ) using the θ = ρ*u relationship; irrigation time (Tr, in minutes) is calculated with the following equation [3]. 𝐴𝐴𝑥𝑥𝐴𝐴𝑥𝑥𝐴𝐴 𝑇𝑇𝑟𝑟 = (𝜃𝜃𝑐𝑐𝑐𝑐 − 𝜃𝜃) 𝑥𝑥1000 (7) 𝑄𝑄𝑠𝑠 Where A is the distance between the drip tapes (0.35 m), Z is the depth of the root system (Figure 15), determined depending on the stage of development of the crop (0 - 0.35 m), θcc and θ is the field volumetric humidity and at plot capacity at the time of sampling, respectively, L is the length of the irrigation tape, and Qs is the irrigation flow per furrow (in L min-1), resulting from multiplying the dripper flow (obtained from pressure uniformity tests) with the number of drippers per row. Practical Field Guide 23 Figure 15: Dimensions of the volume of soil watered per row in the drip irrigation system, with A (0.4 m) x L (10 m) x Z. Where A is the width of the furrow to be irrigated and L is the length of the furrow. Z is the depth of the root system of the crop. III. Equipment and materials • Microwave oven (Model CQ1570, Samsung, Bangkok; Thailand) • Digital scale (Model PAJ3102N, OHAUS, USA) • Punch-type soil sampler (Figure 16a) • Plastic bags • Petri dishes a) b) Figure 16: Punching soil sampler (a); obtaining the soil sample in the field (b). 24 Practical Field Guide IV. Procedure 4.1. Extract 3 composite soil samples per plot with the punch-type soil sampler at the depth of the crop’s root zone of the crop of 0.25 m (See Figure 16b). 4.2. Place composite samples in previously labeled plastic bags. 4.3. Take samples to laboratory to obtain determine fresh sample weight (see Figure 17a). 4.4. Mix each sample in the plastic bag and separate 200 g in previously labeled Petri dishes (see Figure 17b). 4.5. Weigh the wet sample from each Petri dish (record the weight of the Petri dish) and determine Wsh by subtracting Petri dish weight from sample weight. 4.6. Dry in a microwave oven for 25 minutes (wear appropriate gloves). 4.7. Weigh the dry sample and determine Wss by subtracting the weight of the Petri dish from the weight of the entire sample. 4.8. Use Equation 6 to determine gravimetric moisture (u). 4.9. Determine the irrigation run time (Tr) using Equation 7 and the data shown in Table 3 (use a spreadsheet template). 4.10. Determine the irrigation layer. Use the following relationship Lr= (θcc - θ) x Z Table 3.- Main important variables for drip irrigation Apparent density (g cm-3) 1,6* Dripper flow (cm3 cm-3) 31,8* Caudal de gotero (L h-1) 1,56 Number of drippers per row (2 tapes with 0.2m spacing between drippers) 104 *These values were determined for the soil of our experimental station in La Molina - Lima, Peru based on the collection of data in 2 pits established in experimental potato fields [2,3]. a) b) Figure 17: Soil samples labeled in plastic bags (a) and soil samples on Petri dish (b) Practical Field Guide 25 V. Result and discussion • According to the gravimetric humidity of the soil, determine the volume of water needed to bring the soil to field capacity in the drip irrigation plot. Discuss based on the given physical soil parameters. • Apply irrigation in the drip irrigation plot for the determined time. • Determine the irrigation layer (Lr) of the plot to be irrigated. Table 4.- Plot time and drip irrigation layer. Wsh Wss u θ Tr Lr Sample Remarks (g) (g) - (g g 1) (cm3 cm-3) (min) (mm) 1 2 3 4 Wsh = wet weight of soil sample, Wss = dry weight of soil sample, u = gravimetric soil moisture, θ = volumetric soil moisture Tr = irrigation time, Lr = irrigation layer VI. Literature 1. García, J. 1992. Agrometeorología: Energía y Agua en la Agricultura. UNALM, 174p. 2. Silva-Díaz, C.; Ramírez, D.A.; Rodríguez-Delfín, A.; de Mendiburu, F.; Rinza, J.; Ninanya, J.; Loayza, H.; Quiroz, R. Unraveling Ecophysiological Mechanisms in Potatoes under Different Irrigation Methods: A Preliminary Field Evaluation. Agronomy 2020, 10, 827. https://doi.org/10.3390/agronomy10060827 3. Yactayo, W., Ramírez, D. A., Gutiérrez, R., Mares, V., Posadas, A., & Quiroz, R. 2013. Effect of partial root- zone drying irrigation timing on potato tuber yield and water use efficiency. Agric. Water Manag, 123, 65-70. https://doi.org/10.1016/j.agwat.2013.03.009 26 Practical Field Guide Practical Field Guide 27