Sander Hogewoning - Insight in Real-time fresh weight production of your crop

Insight in real-time fresh weight production of your crop in opdracht van Bayer / Nunhems

Sander Hogewoning Plant Lighting B.V. 13 June 2018

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Plant Lighting team: 

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Expertise:    

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Dr. ir. Sander Hogewoning, Dr. ir. Govert Trouwborst, ir. Richard Muilwijk & Stefan van den Boogaart

photosynthesis, transpiration and CO2 plant responses to light spectrum light sources (e.g. LED) and signalling light phenotyping

We do research for:   

growers and plant breeders suppliers in horticulture government institutions and grower collectives

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science science practise practise

Insight in real-time fresh weight production of your crop: Why is this important?

• Now planning is based on ‘green fingers’ and simple conversion factors •

e.g. 1 tomato truss requires 40 joules/cm2

• Modern markets increasingly require accurate planning. This becomes ever more important for the economical success of the grower.

• Simply converting the daily light integral to harvest is not good enough, because: • crop photosynthesis becomes increasingly less efficient at high irradiance • CO2 concentrations in a greenhouse vary.

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HortiSense Crop Module • Hortilux initiative to improve light use efficiency in horticulture • Development joint effort Hortilux (product owner) & Plant Lighting (plant physiology and modelling) • Two modules: • Assimilation module • Production module

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HortiSense Crop Module: assimilation module • This module calculates real-time photosynthesis of a greenhouse crop.

• Calculations are based on the following data: • • • • • •

PAR (in greenhouse) Temperature CO2 LAI (= m2 leaf area per m2 greenhouse area) Light distribution through canopy (3D) Photosynthesis characteristics leaves (3D)

• Focus at this moment is on high-wire grown crops

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How to determine the 3D light distribution?

• Model input: PAR measured above canopy + LAI • Model processing: formula fitted to define light extinctions through canopy.

• Fitting based on detailed measurements in greenhouse.

Lichtuitdoving Light extinction throughgewas canopy

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% extinctie

0.8 0.6

% extinctie 0.4

uitdoving januari uitdoving oktober

0.2 0 0

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1

2

LAI

3

4

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How to determine 3D photosynthesis?

• Model input: PAR, CO2, temperature and photosynthesis characteristics per leaf layer • Model processing: Calculation of photosynthesis per leaf layer. Summation of all leaf layers gives the assimilate production (sugars) per m2 crop.

• Photosynthesis characteristics based on detailed measurements in greenhouse.

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Example leaf-layer and crop photosynthesis calculated CO2-opname (µmol/m2/s)

Photosynthesis leaf and crop at stable CO2 concentration CO2-fixation (µmol/m2/s)

65 55 45 35 25 15

Photosynthesis crop Photosynthesis single top leaf layer

5 -5 0

200

400

600

800

1000

1200

1400

1600

1800

Fotosynthese-respons op CO2, Tomaat

38 34 30 26 22 18 14 10 6 2 -2

tomaat top

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PAR (µmol/m2/s)

200

400

600

800

1000 1200 1400

CO2 kas (ppm)

Example photosynthesis in a tomato crop measured in 2017

HortiSense Assimilation Module calculates CO2 fixation of the crop real-time, taking into account real-time fluctuations in light and CO2 in the greenhouse.

Result: instantaneous and cumulative productivity (gram sugars/m2) of the crop.

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What to do with the outcome of the assimilation module?

• Light use efficiency:

• Crop management based on assimilate sum instead of light sum.

assimilatierendement groei

• when to switch off the grow-light due to a too low instantaneous light use efficiency? netto rendement gewasfotosynthese van +1μmol • ‘too low’ depends on cost electricity and licht 100% 90% €/kg harvest.

80% 70% 60% 50% 40% 30% 20% netto rendement gewas per lichtstap

10%

0% 0

• Decision support: • anticipate instead of respond • simulate the effect of an action • e.g. increased CO2 or reduced lighting

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200

400

600

800

PAR (µmol/m2/s)

1000

1200

1400

1600

Light use efficiency for growth initially rises with increasing light. This is because the leaves also produce assimilates for maintenance respiration. Per extra µmol PAR relatively more assimilates are available for growth. At higher PAR the light use efficiency drops again due to the lower photosynthetic efficiency at high light.

The next step: HortiSense Production module •

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Predicts harvest, and therefore also allows growers to anticipate on deviations from the production target: •

lower than target: increase productivity (e.g. more light or CO2), or inform client/ buy elsewhere to deliver to client

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higher than target: reduce productivity & safe costs, or try to sell more…

Accuracy prediction depends on quality of parametrization of the relevant factors. Assimilation is very important, but not the only factor…

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Other factors to make the step from assimilation to production‌ a)

losses produced assimilates:

(e)

• maintenance respiration • growth respiration

b)

conversion efficiency assimilates to dry matter

c)

allocation assimilates to plant organs

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temperature-dependence ripening fruits

e)

temperature-dependence leaf and truss appearance rate

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conversion dry weight to fresh weight

(a)

(d) (c) (b)

(a)

diagram: Marcelis et al. 1998

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(f)

Summarising HortiSense Crop Module allows: • Real-time insight in crop assimilation

• Harvest prediction (improving by additional research & machine learning) • Anticipate instead of respond to crop performance • no more ‘action when you are already too late’

• Decision support for greenhouse management decisions • grow light on/off, CO2,…

• The quality of the model depends largely on the quality of the parametrization (‘crap in=crap out-principle’)

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Contact

Sander Hogewoning 030 75 12 069 info@plantlighting.nl www.plantlighting.nl Plant Lighting BV Veilingweg 46 3981 PC Bunnik (NL)

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