A primer on data-driven growing and technologies for optimal crop production in the greenhouse

This neobook is designed to provide the technical training and tools to greenhouse growers. The book is written for growers ... by a collective group of plant scientists, physicists, technologists, and growers.

Why do we call it a neobook?

What is #datadriven growing?

Growing plants can be a complex task often described as a work of art. What we mean by this, is that we all know plants require certain things to grow and thrive, such as light, water, and nutrients, but anyone that grows a plant knows it is not as simple as 1,2,3. This is because the factors plants need to thrive interact with and influence each other. For example, light also has a heating element that affects the temperature, water can affect the temperature by changing the humidity, and so on. What complicated things even more, is that plant growth interacts with the climate; transpiration increases heat and humidity, photosynthesis can affect CO2, and so on. In order for growers to be successful, they must know the art of how to balance many different factors to keep their plants happy. Up until now, this art form of growing has relied on years of experience to develop the knowledge-base and intuition required for optimal production.

Data-driven growing is a different form of growing, where growers read the data about their climate factors and plant growth factors, and can tell how these measurements will influence their yield. In #datadriven growing, growers not only react to data points, but are able to predict downstream effects on their crop early on to take action before any negative effects unfold. For example, growers may see the absolute humidity of their greenhouse is high and notice the photosynthetic rate of their plants in one area has decreased, indicating these plants are under some sort of stress, such as a fungal pathogen. These growers could take action to quarantine these plants to prevent fungal pathogens from spreading throughout the greenhouse, all before the physical plant symptoms are visible to the naked eye. Recent technology advancements such as artificial intelligence (AI), internet of things (IoT), and intelligent automation (IA) have begun to revolutionize the field of agriculture, ushering in a new digital age. Many different types of data can be collected within indoor farming facilities to produce a digital image of the climate and current crop conditions using IoT sensors. Growers can now access these data points from anywhere with wifi, even on their phones. Technologies like Koidra’s Krop Manager platform utilize these data points along with AI and the mathematics defining nature to explain how different climate factors influence each other and plant growth. For the first time ever, growers can harness the power of big data in the palm of their hands to monitor and analyze how their current climate status is affecting their crops, and what actions they can take to improve yield and resource use efficiency. No advanced mathematics degree required 😉.

Imagine predicting precisely when and how much water your crops will need in order to maximize growth, minimize water use, and increase profits. Or, being able to predict that turning the temperature down 5 more degrees now instead of 2 degrees 8 hours later will save more energy and keep your plants happier? These are the types of predictions made possible with data-driven growing, based on the data collected from sensors and the math behind the nature of growing plants. This book will cover the topics of plant growth fundamentals and how growers can use new technologies available to improve their controlled environment agriculture production with data-driven growing.

Vegetable crop production is a bio-economic activity: Physically speaking, it  takes place in the field or in a greenhouse where the biological processes of growth and development are under the technical control of the grower. But together with biology and technology, economics is a key driver in these bio-economic systems of vegetable crop production: Eventually, the grower needs to make profit to operate sustainably. To understand the behavior of these systems, we will first look at the major relationships (Figure 1).

Cost vs Revenue

Profit is the difference between revenue and costs. For the company, especially the internal costs matter, but on a higher level, e.g. the level of the society or of an ecosystem, costs related to the use of natural resources like water or emissions of greenhouse gases are equally important. Investments into installations like the greenhouse are fixed costs, whereas expenditures for fertilizers, pesticides or energy are variable costs. The latter are relevant for day-to-day control decisions, whereas fixed costs are more strategically important.

We are looking at a future of renewable energy systems, relying far more on solar and wind than on fossil fuels. However these systems can vary wildly in their hour to hour energy output, in sharp contrast to already established generators. This necessitates the development and creation of large energy storage solutions, like hydroelectric dams and water pump systems. While at the current time energy prices are often cheaper at “off peak hours” [Wikipedia] this could change in a future more dependent on renewable energy. Here, the necessity of energy storage will be the limiting factor, perhaps resulting in cheaper energy during the day and windy hours. The revenue is the product of the (marketable) yield and the price per unit produced, which, in vegetables, depends mostly on quality and season.

Crop yield and price

Biologically, marketable yield is the product of the total plant mass produced and the fraction of plant mass which constitutes the marketable product. This fraction is called the harvest index. During production, plants may not produce as much as they could under the given physical conditions, because, for instance, insects feed on them or fungi reduce their photosynthetic area. The proportion of plant mass protected from getting lost can be considered the protection efficiency which, together with the potential plant mass, determines the total plant mass.

Since light is the energy source of plant growth and usually the main constraint to plant growth, potential plant mass can be described as the product of light intercepted by the plant and light use efficiency. It should be noted however that “more light = more yield” is not an accurate equation.

Prices for vegetables depend on various factors with season and quality of the produce being of foremost importance. We can break down “quality”  into “external quality” and “internal quality”, which are further subdivided into, for example, “look” smell” “taste” and “nutrients” or chemical residues. The various quality and yield traits may be inconsistent with each other. Taste may conflict with yield, external quality with chemical residues. More info about these in the toggle box.

Same with the time of sale. Prices are highest when there is high demand and little supply on the market, e.g. in early spring.. At the same time many products are only pushed to the market at a certain time because they cannot be sold around the year, like large orange pumpkins for Halloween. Also keep in mind that the expectation of high price periods might lead other growers to adopt the same strategy, driving prices down again, which has to be weighted in with the possibly higher production costs.

Protection efficiency

The loss factor characterizes the amount of biomass that is lost by external causes, independent from drought or light. In this category, we talk about plant pathogens and insect damage and further separate the plant protection into preventive (passive) and combative (active).

Active plant protection deals with the direct combat of pathogens, pests and unwanted growth of weeds by directly targeting them. Mechanical plucking, chemical agents and the direct handling of infected plants are necessary to protect the whole greenhouse. Based on the intensity of the detected danger this ranges from the plucking of weeds or the application of poison to the removal of entire plants. Combative measures are effective but come with a price. Due to their nature they can only be used when the threat has already shown itself, when the plants are already infected. Early detection systems like sensors in the greenhouse can help, but they cannot prevent it.

Preventive measures are used to prevent an infection in the first place, but need to be carefully considered. Like all preventive actions they cost money and time, without showing a direct positive effect. It is impossible to tell if a greenhouse was not infected by a pathogen due to the preventive measures or just by random chance. Was the application of preventive actions the cause for healthy plants or an unneeded expense? In models this is the area for risk calculations, statistical models that draw data from environmental conditions, other growers experiences and analytical data of the cultivar to determine the risk of an infection. If these risk calculations, whether done by a AI or the growers experience signal a large potential risk for the crop preventive measures are advised. For more details see this article on risk management [Wikipedia].

Further details can be found in the IPM (Integrated Pest Management) section of this handbook.

Light use efficiency

The potential yield is the product of (photosynthetic) light energy uptake of a crop and its light use efficiency (LUE).  Light use efficiency of a plant canopy is determined by the photosynthetic rates of the individual leaves and the canopy structure, which controls light distribution over the canopy and is characterized by the light extinction coefficient. The photosynthetic rate of a leaf depends on its photosynthetic capacity and the availability of CO2 in the mesophyll. The rate of CO2 transport into the mesophyll depends on stomatal conductance and atmospheric CO2 concentration, which can be controlled by the grower. The photosynthetic capacity is mainly determined by the capacity of the biochemical apparatus, Vcmax, and capacity of the electron transport chain, Jmax.

Plants exchange gases like carbon dioxide, oxygen and water vapor through their stomata with the environment: . Depending on the CO2 concentration in the atmosphere, which can be controlled in the greenhouse by enrichment from gas tanks or heaters. The stomatal conductance is controlled by light, the CO2 content and the water vapor pressure of the atmosphere, and plant water status

CO2

Plants breath CO2 through their stomata, which allow the gas exchange. Depending on the CO2 in the atmosphere, which can be controlled by either removing CO2 from the atmosphere or adding more from gas tanks. The stomatal conductance depends on the need for the plant to breath and control its water relations, since the stomata are both needed for the gas exchange and the evaporation of water to disperse heat. More information on this can be found in the water relations section. Carbon taken up through the stomata is metabolized via photosynthesis to store the intercepted light energy in the form of sugar, which is used as a fuel for the metabolism to create proteins. The rate of carbon per energy unit of light is described as the assimilation rate.

Assimilation rate

The assimilation rate describes the rate at which carbon from the air is taken up into the plant and used in the metabolism. Photosynthesis is responsible for this, breaking up CO2 to access the carbon inside, metabolizing it into sugar. Oxygen is a byproduct of this reaction, which incidentally allowed the development of higher life on earth. Looking back into history we can roughly pinpoint the time at which photosynthesis developed in cyanobacteria, which came along with a mass extinction of all species that were unable to adapt to this sudden rise in oxygen in the atmosphere. For more information please look at the “great oxidation event” [Wikipedia].

The biochemical reactions that allow photosynthesis to happen in detail, its dependency on nutrient supply, Vmax (the maximum rate of carboxylation) and temperature are too complex to break down here in detail. In short, the photosynthesis apparatus works better at higher temperature, but like all enzymes and proteins it has a maximum temperature after which it starts to break down, or denature. For the photosynthesis enzymes the “optimal” temperature lays around 20°C, with higher temperatures slowly decreasing its effects. Above 40°C the enzymes start to break down quickly. For more information on the effects of temperature on crop photosynthesis please read this article by Moore et al (2021) “The effect of increasing temperature on crop photosynthesis: from enzymes to ecosystems.

In our growth models and harvest predictions we are often separating the yield into two parts, on one side the pure biochemical machinery that, roughly speaking, turns light energy into biomass in “sources”, and the plant development where this biomass is send into various “sinks”. Over the course of the plant development the focus of the “source/sink” ratio is changing. One of the best examples for this are the so-called “early” and “late” variety of various vegetables like cabbage.

Early varieties shift from leaf and root development to fruit development early, resulting in a quick harvest of small yet already developed fruits. Late varieties go the other way, focusing on large leaf and root development first before they begin to produce very large fruits. Depending on what the market demands the choice of the appropriate variety if important. Local markets prefer early fruits of manageable size while larger commercial buyers prefer large fruits for their higher yield.

The canopy density, meaning how tightly the plants are placed together, also plays into this calculation. Early plants are grown closer to another since they will not expand in size as much as late plants. These need to be separated either during the growth or from the beginning so that enlarging leaves and fruits don’t compete for space and light. Of course a higher canopy density increases the yield per area, but only as long as the negative effects of competition can be compensated. Additional lighting or intercanopy lighting are common ways to increase the supply of light in densely packed plants.

Light interception

Plants regulate their leaf positions and leaf angles [Wikipedia] depending on the time of day (Circadian cycle/nastic movement), the light intensity (sun avoidance), the position of the sun (heliotropism), water relations in the soil and plant (drought response), impact and touch, heat/cold and the shading by other plants, structures or even itself (shade avoidance).

The three main driving patterns of this leaf movement are the Circadian cycle, the Heliotropism mechanisms and the shade avoidance:

When sunlight is intercepted by a leaf not all wavelengths are absorbed by the chlorophyll complex. If that were the case, leaves would be black and not green. Instead the so called “green gap” [Second.wiki] in the visible light and those wavelengths “above” red (far red from 710 to 850 nm) are passing through the leaf undisturbed. As such the ratio of red to far red below a leaf is very different than above, with the far red ratio increased.

The phytochrome complexes are capable of detecting this ratio and can send the signal of shade down the response ladder, activating the elongation response. In dense canopies this effect can lead to stem and leaf elongation where plants are spending more energy on growing upwards faster, decreasing fruit development [Greenhouse product news].

The self shading of plants is partly prevented by the plants of leaf shape and position on the stem. This orientation is called phyllotaxis [Wikipedia].

Fixed targets, variables and control parameters

In our binary system we can only really influence the parameters that are not controlled by other parameters. The actual price on the market for example is not ours to control, we can only set the price when we sell our product on the market. As such we are left with the following parameters that we can “control”: Ecological costs, Social costs, Fixed costs, Variable costs, Harvest index, Quality, Time of harvest/sale, Loss factor, CO2 atmosphere, Water, Temperature, Light, Nutrients and, despite not mentioned in the diagram so far, the Substrate.

We further divide these into the fixed “targets”, variables and control parameters. To explain:

Substrate in this setup is treated as a storage for water and nutrients, the details of root growth are ignored for the moment but could be included later.

And only now are we slowly approaching the actual parameters that we can directly control in the greenhouse, the ones where the plant growth is concerned. Pests and diseases take away energy and need to be cured or prevented, assuming the cost of the cure is not higher than the loss of crop. Constant checkups and preventive measures are costly as well after all. If the risk of an infection is higher at higher temperatures, but higher temperatures mean more yield, is this an acceptable trade-off? What about the heating costs? Slowly the network needed to answer the questions “What is my profit” and “How can I maximize profit” is revealing itself. We could go even further into detail, talk about the large variety of pests and loss factors, the calculations between leaf size and leaf area index, the physical and chemical reactions that convert the light on the leaves into energy, how this energy is distributed through the plant and which stages in a plants life are the most influenceable to steer towards certain goals. The light interception for example is determined through the light in the greenhouse or field, in combination with the size and orientation of the leaves. The light use efficiency is determined through the photosynthesis, which in turn depends on water relations, which depend on transpiration and temperature, which can be controlled by heating, which influences the price for the greenhouse and so on and on.

For example, imagine a grower wants to change the nutrient setup due to high costs of the nutrient mix (Nutrients → Fixed costs). An AI could point this out, if it were to be tasked with reducing the fixed costs. The nutrient mix used is tagged with multiple stats, such as the costs for its use, its effect on the assimilation rate and the fruit quality, but also the ecological costs. Changing the nutrient mix to a different one changes these tags, with new costs for usage, effect on quality and ecological costs. With these new fixed effects the AI can recalculate the control parameters, determining new optimal light, temperature and water controls. All of which come again with new tags for fixed price, quality, assimilation rate and ecological costs.

This is the power of AI. The ability to build a network that calculates all these parameters in real time, using data from a central network and direct data from the growers. But in order to function one question has to be answered first:

What exactly are you looking to produce? And how are you planning to produce, grow, market, store, transport, sustain, defend, protect, harvest, sell, use and plant it?

Section: GIGO

What do a space probe crashing into mars and a computer pausing Tetris have in common? GIGO. In 1999 Nasa tried to send the “Mars Climate Orbiter” on a stable course around Mars. However, when the probe, far away from earth, was calculating the optimal height around mars a system failure approached. The company that had developed one piece of the ground software had set it to operate in feet and inches. Nasa uses metrics. As such the internal computer accepted the data, was unable to check the correct unit, and calculated a path that steered the probe straight into mars [Wikipedia].

In 2013 an AI system was developed to play a variety of old Nintendo games, learning based on its final score. Actions that caused a rise in points were rewarded, actions that lost points were “punished” and failing a game was seen as a large point reduction. And the best summary of what failed is perhaps the game “Tetris”, in which the ai learned to stack the blocks as fast as possible and then pause the game right before it lost. Since the game never stopped it had never lost. (The first level of Super Mario Bros. is easy with lexicographic orderings and time travel… after that it gets a little tricky. [Murphy, 2013])

What can we learn from these amusing stories? Well, amusing to use at least, Nasa was probably not laughing quite as much. We can learn to check our data and check our model. The binary model above shows how we can define the different parameters used to describe the plant growth operation and if one of these parameters is not brought into the plan then the system will ignore it. An optimization program is a tool to let you know which constraints you forgot. And an AI is a very fast optimization program [Hofstätter, 2021]. If a system is set to increase profit but the cost of water is ignored then an AI will use this, increasing water use to near infinity simple because it “knows” that plants grow better when they have more water. Same for nutrients. When we ignore the damage of excessive light the AI will increase light intensity simply because it “knows” that plants grow better when they get more energy. When we don’t tell the AI what we harvest from a plant then the ai will ignore it. When we don’t include pests and infections into the model the AI will be unable to calculate these, instead for example reading the damages as results of heat. If we don’t calculate the social and ecological costs then AI will ignore them, pushing the maximum amount of cost on it.

The cost of perfection is infinite

But we can at least come close to it by making sure we precisely know what we are looking for when we declare our goal for plant growth. What do we grow, at what time, for what purpose, for which market, at what cost. And in order to feed these data points into the system we split each parameter into two more, creating the binary tree.

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Photosynthesis

The photosynthesis process evolved 450 million years ago. With this process, plants convert carbon dioxide and water into carbohydrates using light energy. Carbohydrates synthesized in the photosynthesis process will be distributed to all plant organs to fuel their activities. The photosynthesis process can be described as a chemical equation:

$H_{2}O$ is absorbed via root, and the gases $CO_{2}$ and $O_{2}$ enter and leave the plant through tiny pores in the leaf called stomata.

Photosynthesis occurs within a special cell compartment called the chloroplast. When light is intercepted by leaves, individual photons (particles of light) are absorbed by a pigment called chlorophyll (also responsible for the green color in leaves). Chlorophyll is stashed in membranous sacs called thylakoids. Stacks of thylakoids fuse to form single units called grana. Thylakoids and grana are filled with lumen, and the chloroplast is filled with stroma (see figure below).

Photosynthesis can be divided into light-dependent and light-independent processes. The light-dependent process occurs within the thylakoid membrane and requires a steady photon stream. In this process, photons transfer energy to chlorophyll, and light energy is converted into chemical energy in the form of the molecules ATP and NADPH. The light-independent process (the Calvin Cycle) occurs in the stroma and does not require light. During this process, energy from the ATP and NADPH molecules is used to assemble carbohydrate molecules, like glucose, from carbon dioxide.

Transpiration is an important process within plants that occurs when water vapor leaves the plant through leaf stomata. The exit of water molecules through transpiration is responsible for the plant’s ability to pull water from its growth media up through its roots. Water’s cohesive property is responsible for this, since water molecules like to stick together; as molecules begin to evaporate through the stomata, the remaining molecules inside the plant’s vascular system are pulled upwards. This pull occurs all the way down the plant from the leaf to the root, where the plant can then pull more water up through its roots (see figure below).

Transpiration allows for the constant flow of water required by plants to perform photosynthesis and other growth processes, as well as providing turgor within the stems for the plant to stand upright and not wilt. Transpiration has a cooling effect on the plant in a similar way that sweating has on humans- heat held by water molecules leaves the plant as the molecules evaporate. Plant’s rate of transpiration can be modeled using mathematical equations, and used in data-driven growing as a growth factor.

In this section, we will explain how the crop responds to each environmental factor such as light, temperature, carbon dioxide, humidity, etc. However, it’s critical to note that crops do not respond to these factors in a mono-factorial way or in any linear fashion.

Crops require light in order to carry out photosynthesis, produce carbohydrates, and increase biomass (grow!). Plants absorb light through their leaves, and therefore the more or bigger leaves in their canopy the more light they can absorb. As the amount of light absorbed by a plant increases, the photosynthetic rate also increases to a certain point as long as other nutrients are not limited. Heat as the result of light or photosynthesis is released from the plant through transpiration.

Too much light, either in length or power, can have negative effects on plant health. Plants can experience sun damage in the form of chlorosis- a yellowing of the leaf surface where the chlorophyll is lost. Chlorosis is not only caused by too much light, but can also be a sign of nutrient deficiencies and some diseases. Another way plants can protect themselves from too much light is the buildup of anthocyanins- deep purple or red molecules that act as a physical barrier to light.

Since plants require light to grow, if a light source is placed on one side of a plant, then that plant may grow in the direction of the light. This phenomenon is called phototropism.

Light can be supplied by natural sunlight or by artificial light sources.

Temperature is one of the most influencing factors on the growth and development of plants besides light, CO$_2$, humidity, and nutrient. The optimal temperature varies depending on plant species and the stages of growth and development. In the vegetative stage, when the plant is young, temperature plays an important role in building biomass. It was shown in the study of Heuvelink that the young tomato at 24°C has significantly higher biomass compared to 18°C. The reason is that at a higher temperature, plants develop more leaves and hence gain more light interception and grow faster. In the generative stage, the photosynthesis process is not so sensitive the day/night temperature regime. However, the fruit set is more vulnerable and show a remarkable reduction in the number of fruit at a high temperature stress (Suguru Sato et al.). On the other hand, too low temperature can have unwanted effects such as smaller fruit, mis-shapen fruits (A. Tiwari et al.) Besides the average temperature, the difference in temperature between day and night (DIF) is also important. Usually temperature is higher during daytime, if temperature is higher during nighttime we have an inversed DIF. An inversed DIF results in a reduction of both plant growth and development but the reduction of plant growth due to inversed DIF is more obvious. To control temperature in a greenhouse, we use greenhouse facilities such as ventilation, fogging system, thermal screen, and heating system. When it is too warm inside greenhouse, ventialtion is the most effective and cheapest way to discharge energy by exchanging hot air inside greenhouse with cooler air outside. Fogging system should be used just in case the greenhouse air is dryer than expected. When it is too cold inside greenhouse, we can deploy energy screen and/or turn on heating system. During nighttime, it is suggested to close energy screen and turn on heating at the same time for energy saving. However, during daytime when the amount of PAR enters greenhouse matter we need to be more thoughfull about wheter close energy screen or not. Usually it is suggested to close energy screen during daytime on cloudy and cold days.

CO$_2$ enrichment

As described in chapter 1.2 the CO$_2$ concentration of the ambient air plays an important role for photosynthesis. In the end of the 80s an air concentration of around 330 vpm was typical. Nowadays concentration reaches ca. 0.04 % (400 vpm) (Wikipedia, 2022, Carbon dioxide in Earth's atmosphere). In a greenhouse the CO$_2$ concentration decreases during daytime due to the CO$_2$ uptake of the plants by photosynthesis. So, under non-ventilated conditions values can drop below 200 vpm and this results in a reduction of mass production. The moment the vents open the incoming fresh air offsets this effect. At night there is an increase of CO$_2$ concentration caused by the dissimilation of the plants. But we are only talking about an increase of around 100-150 vpm.

Fig. xx shows the increase in the production of greenhouse crops with increasing CO$_2$ concentration (µmol mol-1 equivalent to vpm). It has to be noted that the slope decreases with increasing CO$_2$ concentration. So, it always has to be calculated if an additional increase of CO$_2$ is economical.

In practice farmers increase the values to around 800 vpm CO$_2$. Some farmers even go up to 1000 vpm even under the situation of open vents. For cucumber for example this should result in the effect that all fruits on the main stem develop to a harvestable fruit size. Normally some of the fruits on the main stem dieback due to the fact that there are not enough assimilates to feed all the developing fruits. There are several ways to enrich the greenhouse air with CO$_2$:

Important remarks: For all methods using combustion of gas it has to be remarked that the combustion produces NOx, CO, phytotoxic ethylene (C$_2$H$_4$) and hydrocarbons. So, the injection of exhaust fumes should be stopped if CO concentration in the fumes is too high. For all methods (also the use of technical CO$_2$) the enrichment should be stopped by using a setpoint of ca. 1200 vpm. Warning sensors have to be placed in the greenhouse to protect the workers from too high concentrations of CO$_2$ (the maximum workplace concentration of CO$_2$ is 5000 vpm).

One of the control parameters in plant production is the water supply by irrigation or fertigation (Figure $$). These measures have an influence on the water content in the substrate and subsequently on the water content in the plant. As control mechanisms of action, decisions about the frequency and the amount of water/nutrient solution given per application have to be made.To avoid high losses of CO$_2$ the application should be stopped if high wind speeds occur. Here the losses depend mainly on the tightness of the greenhouse construction. Additionally, a stop makes sense if the temperature in the greenhouse is near to the ventilation temperature (e.g. stopping enrichment if temperature reaches 4°C below ventilation setpoint) and if the radiation is too low to reach an effective use of the CO$_2$ in the photosynthesis. So, the beginning and the end of enrichment can be controlled by e.g. using sunset and sunrise time (e.g. starting 1 h before sunrise and stopping 1 h before sunset) or absolute minimum radiation values.

The relative humidity (RH) of the greenhouse air influences the transpiration rate of plants. High RH of the greenhouse air causes less water to transpire from the plants, which causes less transport of nutrients from roots to leaves and less cooling of the leaf surfaces. High humidities can also cause disease problems in some cases. For example, high relative humidity encourages the growth of botrytis and mildew.

One of the control parameters in plant production is the water supply by irrigation (Figure $$). The irrigation has an influence on the water content in the substrate and subsequently on the water content in the plant. As control mechanisms of action, decisions about the amount of water given per application and the frequency of the irrigation measures have to be made.

1.1 Leaf Expansion Rate and Stomatal conductance affected by water supply

In the water usage cascade of a production system from water in the substrate to leaf transpiration, the physiological important parameters water influences are leaf expansion rate (LER) and stomatal conductance (gs) (Figure $$). LER is determining plant leaf area and gs is one of the determinants for the CO$_2$ influx into the leaf, both having a decisively impact on photosynthesis.

1.1.1 Leaf expansion rate

In the phase of leaf growth, we have to distinguish between cell division and cell expansion. In plant organs cell division is only active for a relatively short period, it is finalized long before the organ reaches its final size by the process of expansion. For cells to expand the pressure in the cells is important. This pressure is called turgor and depends on the water status of the plant. A low turgor caused by restricted water supply decreases the turgor and decreases cell expansion. As a result the leaf organ will be of a smaller area. An ample supply of water is a prerequisite for high plant leaf area increasing the light interception of the plant canopy.

1.1.2 Stomatal conductance

The leaf lamina of plants is equipped with stomata. These stomata function as a bridge between the plant tissue and the ambient air environment. Water is transpired via the stomata to the environment (for the function of transpiration see 1.2.2). Prerequisite for this transpiration is a sufficient water potential in the leaf lamina so that the stomata of the leaves keep open to allow the water to evaporate and leave the stomata pore as water vapor. Physically this control function is expressed as stomatal conductance or as inverse stomatal resistance. As rule of thumb around 95 % of the transpiration is realized through the stomata, around 5 % via the leaf cuticula (Taiz and Zeiger 2006). To keep up a high water potential in the leaf and consequently a high stomatal conductance again an ample water supply plays the decisive role. But why is a high stomatal conductance so important?

1.2 The role of stomatal regulation for photosynthesis

In the chapter above the role of the stomata was more focused on transpiration and energy balance. There is a third and maybe even more important function of stomata: the gas exchange.

For photosynthesis plants have to take up CO$_2$ into their tissue. The CO$_2$ enters the plant via the stomata. Because the opening of the stomata depends on the water situation in the plant, there is a clear link to the stomatal conductance. Besides the opening of the stomata also the concentration gradient of CO$_2$ between the outside air and the air inside the stomata plays an important role. As we know the ambient CO$_2$ concentration is rising due to climate change. At the moment it is ca. 0.04 % (400 vpm) (Wikipedia, 2022, Carbon dioxide in Earth's atmosphere). To increase the gradient and consequently increase the rate of CO$_2$ influx, the grower can increase the ambient CO$_2$ concentration in the greenhouse by adding CO$_2$ via technical gas or by burning fuel using fired heaters. The desired setpoint for this increase depends on a lot of parameters, but values of 800 vpm CO$_2$ are not unusual. Of course, this supply only makes sense during daytime when the photosynthetic apparatus is active. The intensity of photosynthesis controls the decline of CO$_2$ in the stomata, leading to a gradient of CO$_2$ between inside and outside of the leaf. In the end this concentration gradient and the stomata opening width determine the CO$_2$ supply for photosynthesis.

It has to be mentioned that the CO$_2$ concentration itself has an effect on the stomata opening. A decreasing CO$_2$ concentration in the stomata results in an opening reaction of the stomata. Evolutionarily it makes a lot of sense to keep stomata open under lower CO$_2$ concentration to enable as much photosynthesis as possible under this condition. Within limits this CO$_2$ effect even counteracts the closing reaction by decreasing water potential.

1.3 Transpiration

Plants are exposed to energy incidence by light and ambient temperature. This results in increasing temperatures of the plant surface. As long as this increase has positive effects regarding the biochemical processes of the plant metabolism this is a benefit for plant growth. To avoid excessive plant surface temperature plants are able to transpire, meaning they use the physical process of evaporative cooling. The evaporation of water is energy demanding. The evaporation of 1 g of water needs the energy of 2.26 kJ (Wikipedia, Enthalpy of vaporization). This energy is taken from the surrounding air or tissue leading to a decrease of their temperature. So how does this work in plants?

The extent of the transpiration depends, besides the plant’s internal water situation, on the following climatic conditions:

High temperature and high solar radiation warm up the leaf lamina. Increasing leaf lamina temperature increases evaporation in the stomatal pore and consequently transpiration. The other driving force is VPD in the air boundary layer near the lamina surface. In the stomata pore the VPD is assumed to be zero (the air is saturated with water vapor, 100 % relative humidity). A higher VPD (meaning drier air) outside the leaf results in a higher transpiration rate. The transpiration itself subsequently decreases the VPD in the boundary layer of the leaf and therefore has a decreasing feedback loop on the transpiration rate. Now the role of the wind speed comes into effect: A high wind speed leads to a faster exchange of the boundary layer air volume. So, the air with the lower VPD is replaced by surrounding air which is in most cases drier. This air exchange has a positive effect on transpiration. The difference of VPD between inside and outside leaf increases faster with higher wind speed resulting in a higher transpiration rate.

Transpiration has been modeled by several authors. A comprehensive review can be found in Katsoulas and Stanghellini (2019).

1.4 Water in the substrate

As stated above plant production needs water. Plant tissue consists of dry matter produced by photosynthesis using air CO$_2$ and water and by water itself. Both sum up to the fresh weight of a plant. But which water sources are used for this tissue production? Are there also losses in the production system? And taking the ecological footprint of plant production into account, how can we produce plants of the desired quality in a water efficient manner? The agricultural sector accounts for around 70 % of the global freshwater withdrawal (World Bank 2022). The availability of water in an acceptable quality for plant production for a reasonable price will decrease more and more due to higher use for industry and a higher municipal demand. Additionally, in some areas natural water resources are getting scarce due to climate change.

In greenhouse production many substrates are used. Crops can be planted directly in the natural soil of the greenhouse area or outside this soil. In the latter case inert substrates like e.g. rockwool or organic materials like e.g., peat, composts, coconut fibres, wood fibres, are used. One of the important characteristics of these materials is the water holding capacity (WHC). The WHC determines the amount of water which can be stored in the substrate and thereby determines the amount of water which can be given per dressing without inducing leaching and possible water loss. To avoid the need of intensive monitoring, reduce the number necessary irrigation actions and still assure an ample supply of water for the crop, substrates with high WHC are preferred.

Water loss in a substrate occurs, besides the uptake by the roots, by drainage and evaporation. In a greenhouse drainage happens if the substrate is supplied with a water amount which exceeds the WHC. In general, this can be avoided by a correct irrigation control. Sometimes drainage is done on purpose to leach high salt concentration from the substrate. A drainage must not be a loss of water if the irrigation system is constructed as closed system in which the drainage water is recirculated. Evaporation is a real loss and should be avoided or at least reduced by measures like covering or even wrapping the substrate using foils.

The transpiration of the plant and the evaporation of the soil sum up to the so called evapotranspiration.

As stated above, plant production needs water. Plant tissue consists of dry matter produced by photosynthesis using air CO$_2$, ingested nutrients and water itself. All sum up to the fresh weight of a plant. But which water sources are used for this tissue production? Are there also losses in the production system? And taking the ecological footprint of plant production into account, how can we produce plants of the desired quality in a water efficient manner? The agricultural sector accounts for around 70 % of the global freshwater withdrawal (World Bank 2022). The availability of water in an acceptable quality for plant production for a reasonable price will decrease more and more due to higher use for industry and a higher municipal demand. Additionally, in some areas natural water resources are getting scarce due to climate change.

In greenhouse production many substrates are used. Crops can be planted directly in the natural soil of the greenhouse area or outside this soil. In the latter case inert substrates like e.g. rockwool or organic materials like e.g. peat, composts, coconut fibers and wood fibers are used. One of the important characteristics of these materials is the water holding capacity (WHC, see Figure xx). The WHC determines the amount of water which can be stored in the substrate and thereby determines the amount of water which can be given per dressing without inducing leaching and possible water loss. To avoid the need of intensive monitoring, reduce the number necessary irrigation actions and still assure an ample supply of water for the crop, substrates with high WHC are preferred.

Figure xx: Water holding capacity by soil type. Source: New Mexico State University Climate Center (http://weather.nmsu.edu/models/irrsch/soiltype.html). Found on: https://www.specmeters.com/assets/1/7/water_holding_capacity_chart.pdf

Water loss in a substrate occurs, besides the uptake by the roots, by drainage and evaporation. In a greenhouse drainage happens if the substrate is supplied with a water amount which exceeds the WHC. In general, this can be avoided by a correct irrigation control. Sometimes drainage is done on purpose to leach high salt concentration from the substrate. A drainage must not be a loss of water if the irrigation system is constructed as a closed system in which the drainage water is collected and recirculated. Evaporation is a real loss and should be avoided or at least reduced by measures like covering or even wrapping the substrate using foils.

The transpiration of the plant and the evaporation of the soil sum up to the so-called evapotranspiration.

1.5 Water uptake by roots

The water uptake by roots follows the potential gradient between the water potential in the substrate and the water potential in the roots. Water always flows from the higher to the lower potential. Be aware that the water potentials in both elements are negative. To suck water from the substrate, the roots need a more negative water potential than the substrate. This leads to the effect that not the whole water volume of the soil can be taken up by plants. Herbaceous plants have water potentials from around -0.2 to -1 MPa, trees and bushes down to -2.5 MPa and plants in arid regions can reach -10 MPa.A substrate which is filled with water (including the pores) has a water potential of 0 MPa.

There are two important statutory thresholds of substrate water status: water holding capacity and permanent wilting point. Plants can access the amount of water between these two substrate conditions. How much water this is depends on the physical substrate properties as the distribution of substrate particle sizes and proportion and size of pores in the substrate. Looking from the side of the root also the intensity of rooting (expressed as root length density) and the root age determines the volume of water available for the plant. Concerning the root age there is the fact that older roots are more ineffective in taking up water. The highest uptake rate can be found in young growing roots and there especially in the root apex.

1.6 Irrigation & Fertigation

Plants need water to keep up their tissue turgor as well as to transport nutrients, assimilates, phytohormones and other organic or inorganic substances through their vessels. Water is also necessary for numerous chemical reactions in the plant. So, in addition to an adequate above ground environment, it is important to supply sufficient water to the substrate so that the plants don't experience any deficiency. Sounds easy, but in practice a lot of parameters have to be taken into account to decide when, how much and how to irrigate. It even becomes more difficult if by irrigation also nutrients should be applied. The latter is called fertigation (see chapter ‘Fertigation’).

1.6.1 When to irrigate?

Plant indication

It would be easy to start irrigation the moment that deficiency symptoms like beginning wilting of leaves start to be visible. But this is much too late. What could be other symptoms a plant shows on the way to drought stress? A first sign is the increase of leaf temperature due to the beginning closure of the stomata followed by lower transpiration cooling. This is difficult to measure because there are often much bigger short-term changes in leaf temperature due to varying radiation by e.g. changing clouds. Another indication is the decreasing water transport in the vessels. There are systems available to measure the ‘speed’ of the water column in the stem, but they are very sensible in the application. The transport rate also depends on other factors like changing radiation, leading to the fact that to derive existing stress is not trivial. Additionally only one or some few plants of the whole crop are measured. These facts show that the plant itself is a complicated indicator to derive daily irrigation measures.

Substrate indication

For a farmer there are two soil conditions which should be avoided. One is the so-called waterlogging. In this situation there is the danger of root damage by a too low concentration of oxygen in the root environment. Crops differ in their sensitivity against waterlogging. The opposite situation is a too low water content of the substrate so that the roots are only able to take up an suboptimal water amount from the substrate. So, the water content has to be in the range between these extremes. How can we measure and evaluate the substrate water condition? A good indicator is the percentage of the water holding capacity (WHC, %). The WHC defines how much water the substrate can hold against gravity in % of its volume. For a soil this is called field capacity (FC). Due to their different physical properties different substrates have different WHC values (s. Table $$). For production a substrate with a high WHC is positive because the irrigation frequency can be reduced. There is no fixed value for the WHC to be sufficient for unrestricted water uptake of the plant, because due to the physical properties of the substrate the water potential of the substrate by a given WHC is different (s. Table $$, to be added). As herbaceous plants have a water potential of -0.2 MPa to -1.0 MPa the water potential of the substrate should not be more negative to avoid drought stress. Remember from above the value of -1.5 MPa as the permanent wilting point (PWP).

Be aware of the fact that the WHC of a substrate can change during production due to compaction and by root growth. The substrate gets more dense, so the WHC decreases (Fig. xx, to be added).

As instruments for measuring the water situation in the substrate mainly the following tools are available: tensiometer (measuring the matric potential in Pa), TDR or FDR sensors (time domain reflectometry/frequency domain reflectometry, measuring the volumetric water content of a soil in Vol. %). For the latter data about the relation between the volumetric water content and the matric potential of the specific substrate is necessary.

To be added: photos of tensiometers and TDR/FDR sensors

1.6.2 How much to irrigate?

If no uncontrolled irrigation is possible (e.g. rain in open field production) it might be assumed that it is optimal to irrigate to full WHC. But to avoid a too low oxygen concentration, the substrate is normally only filled up to 90-95 % of the WHC. Otherwise there would also be the danger of producing drainage causing water and nutrient losses. In an open field there should always be a buffer for a possible rainfall event.

If the production system is constructed as a closed system (means that excessive water is sampled and reused), then it is possible to give more than 100% of the WHC. One advantage is that if some single drippers release less than expected, every plant gets sufficient water. The second advantage is that high salt concentrations in the slabs by fertigation can be flushed out (see also chapter ‘fertigation’).

1.6.3 How to irrigate?

1.6.4 Fertigation and fertilization

Organic farmers are not allowed to work with mineral fertilizers in the fertigation solution. So they work with a combination of base fertilization direct on the soil by organic fertilizers as e.g. horn shavings, horn meal, pig bristle pellets, supplemented by top dressings especially for N via drip fertigation using e.g. sugar beet vinasse. The latter contains N, P, K, Ca, Mg and some micronutrients. Vinasse is a viscous material which is diluted to a certain extent in order not to clog the drippers. A pure supply with vinasse for crops like e.g. cucumber and tomato is not possible. The base fertilization using solid fertilizers onto the soil leads to the need of an additional sprinkle irrigation to wet the whole soil surface with the scattered fertilizer. The drip fertigation moistens only a small area around the dripper. Using only drip lines here would result in undissolved solid fertilizer on the soil surface. The sprinkler irrigation can be mounted on soil level (see Fig. $$) or over the top of the canopy (see Fig. $$).

Fertigation is a composition of the two words ‘fertilization’ and ‘irrigation’. In greenhouse production water is given mostly together with nutrients as a fertigation.

Air boundary layer

The air boundary layer of a leaf is the layer of unstirred air around the leaf surface. The extent of this layer depends on wind speed (thinner layer under higher wind speed) and the leaf size (Taiz and Zeiger 2006).

Evaporation

The transition of liquid water (here water in the soil) to water vapor. Evaporation occurs on the soil surface, especially if the surface is wet. A dry soil surface acts as an isolation barrier against evaporation.

Evapotranspiration

The evapotranspiration is the sum of the evaporation of the substrate and the transpiration by the plant.

Fertigation

Fertigation is a composition of the two words ‘fertilization’ and ‘irrigation’. In greenhouse production water is given mostly together with nutrients as a fertigation.

Field capacity

Field capacity (in substrates called ‘water holding capacity’) is the amount of water per volume (L m-³) or per g of soil (g g-1) which a soil can hold against gravity. It can also be expressed as suction (kPa) at this water content.

Permanent wilting point

The permanent wilting point (PWP) is defined as the minimum water volume in a substrate that the plant needs not to wilt. By convention the PWP is defined at −1.5 MPa of suction pressure. (Wikipedia, 2022, Permanent wilting point)

Leaf expansion rate (LER)

The LER is defined as increase of leaf area per e.g. unit of time (cm² d$^-$$^1$) or temperature sum (cm² °Cd$^-$$^1$)

Root length density

The root length density (m m-3) describes the intensity of rooting in the substrate volume.

A stoma (Wikipedia; Stoma) is a cell structure in leaves of plants which forms a pore. Water evaporates from the leaf mesophyll cells into the air filled pocket of the stoma inside the leaf. From there the vapor is transported to the air outside the leaf. The aperture of the stoma is controlled by guard cells.

Stomatal conductance (mmol m$^-$$^1$ s$^-$$^1$) expresses the net molar flux of CO$_2$ entering or water vapor exiting the stomata of a leaf. Its inverse is called stomatal resistance (s m$^-$$^1$) (Wikipedia, 2022, Stomatal conductance)

Pressure of the cell sap on the cell wall. If the osmotic potential inside the cell is more negative than that of the apoplast, the cell takes up water. The resulting pressure tensions the cell wall. This pressure is intercepted by the elastic tissue pressure.

Vapor-pressure deficit (VPD)

The VPD describes the difference (deficit) between the amount of water vapor in the air under saturated condition and the actual amount of water vapor (Wikipedia; vapor-pressure deficit). The unit is Pascal (Pa). It has to be taken into account that air of higher temperature is able to include a higher amount of water vapor. So the VPD depends on ambient temperature. Water vapor is transported in the air from a lower VPD to a higher VPD.

Water holding capacity

Water holding capacity (in natural soil ‘Field capacity’) is the amount of water per volume (L m-³) or per g of substrate (g g-1) which a substrate can hold against gravity. It can also be expressed as suction (kPa) at this water content.

Water potential

Water transport in plants is described by the water potential concept.

The water potential Ψ (Psi) is defined as the potential energy of water per unit volume relative to pure water in reference conditions. It quantifies the tendency of water to move from one area to another due to osmosis, gravity, mechanical pressure, and matrix effects such as capillary action (caused by surface tension). (Wikipedia; Water potential)

Water always flows from a higher to a lower potential. Unit is Pascal (Pa).

References

Hochmuth G, Hochmuth B (1995).  Challenges for growing tomatoes in warm climates. Greenhouse Tomato Seminar. Montreal, Quebec, Canada. ASHS Press, Alexandria, Virginia pp. 34-36. In: Heuvelink, E. (Ed.) 2005: Tomatoes. CAB International. Wallingford, UK. p 279.

Idso S B, Jackson R D, Pinter Jr. P J, Reginato R J, Hatfield J L (1981). Normalizing the stress-degree-day parameter for environmental variability. Agricultural Meteorology, 24, 45-55.

Katsoulas N, Stanghellini, C (2019). Review: Modelling crop transpiration in greenhouses: different models for different applications. Agronomy 9(7), 392. doi:10.3390/agronomy9070392

Nederhoff E M (1994). Effects of C0%-2% concentration on photosynthesis, transpiration and production of greenhouse fruit vegetable crops. Dissertation. Agricultural University, Wageningen, The Netherlands. p 2.

Taiz L, Zeiger E (2006). Plant Physiology, Fourth Edition. Sinauer Associates, Inc., Sunderland, MA, USA. P. 65. ISBN 0-87893-856-7.

Wikipedia (2022). Different search terms as indicated in the text. https://en.wikipedia.org.

World Bank (2022). Water in Agriculture. https://www.worldbank.org/en/topic/water-in-agriculture#1. Last retrieve 23.02.2022.

Yan H, Huang S, Zhang C, Coenders Gerrits M, Wang G, Zhang J, Zhao B, Acquah S, Wu H, Fu H (2020). Parameterization and application of Stanghellini model for estimating greenhouse cucumber transpiration. Water, 12, 517. doi:10.3390/w12020517.

The indoor greenhouse climate is affected by the outdoor environment and greenhouse design which includes heating, insulation, shading, cooling, CO2 enrichment, humidification, and de-humidification. The scheme below describes energy exchange processes that control the climate inside the greenhouse. For example, processes that rule the canopy temperature are: PAR and NIR radiative heat exchange between canopy and Global radiation, between canopy and lamps; FIR radiative heat exchange between canopy and inter-lamp, between canopy and heating pipe; sensible heat exchange between canopy and greenhouse; and latent heat exchange between canopy and greenhouse air via transpiration.

All vapour fluxes inside greenhouse are depicted in the figure below. The vapour flux from canopy to the greenhouse air $(MV_{CanAir})$ is transpiration. Plant transpiration is the process of water movement through a plant and its evaporation. Up to 95% of the water is lost by transpiration, and only a small amount of water taken by the roots is used for growth and metabolism. Plant transpiration occurs through pores on leaves, which are called stomata. Transpiration rate is influenced by relative humidity, temperature of the greenhouse air, wind, and sunlight. At low relative humidity, high temperature, strong wind, and high sunlight intensity the transpiration rate will be high. In this circumstance, plants need to be provided more water than usual. Usually, greenhouse air receives vapour fluxes from canopy via transpiration, or humidification systems such as pad, fogging or blowing. And there are vapour fluxes from greenhouse air to the top air, screen, and outside air, and mechanical cooling system.

Leafy greens is a term for plant leaves eaten as a vegetable for example Lettuce, Kale, Microgreens, Collard Greens, Spinach, Cabbage, Beet Greens, Watercress, Swiss Chard, Arugula, Endive, Bok Choy, Turnip Greens, Purslane, Radicchio, etc. They are all rich in nutrients and can be eaten raw or cooked.

Lettuce is one of the most popular vegetables, and it has grown more and more all around the world in past decades. According to the shape of the lettuce head and predominant use, lettuce cultivars can be classified into five types:

Much research has been conducted looking into the optimal environment to produce lettuce cultivars, and key environmental values have been well established.

To learn more about lighting and temperature’s effects on different cultivars of lettuce, check out this publication.

Tipburn

Tipburn is primarily caused by the calcium deficiency at the tip of young leaves. This frequently happens to the young inner leaves. The underlying cause is two fold:

How to avoid tipburn

Discoloration other than tipburn

Iron Deficiency

The most common nutrient deficiency in lettuce grown using hydroponics is iron deficiency. This deficiency appears as chlorosis (yellowing) of the leaves around the veins, usually affecting younger leaves first. The underlying cause can be two-fold:

How to avoid iron deficiency:

To learn more about iron deficiency in lettuce, read this article.

The optimal environment for tomato is shown in the figure below.

Light: Tomato requires a daily light integral (DLI) of more than 20 mol/m2/d (this value can increase toward the end of the season) with a maximum photoperiod of 18 hours per day. For tomato growth in the Winter when natural light is limited, supplemental light is necessary for plants to grow normally. The most common supplemental light sources are HPS and LED. Compared to HPS, LED is getting more and more attention due to its high efficiency and long lifetime. Additionally, LED generates less heat compared to HPS making it possible to bring the lamps into the crop canopy for inter-lighting. However, HPS is cheaper to set up and can provide an intense amount of light for plants. The combination of HPS as grow-lighting and LED as inter-lighting was shown to increase the yield of tomatoes by 20% compared with using grow-lighting HPS only (Moerkens et al., 2016). CO2: CO2 is an essential factor for plants to photosynthesize. CO2 enrichment in semi-(close) greenhouses can result in a 10-20% higher yield compared to an open greenhouse. Though the leaf- and truss-appearance rates are not affected by CO2 concentration, the fruit set increases when the CO2 concentration increases. Temperature: The fruit growth period is primarily dependent on temperature. Other factors like light, CO2, humidity, plant density, and nutrient contents have a small effect on the fruit growth period. According to the study of De Koning, 1994, 2000; Adams et al., 2001, the fruit growth period decreases with increasing temperature from 14 to 26°C, and high temperature also promotes fruit ripening. Humidity: The recommended value of vapor pressure deficit (VPD) for tomato is from 0.2 kPa to 1.0 kPa. Too low VPD increases the risk of diseases such as Botrytis. On the other hand, too high VPD reduces the photosynthesis rate due to stomatal closure. Both cases lead to a reduced leaf area and hence reduce fruit growth rate and yield.

What and why is topping? Topping is literally cutting the top of the main stem off of your tomato plants.

There are two great reasons to top your tomato plants. The first reason is when tomato plants are outgrowing your infrastructure, they can snap easily, especially when the wind is strong. Once the plant snaps, it will get damaged and rotting. To control the growth, we need to top them and cut the head off so plants stop growing taller. The other reason is that we want to maximize the chances of setting fruit and fruit production. By removing the heads of plants, they stop encouraging leaf growth and put more energy into flowers and fruits.

When to top? We should top tomato plants around 45 to 60 days before the season ends. That will allow the roots to concentrate as much energy as possible on fruit set and production and make fruits grow as quickly as possible.

How to top? Use a sanitized, washed, and dried pair of shears to cut off the head right behind the top flower cluster of the main stem. After topping, the main stem will not grow any further, and the flower cluster is at the top of this stem. While topping, we also want to remove all suckers because we don't want them to develop individual main stems on their own.

Most of the sections for tomato are also applicable for other vine crops such as cucumber, bell pepper, etc. Here, we only highlight the key differences.

Fruit characteristics

Leaf characteristics

Specific leaf area index (m2 of leaf per mg of dry matter): 3.78e-5

(higher than that of tomato, which is 2.66e-5)

Climate preferences

Topping and pruning

We do not have to top cucumber unless plants are spreading out too much and the end of the season is approaching, you can top off your plants to stop the new growth and let the plant focus on finishing its current fruit. However, for cucumber, we should do pruning once a week during the growing season. Pruning is to avoid vines grow out of control, diseases (such as powdery mildew), poor airflow..

The main idea of Integrated Pest Management (IPM) is using biological control when you can, chemical control when you must. IPM is different in different stages: before planting, early stage of pest, and lesion appears on plant.

Soil health: Soil with sufficient nutrients and moderate porosity ensures the growth of healthy roots. It helps plants grow healthy and resistant to many pests and diseases. In addition, soil sanitation helps eliminate some pathogens available in the soil.

Choice of variety: Choose disease-free and insect-free certified seeds and plants if possible. It is important to start with sturdy plants with healthy roots because diseases and insects in young plants can later cause heavy losses in your greenhouse. Precision sowing: placing seed at a precise spacing and depth, by doing so, each plant has optimum space to grow and develop. Precision sowing also makes week management easier and reduces the risk of pest and disease.

Crop Hygiene: Remove and destroy the infested or diseased plants/seeds so they do not become sources of re-infestation.

Pests and diseases can be early detected by human eyes, traps (sticky trap, pheromone traps), magnifying glasses or special cameras on drones. In the early stage, when the symptoms are still subtle growers can apply mechanical and/or biological managements such as using natural enemies, using trapping techniques and pheromone traps, using plant nutrition, matching IPM and crop, climate management. Application of these methods should be considered in combination with the economic thresholds.

If the IPM in before planting and in the early stage are not well done, the symptoms of pests and diseases will become more serious with time, and when the lesion appears on plants growers will have to apply biopesticides or even chemicals which is usually the last recommended solution because pesticides and chemicals can kill both beneficial insects and pest species. On the other hand, pesticides and chemicals can be harmful to environment and pesticide residues in fruits or vegetables are hazards to users if they are overused.

In this chapter, we focus on improvements that can be added to your existing greenhouse to achieve better productivity. For that reason, we will not discuss technologies that you can't easily adopt, such as greenhouse structure and glazing materials.

Movable screens: There are three types of screens for different purposes to help control the climate inside the greenhouse.

Supplemental lighting is used in greenhouses to increase crop production during time periods with low levels of solar radiation. These time periods usually occur during the winter months, but cloudy summer days can be as dark as some of the darker winter days. Thus, if crop production is on a tight schedule, supplemental lighting may be required year-round. Sometimes, photoperiod lighting is also defined as supplemental lighting. But since the light intensities required are very low, and photoperiod lighting consumes limited amounts of energy, it is not considered in the context of this discussion. Despite the installation and operating costs associated with supplemental lighting systems, growers are discovering the benefits. These systems can help improve crop quality, keep production on schedule and reduce the length of the growing cycle. Thus, growers produce a higher-quality product while keeping their production schedules on target, and they are able to produce more crops per year.

High-intensity discharge lamps, especially high-pressure sodium (HPS) lamps, have been traditionally used for supplemental lighting in commercial greenhouses to increase photosynthesis. High-pressure sodium lamps are the most widely used lamp type because of their relatively high efficacy (conversion of electricity into photosynthetic light) and lifespan of 10,000–12,000 h. However, approximately 70% of the energy consumed by the fixtures is not converted into PAR and, instead, is emitted as radiant heat energy. The surface temperature of HPS lamps can reach as high as 450 C, which requires the separation of lamps from plants (Fisher and Both 2004; Nelson 2012; Spaargaren 2001). Additionally, HPS lamps primarily emit light in the range of 565–700 nm, which is predominately yellow (565–590 nm) and orange (590–625 nm) light. They only emit 5% blue light, which is low compared to solar radiation which contains 18% blue light (Islam et al. 2012).

Light-emitting diodes are a promising supplemental lighting technology for the greenhouse industry as they surpass in many aspects capabilities of commercially available lamps commonly used in horticulture (Morrow, 2008). As described by Bourget (2008), LEDs are robust, solid-state semiconductor devices that can emit narrow-spectrum light to maximize photosynthetic quantum efficiency for specific crop species. In 2008, LEDs were as electrically efficient as fluorescent lamps and slightly less efficient than HPS lamps at converting electrical energy to light (Bourget, 2008). As of 2012, blue and red LEDs are up to 50% and 38% efficient, respectively (Philips Lumileds Lighting Co., 2012). Unlike traditional high-intensity discharge (HID) light sources used in commercial greenhouses today, the relative coolness to the touch of LED photon-emitting surfaces allows them to operate in close proximity to plant tissue without overheating or scorching plants, thereby increasing available PAR at leaf level using less energy. With ongoing improvements in terms of energy efficiency and availability of photosynthesis-driving wavebands, LEDs provide potential solutions to the profitability and sustainability issues that greenhouse growers face.

Research in plant growth chambers and tissue culture laboratories has proven that LEDs are an efficient light source for plant lighting in controlled environments (Hoenecke et al., 1992; Jao and Fang, 2004; Jao et al., 2005; Nhut et al., 2000; Poudel et al., 2008; Schuerger et al., 1997; Shin et al., 2008; Tanaka et al., 1998). However, the potential of LED supplemental lighting for large-scale greenhouse operations continues to be explored. Dueck et al. (2012) compared the effect of different irradiation directions of LEDs and HPS on growth and production of greenhouse-grown tomatoes in The Netherlands. They suggested that a combination of overhead HPS and LEDs is the most promising alternative for their climate, when taking into consideration different production parameters and energy costs (lighting + heating) of using the different systems. Another experiment measured responses of photosynthesis and yield for cucumber (Cucumis sativus) grown under either a combination of LEDs (80% red + 20% blue) within the canopy + overhead HPS or HPS only during a winter production cycle (Trouwborst et al., 2010). They reported no improvement in net crop photosynthesis and fruit production when using LEDs + HPS compared with overhead HPS only but attributed their results to low irradiance (light-limited crops) throughout the experiment, regardless of treatment.

The most efficient HPS and LED fixtures have equal efficiencies, but the initial capital cost per photon delivered from LED fixtures is five to ten times higher than HPS fixtures. The high capital cost means that the five-year cost of LED fixtures is more than double that of HPS fixtures. If widely spaced benches are a necessary part of a production system, LED fixtures can provide precision delivery of photons and our data indicate that they can be a more cost-effective option for supplemental greenhouse lighting.

Manufacturers are working to improve all types of lighting technologies and the cost per photon will likely continue to decrease as new technologies, reduced prices, and improved reliability become available.

The preferred unit for measuring light for plant production is µmol m-2 s-1 (pronounced: “micromol per meter squared per second”). This unit expresses the number of particles (photons or quanta) of light incident on a unit area (m2) per unit of time (second). The portion of the light spectrum the plants use for photosynthesis is called Photosynthetically Active Radiation (PAR, 400-700 nm, nm = nanometer), and it is expressed in the unit of µmol m-2 s-1. Sensors used to measure PAR are called quantum sensors and have carefully designed filters such that no light outside the PAR waveband is measured. Our human eye is able to detect light in a slightly larger waveband of approximately 380-770 nm. To measure light in this waveband, a foot-candle meter (or a lux meter) can be used. But measurements with a foot-candle meter include some light with wavelengths outside the waveband used by plants for photosynthesis. Therefore, using a foot-candle meter introduces a small error when we are only interested in measuring the amount of light available to plants for the process of photosynthesis. For this reason, the use of a foot-candle meter is not recommended when evaluating the light environment for plant production. It is possible to convert a measurement taken with a foot-candle meter into a µmol m-2 s-1 value, but the correct conversion factor depends on the light source and is, in the case of mixed light sources, not always easily determined.

Red photons of light have a wavelength between 600 and 700 nm. One of the most common roles for red light is to participate in the physiological process of photosynthesis. Specifically, many LED arrays emit red wavelengths at 660 nm, which is very close to the absorption peak of chlorophyll (Massa et al. 2008). Thus, red LEDs can be used to efficiently drive photosynthetic activity, resulting in increased biomass and overall plant productivity. However, red light alone is not sufficient for the optimum production and quality of most crops. When exposed to solely red light, many dicotyledonous crops develop extensive hypocotyl elongation (Hoenecke et al. 1992). Additionally, Arabidopsis plants grown under only red light develop abnormal morphological characteristics (Goins et al. 1998). However, both red and blue light (400–500 nm) control stem elongation (Kigel and Cosgrove 1991). Specifically, blue light, when combined at a low irradiance with red light, can prevent excessive elongation of hypocotyls, stems, and petioles and deter other morphological abnormalities observed under solely red wavelengths (Goins et al. 1998; Hoenecke et al. 1992).

Red light is involved in much more than simply photosynthetic activity. Phytochrome is one of the primary families of photoreceptors that absorb red light as well as far-red (700–800 nm) radiation. When exposed to light, phytochromes exist in two interconvertible forms, the red-absorbing (Pr) and far-red-absorbing (Pfr) forms (Smith and Whitelam 1990). The relative proportion of Pfr to the total amount of phytochrome (phytochrome photoequilibrium) regulates a variety of photomorphogenic responses including stem extension (Runkle and Heins 2001; Stutte 2009) and flowering (see Chap. 14). These photomorphogenic responses are known to vary with plant species and cultivar, age, light quantity and quality, and temperature. Plants are generally more compact when exposed to light with a high red-to-far-red ratio (R:FR). They are also more sensitive to red and far-red light at the end of the day (EOD), and 10–60 min of EOD red light may be as effective as a high R:FR during the entire photoperiod to inhibit extension growth (Ilias and Rajapakse 2005).

When installing supplemental lighting systems in greenhouses, several factors should be considered. First, the average amount of solar radiation for the location should be investigated.

This will give an idea of the range of solar radiation conditions at the site. One way to determine the amount of light available for crop production at a particular location in the United States is to consult the database of solar radiation data maintained by the National Renewable Energy Laboratory in Golden, Colo. (www.nrel.gov). This database contains solar radiation data for 239 locations across the United States and its territories. For plant production purposes, the solar radiation data can be converted into the units of mol m-2 d-1, indicating the daily sum (integral) of light available for photosynthesis (1 kWh m-2 d-1 = 7.49 mol m-2 d-1). Second, the type of greenhouse structure, glazing and equipment installed will have an impact on the transmission of sunlight. Third, the type of crop (or crops) grown in the greenhouse will determine the plant’s requirements (such as light intensity, duration or light integral). Fourth, the available space in the greenhouse to hang lamps will have an impact on the uniformity of supplemental lighting (the less space available for taller crops in lower greenhouses, the less uniform the light distribution). Finally, the plant’s requirements should be compared to the available amounts of sunlight to calculate the necessary amounts of supplemental lighting.

It is usually not economical to install lighting systems that provide high light intensities in greenhouses because of the large number of lamps required. Therefore, supplemental lighting systems can be designed to provide a certain light integral during a 24-hour period such that the sum of the supplemental light integral and the solar radiation integral meet the plant’s requirements for even the darkest day of the year. The light integral supplied by the supplemental lighting system depends on the average light intensity provided by the lamps and the duration of operation. The light intensity supplied by commercial supplemental lighting systems usually is not higher than 200 µmol m-2 s-1 (0.72 mol m-2 hr-1 or 17.3 mol m-2 per 24-hour period).

In addition to light intensity, light uniformity is an important factor to consider when designing lighting systems for greenhouses. In general, except when clouds are passing overhead or when structural elements create shading patterns, sunlight is uniform from one location to the next inside a greenhouse. However, due to the distance between lamps and the distance between the lamps and the crop, supplemental lighting systems will always provide non-uniform lighting patterns over a plant canopy. It is the task of the designer to optimize light uniformity by carefully calculating the light distribution from each lamp and the different paths the light can travel from each lamp to the crop underneath. Fortunately, computer software programs exist to assist the designer with this complicated task and in general, a careful design results in very acceptable light distribution and uniformity over a crop canopy.

Greenhouses and indoor farms require constant monitoring and environmental regulation to ensure optimal plant growth. Many factors such as humidity, temperature, light levels, irrigation and more must be constantly kept in check or your plants may suffer. Manually checking these conditions in your growing environment can be time-consuming and tedious. Not to mention the paranoia over whether a door was left open or leaks in irrigation equipment causing a climate catastrophe. Sensors are an excellent tool to help you monitor your growing environment quickly from anywhere and begin automating your indoor growing environment.

There are many different types of sensors available for greenhouses and indoor farms to constantly monitor and measure such variables. Sensors equipped with Internet of Things (IoT) technology are especially capable of transmitting the data collected to a data management system for remote access. For example, instead of manually checking a thermometer, a temperature sensor could be used to automatically collect this data and report it to an online server or data management system. The data can now be accessed remotely instead of having to walk into your greenhouse and check a wall-mounted thermostat.

Sensors can also increase the amount of observations you can make about your greenhouse. For example, temperature sensors can check the micro-climate of every growing zone in your greenhouse. This can be important because although it is optimal for the entire greenhouse to have the same exact temperature, you likely know that is not always the case realistically. Clouds blocking the light over certain sections, uneven drafts from fans and ventilation equipment, and uneven plant crowding as your crop matures can all play a part in offsetting the balance and consistency in your greenhouse climate variables. Realizing such differences, via the data collected by sensors, means that each area can be handled exactly as it needs to be to restore optimal climate for plant growth. This is how sensors are paving the way for precision agriculture.

Not only can sensors monitor your grow environment, but many also include the capability to respond to changes in the environment either automatically or manually. For example, you may set your temperature system to automatically begin heating if your temperature sensors register a lower-than-optimal temperature. On the other hand, you may be able to review your temperature sensor data remotely and make the decision to begin heating based on your observations, likely from a desktop or mobile app. Using sensors to create a “smart greenhouse” can save a lot of time and effort from constant manual climate monitoring, mitigate response time to and losses from unpredictable climate interruptions (i.e. leaving a door open), and collect valuable data about your grow system and how your plants respond to environmental changes.

In this chapter, we focus on the software technology that can unlock your sensor data’s true value, and the basics of data-driven growing. The data collected by your sensors is valuable on its own for the ease of remotely monitoring several growing conditions. However, analysis of this data can do so much more for your greenhouse production, such as improve and increase your yield, reduce your resource usage, and overall increase your profits. The name of this game is data-driven growing: using data in a proactive way to guide your growing. We outline the steps below to achieve data-driven growing, which are data collection and visualization, data analysis, and digital decisions, all of which are taken care of by software technology such as Koidra’s.

The first step to improve your data-driven growing game is having a good data platform. You need to be able to collect and unify your data under one (digital) roof. A large spreadsheet of data points is not useful, we want easy-to-read charts that convey a message. The data needs to be visualized with tools such as operational dashboards, which growers can directly use for crop monitoring and decision making. Figures 2 and 3 provide examples of customizable dashboards with critical growing metrics such as light levels, CO2, temperature and more.

Before investing in a data platform, there are some important questions to ask: Is it another silo in your existing mix of data silos (i.e. isolated, unintegrated data)? Can it be integrated with your existing or new control systems? Can the data be turned into actionable insights? Once you find the data useful, can you operationalize upon that data (i.e. can the control system use it)?

In addition to sensor data, we also recommend manually registering crop measurements on a low-frequency basis (such as day, week).

The decision logic embedded in applications are called digtal decisions. In a nutshell, digital decisions are operational decisions in real-time or near-real-time. They are optimized by

For greenhouse operations, digital decisions are primarily the automated climate control decisions although they may include some other actions in special settings (such as as the decision to move the gutters in a lettuce greenhouse to optimize the plant density in real time). Below is a schematic of a digital decision making system for a greenhouse.

[to be written]

A data silo is a collection of data that is kept in a system that is not easily or openly accessible, sometimes even to those who generated the data. Data silos are unfortunately common in smart greenhouses that use sensors. Oftentimes sensor companies will collect the data and “silo” it into their own private management system, while only giving consumers access to select data points. For example, a temperature sensor may show you the temperature for the last 24 hours, but will not allow you to access the temperatures it recorded last season or even last week.

Another way data can be “siloed” is if data is not kept altogether in a central location. This case occurs commonly in greenhouses or indoor farms that use different types of sensors from multiple companies. One company may store the temperature and humidity data in their silo, but the lighting company stores their data in their own silo. Even when the data is accessible, it is often “spaghetti-ed”, for example in long excel sheets that require massive amounts of scrolling. No simple cut-and-paste could seamlessly combine the data from different silos.

We know the climate and crop variables inside greenhouses interact with and influence each other. Therefore, in order to make any type of data-driven growing decision, growers need access to all of their data in one place.

Digital Horticulture Roadmap

Hannah Gardner

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@Ketut and @Hanh Bui to add your names and some info about you here.