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- Zeitschrift
- eISSN
- 1178-5608
- Erstveröffentlichung
- 01 Jan 2008
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- 1 Hefte pro Jahr
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- Englisch
Greenhouse structures adapted to new possibilities in the 1960s, when wide sheets of polyethylene film became widely available. Water-related greenhouses became more prevalent in the 1980s and 1990s. Greenhouses connected to gutters are usually covered with a polycarbonate structural material [1, 2] or a double layer of polyethylene film with air blown between the layers to provide increased heating efficiency. Heating inputs have been reduced as the ratio of floor area to exterior wall area has been greatly increased. Water-connected greenhouses are now commonly used both in production and in situations where plants are grown and are also sold to the public [3, 4].
This article is concerned with monitoring the nutrition available for the plant to grow in the best conditions, and with enriching the soil with the most appropriate amounts of these nutrients, most importantly nitrogen, phosphorus, potassium (NPK). The aim is to reach the optimum production level. Other variables have their influence on production, such as improving the surrounding conditions of the crops in greenhouses, also to increase production and reduce cost. These surrounding variables will be adjusted to reach the best conditions for growth and production [5, 6, 7]. Conditions will be read using sensors and transmitted to IoT big data management to read for optimal conditions to plant and cultivate crops. The variables to be considered are breathing (ventilation), atmosphere temperature (heating and cooling), lighting (photosynthesis) and others.
In plants, photosynthesis occurs mainly within the leaves. Since photosynthesis requires carbon dioxide, water, and sunlight, all of these substances must be obtained by or transported to the leaves. Carbon dioxide is obtained through tiny pores in plant leaves called stomata. Oxygen is also released through the stomata [8]. Water and nutrition are obtained by the plant through the roots and delivered to the leaves through vascular plant tissue systems. Sunlight is absorbed by chlorophyll, a green pigment located in plant cell structures called chloroplasts.
If we took this equation as basic to growth in the chosen plants, then we must study each input of this equation and determine what the variables are that affect each input.
Ventilation is one of the most important components of a successful greenhouse. If there is no proper ventilation, the [9, 10] greenhouse and its growing plants can become exposed to severe problems. The main purposes of ventilation are to regulate
The volume of water needed by tomato plants for optimal growth and production varies with the season and size of the plants. Soil moisture can determine how much water should be added, and soil moisture sensors can measure the appropriate amount of water needed. Young seedlings usually need about two fluid ounces (50 ml) per plant per day, while mature plants need two to three quarts (2 L) per day. On average, 90% of the water taken up by [11] the plant is used for transpiration (cooling), and the remaining 10% is used for growth. Inadequate amounts of water lead to wilted plants, and wilted plants are not productive. Prolonged water deficits can lead to permanent wilting, which can result in the death of the growing tips of the plant.
The water should be provided in six to twelve (or more) applications per day, depending on the type of growth medium used. Well-drained media, such as rice hulls, may need more than twelve applications per day. The timing of [12] applications should be determined by the water demand of the plants, with most of the applications occurring during the day. Some nighttime watering may be needed during periods of low humidity. More applications may be needed on sunny days to accommodate the increased rates of transpiration by the plants. Enough water should be applied that some drainage occurs from the growth medium bags (10%–20% of the water applied), and this additional amount of water needs to be added to the total amount of water required.
Light is an essential factor in maintaining plants. The rate of growth and the length of time the plant remains active depends on the amount of light it receives. Light energy is used in photosynthesis, which is the basic metabolic process of a plant. When determining the effect of light on plant growth, there are three areas to consider: intensity, duration, and quality. Light conditions and duration are not included in this research study, as we will make our test in optimum light duration and exclude light variables from this study. The concentration will be on plant nutrition [13, 14].
Increasing the time (duration) that plants are exposed to light can be used to compensate for lower light intensity, as long as the plant's flowering cycle is not sensitive to day length. The increased light duration allows the plant to produce enough food to survive and grow. However, plants require a period of darkness to develop properly and must be exposed to light for no more than 16 hours a day. Too much light is as harmful as too little. When a plant gets too much direct light, the leaves become pallid, sometimes burn, turn brownish, and then die. Therefore, we need to protect the plants from excessive exposure to direct sunlight during the summer months [15, 16, 17].
The most important factor in planting crops is the nutrition of plants. In the next section we will discuss the effect of nutrients on building up chlorophyll [19], the vital input element in photosynthesis. It must be mentioned that there are many chemical subsidizers: most important are the NPK supplements. There are some other chemical elements (e.g., magnesium [Mg], sulfur [S], and calcium [ Ca]) that have their effects on plant growth in all growth stages, from
This section is mostly concerned with the environment [20, 21] (physical surroundings). These elements are important in the process of cultivating tomatoes in greenhouses. As shown in Figure 1, physical conditions can be automated and controlled according to threshold readings of data for each condition. If a threshold is reached, an action will be activated to reduce or increase readings to that most appropriate to the plants. These conditions are:
Figure 1
Smart Greenhouse with ventilation and automated cooling and heating system.
Recommended temperature of tomato greenhouse based on light levels
| Night | 63°F (17°C) | 64°F (18°C) |
| Day | 66°F (19°C) | 70°F (21°C) |
Relative humidity ranges related to temperature in greenhouses
| 60 (16) | 60%–75% |
| 65 (18) | 65%–80% |
| 70 (21) | 70%–80% |
| 75 (24) | 75%–85% |
| 80 (27) | 80%–85% |
| 85 (29) | 85%–90% |
The main idea is to protect plants from extreme cold and frost. But heat can also be deadly; for tomatoes, therefore, it's important to properly manage the temperature and humidity inside the greenhouse [34, 35].
The ideal temperature for a greenhouse is between 80°F to 85°F (26.5°C–29.5°C). You want humidity, but you do not want your humidity to be too high, as high humidity can foster viruses, fungi, and mold.
At 80°F (26.5°C), humidity should be 40%–85%, depending on what plants you are growing. We can determine and control temperature and humidity in [36] a greenhouse using thermometers and humidity sensors. These can be linked to automated systems that adjust the temperature and humidity via fans, windows, humidifiers (and other means which are not our main focus in this article).
Figure 2 defines the best environmental values of temperature and humidity for growing tomato plants. The equation that satisfies this condition is
Figure 2
Relation between temperature and humidity. RH Max, Maximum Relative Humidity; RH Min, Minimum Relative Humidity; Temperature, Absolute temperature degree; RTH, Normal Relative Temperature to Humidity level; TH Max, The Maximum Value of Threshold to Action.
The environmental aspects of plant growing conditions are dealt with by the threshold method with this state.
For example, an event can be reaching a minimum or maximum threshold that will trigger a ventilation fan or opening of the greenhouse walls; other triggers can switch a heater or cooler on or off to raise or reduce temperature.
The main aim of this research to obtain the best harvest of tomatoes [37, 38], which is the most consumed vegetable among the earth's populations. This main goal can be achieved by supervising and controlling conditions around tomato plants and nutrients supplementing tomato plants in greenhouses. We have identified at least six variables that are the main affects for this seedling plant. Half of them are concerned with the surrounding environment and can be controlled as actions responding to threshold triggers; the second half concerns nutrition of the crop. We are mostly interested in NPK nutrition because these nutrients are the most needed [39, 40, 41]. The seventh variable is the
The variables that will be considered are those which have a primary effect on the crop; however other variables also have their impacts on the crop:
The geographic location plays a central role in managing the variables mentioned above [42, 43]. Temperature and humidity in our testing location, for example, are very close to what we needed inside the greenhouse for some seasons of the year. The length of the light (day, night) is mainly responsible for photosynthesis.
Tomato fruits have several stages of growth, starting from seed until collecting ripe fruits. Figure 3 defines the growing stages.
Figure 3
Growing stages of tomato plant last about 100 days.
This research project is based on data reading, supervising, and control of tomato plant growth. In our experiment we will plant one tomato plant in a container. In Figure 4 the dimensions are defined using an inch unit (“). This container will be filled with soil. The whole container filled with soil will be placed on a balance scale and the weight calibrated to zero. Tomato seed will be planted in the soil to start the process. Each day in the morning the weight sensor will send data on the weight of the growing plant: only the plant, with all its contents, such as seeds, leaves, stems, flowers, and fruits.
Figure 4
Testing container dimensions.
The testing area of this research is in Aroub, which located in a suburb of Hebron, a city in Palestine (see Figure 5 for location).
Figure 5
Geographic location where experiment is conducted, Palestine, Hebron district.
This is considered a rich agricultural area that produces all kinds of fruits, especially tomatoes and cucumber. The annual climate condition in this area is given is given in Figure 6.
Figure 6
Annual climate condition of testing area.
As we declared in the introduction to this article [44, 45], there are two parts of supervising and controlling greenhouses. Firstly, the surrounding conditions, which can be managed using given data of sensors on the basis of events – that is, the trigger method. Secondly, management of data concerning nutrition: more precisely, NPK added substances. The surrounding conditions aspect is more simple and straightforward. After testing location climate, we will start planting at 20 April, as this time is ideal for planting tomatoes in that location, as all variable conditions (light, humidity, temperature) are ideal for planting. We will do the planting process in the best light duration for planting tomatoes: at least 8 hours and 9 hours for the fruit formation and mature fruit stages, and no more than 9 hours in vegetative and flowering stages. Daytime ideal humidity levels in a green house range from highs of 90% down to 80%.
The nighttime moisture levels, however, range slightly lower, between 65% and 75%. The least humidity is needed at the fruit formation and mature fruit stages, and the most humidity is required during vegetative and flowering stages. The best temperatures for tomatoes at various stages is as follows: in-earth growing (12–17°C), vegetative (14–17°C), flowering (16–20°C), fruit formation (18–22°C), and mature fruiting (26–30°C). In any case, temperatures should not go above 28°C or below 5°C. The plant will die if temperatures soar above 30°C or drop to less than 0°C. In any case, if the RTH curve hits the upper or lower threshold, it will be a trigger to correct the issue, as mentioned above in the section on surrounding conditions.
Adding nutrition is very important for the plant in all stages mentioned above, from the nursery stage until mature fruiting stage. Basically the nutrients that we will consider in this research are nitrogen, phosphorate, and potassium (NPK), normally, [46, 47, 48], as we have discussed above. We will add to our container the following concentration values to reach better production: N (100–250 mg/kg), P (60–140 mg/kg), and K (60–120 mg/kg). We can control the concentration of these nutrition elements using soil sensors.
The soil nutrient content can be measured using an NPK soil sensor and Arduino of ammonium content. It is necessary to determine how much additional nutrient content should be added to the soil to increase crop production. The soil fertility can be measured using the NPK sensor. The major elements of soil fertilizers are nitrogen, phosphorus, and potassium. By reading values of soil nutrient concentration, we can learn about the nutritional deficiency or sufficiency in soil for plant growing stages. There are many methods for measuring soil nutrient elements, such as optical sensors or spectrometers. But the spectral analytical method of determining the nutrients is only 60% to 70% accurate. While comparing the spectral analysis method with traditional wet chemistry methods, accuracy of the product is yet to be fully resolved. So here we will use an optical sensor to detect nitrogen, phosphorus and potassium in the soil, as shown in Figure 7.
Figure 7
Nitrogen Phosphorus Potassium sensor actual size.
This kind of sensor is low-cost, quick, responsive, high precision, and portable, and it works with network and data transitions module Rs 485, with an output signal which can wirelessly transmit data up to 1200 meters [49]. The advantage of the optical sensor over a traditional detection method is that it gives instant measurements and highly accurate data. All we need is to insert its probes in soil and get the reading using Arduino. Thus, we can easily make our own instrument soil check NPK meter. In our test case we can read the details about the interfacing of soil nutrient sensor or NPK sensor with Arduino and display the NPK data in an OLED display. This soil sensor is suitable for detecting the contents of nitrogen, phosphorus, and potassium in the soil. It helps in determining the fertility of the soil and the sensor can be submerged in soil for a long time. It has a high-quality probe rust resistance, electrolytic resistance, and salt and alkali cover resistance. Therefore, this sensor is most appropriate for all kinds of soil. The sensor has high measurement accuracy, fast response speed, and good interchangeability, and it can be used with any microcontroller [50, 51, 52]. The sensor operates on 9 to 24 volts, and power consumption is very low. The sensor's accuracy is within 2%. The measuring range is from (0–1999) mg/kg. The operating temperature is between 5 to 40 °C. The output signal can be read using a mode for Rs 465 transmitter. The sensor has a predictive layer made using IP Success rating [53]. The sensor we need to make a NPK meter has four wires and works using mode unit 20 Amber converter along with twelve-volt supply.
The system that is shown in Figure 8 has two objectives. The first is to get an instant reading of nutrition concentration in units of mg/kg. This reading will be displayed on an OLED display. The second is to send data, transmitted wirelessly, to a server in a data center, for advanced control and data management to get the best NPK percentages [54, 55] and the most accurate percentage of NPK needed, depending on the growing phases defined in Figure 3. The main objective of big data collected is to control NPK added amounts to increase production of tomato fruits, for more than 90 days, which represents the life cycle. Each day we need to take the measurements of NPK concentration in soil and the weight of the whole plant. We can change the amount of NPK nutrition and see the resulting production, so we will then find the best conditions (values for amount of variables N, P, and K). Then the interface module needs to be connected to the NPK sensor to get the NPK reading. Then we assembled the circuit of the entire system, which can be applied on a breadboard. Apart from the breadboard, we will need any Arduino board, which can be programmable. Similarly, we used an OLED display square where we can display the NPK readings.
Figure 8
IoT system to check and calibrate substants NPK in soil.
This system works to retrieve the data from the RS 485 mode bus from the NPK sensor, which has 3 lines: one line is for getting the nitrogen value in soil. [56] Similarly, the second line is for phosphorus, and the third is for getting the value for potassium. The instruction frame of data consists of the following data sets:
Address code: the address code of instruction frame Function code: the code of function in the instruction Register start address: the address of data reading Register length: the reading of NPK CRC_L, CRC_H: Cyclic Redundancy Check network protocol
The general form of the instruction frame is:
| Address Code | Function Code | Register Start address | Register Length | CRC_L | CRC_H |
|---|---|---|---|---|---|
| 0x01 | 0x03 | 0x00 0x1e | 0x00 0x01 | 0XE4 | 0x0C |
An example of response to inquiry in the case of nitrogen is:
We can calculate the soil nitrogen from the
| Address Code | Function Code | Effective Number of bytes | Nitrogen Value | CRC_L | CRC_H |
|---|---|---|---|---|---|
| 0x01 | 0x03 | 0x02 | 0x00 0x20 | 0Xb9 | 0x9C |
The NPK Sensor has 3 different inquiry frames for reading the value of nitrogen (N), phosphorous (P), and potassium (K). The inquiry frame is provided laterally with the instruction manual. For the NPK data the following individual inquiry frameworks:
Now, we are ready to read data and transmit the data frame to the big data repository. Using Arduino we can read data instantly from OLED and save it into the data center for future management and control.
We have seen in the previous section how to install the control system hooked with the NPK sensor. Programmable Arduino is connected for enabling an instant read of NPK amounts on a daily basis. Two main jobs are needed from the Arduino program: the first is to display the instant reading of NPK concentration in the soil; the second is to send signals to the cloud data center of all readings of given variables [57, 58]. Data transmission can be programmed on daily or hourly (or any specified) time intervals; in our case the data transmission can be on daily basis and no less. A per-day interval is chosen because, as we discussed before, real growth in plants normally occurs at night, which comes as an output of the photosynthesis process.
The interfacing software of the soil NPK sensor is connected to Arduino. It can retrieve soil nutrient values from the sensor via instruction command. The instruction command can be sent, and the value obtained in hexadecimal code. Then the HEX code needs to be converted into number values in decimal to get the value of soil nutrient contents in shape of big data [59, 60, 61].
Here we are using the OLED display to see the soil nutrient values (nitrogen, phosphorus, and potassium) in mg/kg. Also, we need to download the OLED Library. And added to this, the Arduino IDE commands can instruct a set of devices to do the following:
Change the value in one of its registers on/off, which is written to one bit register Get the reading of an I/O port, and get data (8 bits) from holding register and reading from one bit register ( Command generating to the device (Arduino) to send and transmit values of iterations of Coil Registers and Holding Registers.
A Modbus instruction command contains the Modbus address of the device it is intended for (
Figure 9 shows two experimental plantings of tomatoes in two different containers in the same greenhouse conditions. In the first experiment we planted tomatoes using a traditional planting method: this method adds nutrients according to best-practice manual experience, which is adding nutrition as needed. The result – production of green and fruits – is up to 5.6 kg. The second part of Figure 9 shows planting tomatoes using controlled addition of nutrition based on each stage of growth. We found that with IoT controlled NPK addition, production will reach 7.4 kg, which exceeds the first, traditional, method by 2 kg. We can do more readings and experiments, playing with all variables, keeping records in our big data repository, until we define the very optimum production of greenhouse tomato cultivation.
Figure 9
A) Concentrations of NPK and
This research is based on experimental big data applied to smart greenhouse cultivation to give better production for tomato fruits. This article shows that we can define two categories of variables (parameters) that actually affect tomato growth. First: the surrounding environment and conditions like temperature, humidity, and light: these variables can be controlled and kept at ideal levels using RTH (Relative Temperature to Humidity) levels. Also, we can manage this category of conditions for greenhouses using method of sensor readings of values, and actuators based on events and triggers for action. Second: the tomato plant percentage of nutrient concentration in soil where the plant root is located can be known. These nutrients are dissolved in soil where plant roots absorb these nutrients. This article has defined more than five growing stages of the plant life time circle; each stage needs a certain amount of these nutrients added as a solution in the irrigation water (particularly nitrogen, phosphorus, and potassium [NPK]). Using special soil sensors, we can read data for the amount of each element and transmit the data readings to a data repository in a data center. Two experiments on tomato plants are conducted to determine the best amount of each nutrient to add to each plant growing stage. As we noticed, in the first stages of growth plants need the N element, and then we can play with the amounts of P and K to get the best production. The future work on this research is managing the data accumulated in the data center, to determine the best amount of each nutrient to give at each growth stage, and to use this big data to apply to other fruits’ growing stages, to create the best production plan.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
| Address Code | Function Code | Effective Number of bytes | Nitrogen Value | CRC_L | CRC_H |
|---|---|---|---|---|---|
| 0x01 | 0x03 | 0x02 | 0x00 0x20 | 0Xb9 | 0x9C |
Recommended temperature of tomato greenhouse based on light levels
| Night | 63°F (17°C) | 64°F (18°C) |
| Day | 66°F (19°C) | 70°F (21°C) |
Relative humidity ranges related to temperature in greenhouses
| 60 (16) | 60%–75% |
| 65 (18) | 65%–80% |
| 70 (21) | 70%–80% |
| 75 (24) | 75%–85% |
| 80 (27) | 80%–85% |
| 85 (29) | 85%–90% |