Evapotranspiration Model Analysis of Crop Water Use in Plant Factory System

Pamungkas, Agung Putra; Hatou, Kenji; Morimoto, Takeshi

doi:10.2525/ecb.52.183

Cited by 16 publications

(11 citation statements)

References 12 publications

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“…On the other hand varies from crop to crop and stage to stage, details are available in [92]. However, as a case study, as seasonal tomato crop is selected as a reference and its value is shown in Figure 8, whereas for soilless CEA, estimation can be studied in [93].…”

Section: = * Equationmentioning

confidence: 99%

“…Now, can be estimated using Equation 3 where the average values of Kc for humid environment are used to estimate for tomato crop. However, these values depend on environmental conditions, for example, [93] results showed that value was almost equavalent to 1, which makes = 0 . However, both conditions meet Equation 2;…”

Section: Figure 8 Kc For Tomato Crop Under Standard Conditionsmentioning

confidence: 99%

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Building integrated agriculture information modelling (BIAIM): An integrated approach towards urban agriculture

Khan

Aziz

Ahmed

2018

Sustainable Cities and Society

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Urbanisation is transforming human societies in many ways. Besides bringing benefits to people in cities, it also has negative impacts such as food security. One way to meet the challenge is urban agriculture; however, traditional agricultural practices are not suitable within urban areas due to limited availability of land. Therefore, the alternative option is to grow crops inside or on top of buildings, e.g. building integrated agriculture (BIA). But, there is limited research and information available for designers and planners to design such buildings. The presented research project bridges the gap between agriculture and architecture by proposing a building integrated agriculture information modelling tool in integration with Building information modelling. The plugin tool has data on plants' requirements and automatic response to environmental factors. Environmental factors include temperature, light, water, nutrients, air, humidity, spacing and support. In this paper, seasonal tomato is selected as a reference crop, and the impact of environment (temperature, light, water, nutrients and spacing) on its health is discussed and simulated for germination stage. The undertaken project contributes to the concept of BIA and BIM maturity level, which would help to design an optimum environment building for plants.Historically, these practices have been used in many countries, while developed countries have also started taking interest due to increasing food security problems [19]. However, in urban regions, available land is limited therefore UA can be in two ways: open rooftop farming; or high-tech controlled environment agriculture (CEA) [20], which provides ultimate results by providing optimum conditions [21].CEA has been adopted to cultivate off-season crops and producing high-quality crops [22]. Though, for controlled environment building integrated agriculture (BIA), there is limited literature available. The key issue is the structural design of such modern BIA design; where the information on the plant-environment relationship is not available on state-of-the-art building designing tools [23][24][25]. For such practices to be possible, experts from various disciplines, i.e. agriculture, agronomy, architecture, urban planning, engineering, economics and public health will have to come together and work collaboratively [26]. Such intelligent collaborative platforms are also known as Building information modelling (BIM). BIM is a methodology, comprised of processes to generate and manage the information of building or group of buildings [27]. BIM can also be defined as "modelling technology and associated set of procedures to produce, communicate and analyse models" [28]. BIM tools get people and information working together effectively and efficiently through defined processes and technology [29]. Most of the developed countries have been using these tools for improvement in productivity and cost-savings throughout all stages of architectural, engineering and construction (AEC) industry [30]. Therefore, BI...

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Section: = * Equationmentioning

confidence: 99%

Section: Figure 8 Kc For Tomato Crop Under Standard Conditionsmentioning

confidence: 99%

Building integrated agriculture information modelling (BIAIM): An integrated approach towards urban agriculture

Khan

Aziz

Ahmed

2018

Sustainable Cities and Society

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“…It was reported that Penman and FAO-Penman-Monteith equations estimate ET value too much in this study. Likewise, Pamungkas et al (2014) reported that the most suitable ET equation for tomato plants grown in soilless culture was Stanghellini equation. Chartzoulakis and Drosos (1995) and Fernández et al (2010) were determined ET o value by using FAO24-Pan evaporation method in Mediterranean climate conditions.…”

Section: Assessment Of the Equationsmentioning

confidence: 99%

Seralarda Evapotranspirasyon Tahmini için Geliştirilen Denklemler

Karaca

Tezcan

Büyüktaş

et al. 2018

Yüzüncü Yıl Üniversitesi Tarım Bilimleri Dergisi

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It is estimated that the world population will be 9.6 billion by 2050. In order to meet the food needs of the growing population, it is necessary to increase the yield obtained from existing agricultural land. As the greenhouse provides a more controlled environment, the yield taken from the unit area is higher than the field conditions. For this reason, the greenhouse cultivation has been increased in year by year. Irrigation is one of the major cultural applications for increasing yield from the unit area. It is important that crop water requirement should be determined correctly for proper irrigation scheduling in greenhouse. The use of equations based on climate to determine evapotranspiration has been increased in recent years. In this study, estimation performances of evapotranspiration equations based on the reference crop (Penman, Hargreaves, FAO-24-Radiation, Priestley-Taylor, FAO-Penman Monteith, FAO24-Pan Evaporation) and main crop (Stanghellini, Fynn, Takakura, Simplified Model) developed from the past to the present day were reviewed. It is concluded that there is no standard equation under greenhouse conditions to determine evapotranspiration of a specific crop. The reason for this is that greenhouse climate changes depending on greenhouse type, location, direction, cover material, greenhouse volume, ventilation mechanism, usage of thermal curtain and shadow powder and even cultural applications such as hanging. However, it is possible to develop new equation or calibrate existing equations for each different greenhouse in the same region. Therefore, it is suggested that evapotranspiration equations to be used should be selected depending on the type of greenhouses commonly used in the region and, if necessary, modified according to these conditions.

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“…The PM model was primarily developed to predict the T r of crops grown in open field, while the Stanghellini model (SM) was mainly used in regard to greenhouse crops [9]. Previous studies on the validation of the SM with greenhouse pepper [10], acer rubrum tree [11], and tomato [12,13] showed overestimations of the estimated values, but few studies pointed out the reasons these overestimations. The overestimations of the SM may be due to (1) parameterization difficulties of the canopy resistance (r c ) and aerodynamic resistance (r a ) in the model, or (2) that proper observation positions of the input micrometeorological data of the model are not determined due to the meteorological environment in greenhouses being heterogeneous, which is different from in open fields [14,15].…”

Section: Introductionmentioning

confidence: 99%

Parameterization and Application of Stanghellini Model for Estimating Greenhouse Cucumber Transpiration

Yan

Huang

Zhang

et al. 2020

Water

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Accurate estimation of transpiration (Tr) is important in the development of precise irrigation scheduling and to enhance water-use efficiency in agricultural production. In this study, the air temperature (Ta) and relative humidity (RH) were measured at three different heights (0.5, 1.0, and 1.8 m above the ground near the plant canopy) parameterize aerodynamic resistance (ra) based on the heat transfer coefficient method and to estimate Tr using the Stanghellini model (SM) during two growing seasons of cucumber in a greenhouse. The canopy resistance (rc) was parameterized by an exponential relationship of stomata resistance and solar radiation, and the estimated Tr was compared to the values measured with lysimeters. After parameterization of ra and rc, the efficiency (EF) and the Root Mean Square Error (RMSE) of the estimated Tr by the SM based on micrometeorological data at a height of 0.5 m were 95% and 18 W m−2, respectively, while the corresponding values were 86% and 29 W m−2 at a height of 1.8 m for the autumn planting season. For the spring planting season, the EF and RMSE were 92% and 34 W m−2 at a height of 0.5 m, while the corresponding values were 81% and 56 W m−2 at a height of 1.8 m, respectively. This work demonstrated that when micrometeorological data within the canopy was applied alongside the data measured above the canopy, the SM led to better agreement with the lysimeter measurements.

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Evapotranspiration Model Analysis of Crop Water Use in Plant Factory System

Cited by 16 publications

References 12 publications

Building integrated agriculture information modelling (BIAIM): An integrated approach towards urban agriculture

Building integrated agriculture information modelling (BIAIM): An integrated approach towards urban agriculture

Seralarda Evapotranspirasyon Tahmini için Geliştirilen Denklemler

Parameterization and Application of Stanghellini Model for Estimating Greenhouse Cucumber Transpiration

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