Growth, Development and Yield of Horticultural Crop in Intelligent Greenhouses

A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Horticultural and Floricultural Crops".

Deadline for manuscript submissions: closed (15 March 2021) | Viewed by 8382

Special Issue Editor


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Guest Editor
Business Unit Greenhouse Horticulture, Wageningen University & Research, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands
Interests: agricultural engineering; agrotechnology; crop production; engineering; horticulture; physics; plant production systems; optics; energy saving; envelope materials; measurement systems; cropping systems; system development; artificial light; light; greenhouse technology; sustainability; closed systems

Special Issue Information

Dear Colleagues,

In order to supply consumers with fresh products produced close to large cities, greenhouses are an efficient way to produce fresh vegetables and fruits requiring only a small production area. Next to that, climate change causes a need for more protected and controlled crop cultivation, and greenhouses can ensure high yields and product quality. While greenhouse production is related to high water use efficiency and low pesticide use compared to outside production, it is also related to higher energy consumption and higher need for skilled labor. A greenhouse grower needs to make many decisions to maximize their production and to minimize their resources. Crop and greenhouse climate models and/or new intelligent algorithms can help the grower to oversee all the information needed and help to make complex decisions to predict yields and resource use.

In recent years, work has been done on dynamic greenhouse climate modeling and to describe crop production and development related to these climate parameters in crop models. In commercial greenhouses, data are collected mainly on environmental factors and resource use; however, objective data on crop physiological and product quality parameters are widely lacking. Moreover, uncertainty in data and models and a lack of fully understanding crop physiology and quality are a challenge on the way towards “intelligent” greenhouses.

This Special Issue will focus on the production of horticultural crops in intelligent greenhouses. We welcome novel research or reviews covering all related topics, including new crop models for yield or quality prediction, new self-learning algorithms, new sensors and interpretation of their data in relation to crop response, research to understand crop physiology, growth and development to make intelligent greenhouses possible, and case-studies where such models or algorithms are applied.

Prof. Dr. Silke Hemming
Guest Editor

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Keywords

  • Crop modelling
  • Greenhouse climate modelling
  • Artificial intelligence
  • Crop quality
  • Crop physiology
  • Resource efficiency
  • Data
  • Sensors

Published Papers (2 papers)

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Research

10 pages, 1222 KiB  
Article
Growth Stage Specific Lighting Spectra Affect Photosynthetic Performance, Growth and Mineral Element Contents in Tomato
by Giedrė Samuolienė, Jurga Miliauskienė, Algirdas Kazlauskas and Akvilė Viršilė
Agronomy 2021, 11(5), 901; https://doi.org/10.3390/agronomy11050901 - 04 May 2021
Cited by 5 | Viewed by 2980
Abstract
The aim of study was to evaluate if the alternation in growth stage–specific lighting spectrum would be superior for tomato growth, photosynthesis, and mineral element contents compared to constant spectrum lighting. Dwarf tomato (Solanum lycopersicum L. cv. Micro Tom) was cultivated in [...] Read more.
The aim of study was to evaluate if the alternation in growth stage–specific lighting spectrum would be superior for tomato growth, photosynthesis, and mineral element contents compared to constant spectrum lighting. Dwarf tomato (Solanum lycopersicum L. cv. Micro Tom) was cultivated in controlled environment chamber (23/19 °C) under light emitting diode lighting. Three lighting spectrum treatments were set, optimized for different tomato growth stages: “seedling” (S; blue (B, 447 nm), red (R, 660 nm) and far red (FR, 740 nm) light), “growth” (G; R, B and FR light, supplemented with 523 nm green) and fruiting (F; R, B, FR light supplemented with 385 nm ultraviolet A (UV-A)). The total photon flux density of 250 μmol m−2·s−1 was maintained in all treatments. Three lighting spectrums were alternated in seedling (S, G, F), biomass growth (SS, SG, GG, FF) and fruiting (SSS, SGG, GGG, GGF, FFF, SGF) stages of tomato creating growth stage-specific or constant lighting spectrum strategies. The light effects depended on tomato age, however the alternation in growth stage-specific lighting spectrum did not have a pronounced impact on dwarf tomato photosynthetic indices, growth, yield and mineral element content. The investigated parameters mainly depended on the spectrum of the latter growth stage. Full article
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15 pages, 1235 KiB  
Article
Optimizing the Electrical Conductivity of a Nutrient Solution for Plant Growth and Bioactive Compounds of Agastache rugosa in a Plant Factory
by Vu Phong Lam, Sung Jin Kim and Jong Seok Park
Agronomy 2020, 10(1), 76; https://doi.org/10.3390/agronomy10010076 - 05 Jan 2020
Cited by 28 | Viewed by 4903
Abstract
The objective of this study was to determine the proper electrical conductivity (EC) of a nutrient solution (NS) for accumulating bioactive compounds of Agastache rugosa without decreasing plant growth. Six-week-old seedlings were transplanted in a deep flow technique system with Hoagland NS with [...] Read more.
The objective of this study was to determine the proper electrical conductivity (EC) of a nutrient solution (NS) for accumulating bioactive compounds of Agastache rugosa without decreasing plant growth. Six-week-old seedlings were transplanted in a deep flow technique system with Hoagland NS with a 2.0 dS·m−1 EC for the initial week. From eight days after transplanting, the plants were treated with six EC treatments of 0.5, 1.0, 2.0, 4.0, 6.0, and 8.0 dS·m−1 for three weeks. Plant growth parameters, leaf gas exchange parameters, the relative chlorophyll value, and the ratio of variable to maximum fluorescence (Fv/Fm) were measured, and the rosmarinic acid (RA), tilianin, and acacetin concentrations were analyzed at 28 days after transplanting. The results showed that almost all plant growth parameters were maximized at 2.0 and 4.0 dS·m−1 and minimized at 8.0 dS·m−1 compared with the other EC treatments. The relative chlorophyll and Fv/Fm values were maximized at 2.0 and 4.0 dS·m−1. Similarly, leaf gas exchange parameters were increased at 2.0 and 4.0 dS·m−1. The RA content exhibited significantly higher values at 0.5, 1.0, 2.0, and 4.0 dS·m−1 compared with other treatments. The tilianin and acacetin contents exhibited the significantly highest values at 4.0 and 0.5 dS·m−1, respectively. These results suggest optimal EC treatment at 4.0 dS·m−1 for increasing bioactive compounds in A. rugosa plants without decreasing plant growth. Excessively high or low EC induced salinity stress or nutrient deficiency, respectively. Furthermore, among the plant organs, the roots of A. rugosa contained the highest RA concentration and the flowers contained the highest tilianin and acacetin concentrations, which revealed a higher utilization potential of the roots and flowers for bioactive compounds. Full article
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