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The agricultural sector continues to be the largest consumer of useful water. Despite knowing the volume of water required by plants (evapotranspiration), methodologies must be adapted to current production systems. Based on the energy balance (radiation), it is feasible to establish models to estimate evapotranspiration depending on the production system: extensive crops, closed, and interior systems. The objective of this work was to present related research to measure and model the evapotranspiration of crops under current production techniques, based on the energy balance. The original FAO Penman–Monteith model is considered to be the model that best describes the evapotranspiration process, and with advances in instrumentation, there are sensors capable of measuring each of the variables it contains. From this model, procedures have been approximated for its use in extensive crops through remote sensing to calculate evapotranspiration, which jointly integrates the climatic variables and the type and age of the crop, with which real evapotranspiration is obtained. The same Penman–Monteith model has been adapted for use in greenhouse crops, where given the reduced root space and being in a closed environment, it is possible to know the variables specifically. Keeping the root container saturated, crop transpiration will basically depend on the physiology of the plant (LAI, stomatal resistance, etc.) and the characteristics of the air (radiation, VPD, wind speed, etc.). Models based on computational fluid dynamics (CFD) have been developed, which predict the real evapotranspiration of the crop by activating the discrete ordinate (DO) radiation sub-model. For indoor crops, in the absence of solar radiation, and replaced with artificial lights (LEDs)—although it is true that they are hydroponic crops and water can be estimated through a balance of levels—it would be possible to use CFD to estimate transpiration by transforming flux units (Mmol) into radiation (W m−2). The transpiration of indoor crops works as a cooling system and stabilizes the environment of the plant factory or vertical farm. In each crop production system (from open field to indoor crops) models have been developed to manage water and microclimate. The result is reports that more than 90% of the water is saved. [ABSTRACT FROM AUTHOR]

People spend most of their time indoors, and prolonged exposure to pollution can harm their health. The degradation of indoor air quality (IAQ) has raised serious issues. Botanical biofilters are an exciting solution for lowering indoor air pollution. However, plants cultivated inside under low light intensity (10–50 μmole PAR m−2 s−1) generate CO2 in the indoor atmosphere. Combining C3 (Calvin Cycle) and Crassulacean Acid metabolism (CAM) plants may be able to address this problem by lowering CO2 emission levels and enhancing the efficiency of pollution removal by removing the primary indoor air pollutants from actual interior settings, including carbon dioxide (CO2), formaldehyde (HCHO), particulate matter (PM2.5 and PM10), and total volatile organic compounds (TVOCs). As a result, a successful botanical biofilter made of several plants was researched. Indoor plants can phytoremediate a variety of indoor contaminants. However, just a few studies have demonstrated its efficacy in practical contexts. Due to the harsh winter, apartments in South Korea are frequently closed, necessitating the measurement of interior air pollution concentration in real-time. Four apartments (APT I through APT IV) with various ventilation and indoor plant setups were selected for this investigation. Various combinations of indoor environments (ventilation, low light) and a combination of C3 and CAM indoor plants as a botanical biofilter were used to study the sites over two months. Current research indicates that combining a botanical biofilter with ventilation can reduce levels of CO2, TVOCs, HCHO, PM2.5, and PM10 by 76%, 87%, 75%, 52%, and 51%, respectively. The current study concluded that different indoor potted plants provide an effective, affordable, self-regulating, sustainable option for enhancing indoor air quality and, consequently, human well-being and productivity in small, cramped places. [ABSTRACT FROM AUTHOR]

Plants have the potential to reduce CO2 concentration, but their photosynthesis is directly influenced by the indoor lighting environment. As a result, the efficiency of indoor plants is limited by indoor lighting environment. In order to explore the effect of lighting environments on the reduction of indoor CO2 concentration by indoor plants, three representative lighting environments were constructed, including a natural lighting environment, a poor lighting environment and an all-day lighting environment, while five common plants were selected to be planted in five transparent sealed chambers. Experimental results show that the lighting environment affected the CO2 concentration largely in transparent sealed chambers. Compared to the transparent sealed chamber without plants, the highest and average CO2 concentrations were increased by from 47.9% to 160.9% and from 21.6% to 132.4% in the poor lighting environment, respectively, while they decreased by from 60.4% to 84.6% and from 71.4% to 89.7% in the all-day lighting environment. This indicated that plants did not purify the indoor air consistently. Among the selected plants, the most suitable houseplant was Scindapsus aureus, followed by Chlorophytum comosum and Bambusa multiplex. [ABSTRACT FROM AUTHOR]

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Understanding crop responses to the light spectrum is critical for optimal indoor production. Far-red light is of particular interest, because it can accelerate growth through both physiological and morphological mechanisms. However, the optimal amount of supplemental far-red light for indoor lettuce production is yet to be quantified. Lettuce 'Cherokee', 'Green SaladBowl', and 'Little Gem' were grown under 204 µmol·m−2·s−1 warm-white light-emitting diodes (LEDs) with supplemental far-red ranging from 5.3 to 75.9 µmol·m−2·s−1. Supplemental far-red light increased canopy light interception 5 days after the start of far-red light treatment (DAT) for 'Green SaladBowl' and 'Little Gem' and 7 DAT for 'Cherokee'. The increase in light interception was no longer evident after 12 and 16 DAT for 'Green SaladBowl' and 'Little Gem', respectively. We did not find evidence that supplemental far-red light increased leaf-level photosynthesis. At the final harvest, shoot dry weights of 'Cherokee' and 'Little Gem' increased by 39.4% and 19.0%, respectively, while 'Green SaladBowl' was not affected. In conclusion, adding far-red light in indoor production increased light interception during early growth and likely increased whole plant photosynthesis thus growth, but those effects were cultivar-specific; the increase in dry weight was linear up to 75.9 µmol·m−2·s−1 far-red light. [ABSTRACT FROM AUTHOR]

Lettuce grown in indoor farms under fully artificial light is susceptible to a physiological disorder known as tip-burn. A vital factor that controls plant growth in indoor farms is the ability to adjust the growing environment to promote faster crop growth. However, this rapid growth process exacerbates the tip-burn problem, especially for lettuce. This paper presents an automated detection of tip-burn lettuce grown indoors using a deep-learning algorithm based on a one-stage object detector. The tip-burn lettuce images were captured under various light and indoor background conditions (under white, red, and blue LEDs). After augmentation, a total of 2333 images were generated and used for training using three different one-stage detectors, namely, CenterNet, YOLOv4, and YOLOv5. In the training dataset, all the models exhibited a mean average precision (mAP) greater than 80% except for YOLOv4. The most accurate model for detecting tip-burns was YOLOv5, which had the highest mAP of 82.8%. The performance of the trained models was also evaluated on the images taken under different indoor farm light settings, including white, red, and blue LEDs. Again, YOLOv5 was significantly better than CenterNet and YOLOv4. Therefore, detecting tip-burn on lettuce grown in indoor farms under different lighting conditions can be recognized by using deep-learning algorithms with a reliable overall accuracy. Early detection of tip-burn can help growers readjust the lighting and controlled environment parameters to increase the freshness of lettuce grown in plant factories. [ABSTRACT FROM AUTHOR]

The longleaf pine ecosystem is dependent on frequent fire. Climate change is expected to influence moisture availability and it is unclear how drought conditions may interact with prescribed fire to influence management objectives associated with maintaining longleaf pine ecosystems. This study aimed to understand the impacts of drought, fire intensity and their interaction on P. palustris grass-stage seedlings. We used droughted and well-watered P. palustris seedlings burned at two different fire intensity levels at an indoor combustion facility. Needle fuel moisture content of burned seedlings was not different between droughted and well-watered groups. Mortality and resprouting only occurred at fire intensity levels exceeding 3.5 MJ m−2 in combination with drought that resulted in predawn water potentials more negative than −1.7 MPa. Our observations of minimal mortality after exposing P. palustris seedlings to a range of fire intensities in a burn lab contrast the higher mortality observed in field studies for the species. Compared to seedlings and saplings of Western US Pinus species, this study demonstrates that P. palustris is considerably more resistant to the combined effects of high surface fire intensity and drought. [ABSTRACT FROM AUTHOR]

Background: Sansevieria cylindrica (S. cylindrica) Bojer ex Hook. (Asparagaceae) is an indoor ornate plant. The plant was conventionally utilized by the local healers during deliberate, and accidental injuries. The pharmacognostic study of this plant with different parameters was very poorly explored. Hence, the present investigation was carried out to explore, and evaluate different characteristics of the plant. Aim: To explore the preliminary pharmacognostic, physicochemical, phytochemical, microscopic, and phytoconstituents potential of S. cylindrica leaves for authentication of the plant. Method: The morphology, and microscopic properties of plant leaves were evaluated. The herbal standardization was then carried out based on physicochemical parameters including ash values, extractive values, and fluorescence analysis. The qualitative evaluation of phytoconstituents was performed using different chemical tests followed by quantitative estimation of important phytochemical, and analytical profiling of extract. Result: The macroscopy has studied for the basic features like colour, size, odor, shape, taste, surface, and fracture of plant leaves. The microscopical study confirms the presence of vessels, vascular bundles, lignified fibers, and calcium oxalate crystals etc. Physicochemical evaluation showed less quantity of inorganic matter present in the plant. Preliminary phytochemical analysis confirms the presence of glycosides, phenolic compounds, tannins, saponins, flavonoids, steroids, and carbohydrates. Instrumental analysis has given an idea about the identification, and confirmation of various phytoconstituents in the extract. Conclusion: The result of the present study can be meaningfully used as a reference for the standardization, and quality control of S. cylindrica and for the authentication, and preparation of monograph of the plant. [ABSTRACT FROM AUTHOR]

Aim and Objectives: The exploitation, adulteration and substitution of herbs is major hurdle for development of commercial natural products. Thus, the microscopic evaluation is the first step towards standardization of medicinal plant. A leaf from Sansevieria cylindrica Bojer ex Hook is examined both macroscopically and microscopically in the current study. Materials and Methods: Sansevieria cylindrica Bojer ex Hook (Asparagaceae) is an indoor ornamental plant. Macroscopic characteristics viz. size and shape, colour, odour and taste were studied. Microscopic evaluations were performed by means of high-resolution microscope. Anatomy of the leaves was examined by following standard method of section cutting. Results: The macroscopic assessment showed that the plant leaves are light to dark green in colour having highly fibrous structure. Stomatal constants of 230, 19.6% stomatal index, 53.34/mm2 vein islet number, and 79.12/mm2 vein termination number were noted in the leaves. Anomocytic stomata, unicellular trichomes, xylem fibres, oxalate crystals, vascular bundles, etc. were all revealed in detailed microscopy. Conclusion: The macroscopic and microscopic findings of the Sansevieria cylindrica leaf are applicable for standardization and authentication of plant. [ABSTRACT FROM AUTHOR]

Plants improve indoor environmental quality as a visual factor and enhance occupants' overall well‐being. However, research on the mechanisms by which plants improve human cognitive function is limited. This study examined the characteristics of eye movement while viewing indoor plants and their relationship with the cognitive benefits of plants. Thirty students performed cognitive tasks in four desktop conditions: no objects, real plants, artificial plants, and books. Eye movements while viewing plants during rest times in the reading span task (RST), which requires working memory, were characterized by a lower number of fixations, frequent dispersion of fixation points, and a higher number of blinks. Females showed higher RST scores under the real plant condition than under the no‐object condition. These results are consistent with the assumption that plants require lower cognitive effort and better restoration of attention capacity. In addition, in the real plant condition, females showed higher RST scores than males, and only females showed higher creativity scores than those in other conditions. Therefore, gender differences in the cognitive benefits of plants have been suggested. This study provides new insights into the effects of indoor plants on occupants' cognitive functions by quantifying visual perception processes using eye‐tracking technology. [ABSTRACT FROM AUTHOR]

Owing to the COVID-19 pandemic, working from home promotes the importance of indoor environment qualities. With the settings and functions of home offices, an experiment was carried out to determine the interaction effects between indoor plants and traffic noise levels (TNLs) on the performance and environmental evaluations of English reading comprehension tasks (ERCTs) and the performance of short-term breaks. A sample of 22 Chinese university students (12 males and 10 females) took part in the experiment. Two visual conditions (with and without plants) and five TNLs (i.e., 35, 45, 50, 55, and 60 dBA TNL) were included. Participants’ accuracy rates, eye movements, mental workload, and feelings about the environment were collected. The mental fatigue recovery (MFR), visual fatigue recovery (VFR), anxiety recovery (AR), and unfriendly recovery (UR) were measured for the analysis of a 5-min short-term break. The results demonstrate (1) plants have significant effects on ERCTs and short-term breaks, especially at 45 and 50 dBA TNL; (2) the effects of TNLs on ERCTs’ eye movements and work environment satisfaction differ by the presence of plants, e.g., the average pupil diameter (APD), lighting and layout satisfaction; (3) The effects of indoor plants on ERCT differ by the range of TNLs. In conclusion, indoor plants are beneficial to home workers engaged in ERCT when TNL does not exceed 50 dBA. The current data highlight the importance of audio-visual interaction in home offices and provide insights into the interaction mechanism between indoor plants and traffic noise. [ABSTRACT FROM AUTHOR]

This paper presents the implementation of a solar photovoltaic plant as a solution to the interconnectivity problems in the communities surrounding the municipality of Manaure in the department of La Guajira. The design and subsequent implementation of the system is presented here. This proposed system provides electricity to a house located in one of the non-interconnected areas, being a solution to this problem. The implemented system obeys with the standards established by the Colombian technical standard (in Spanish NTC) 2050 and electrical installation regulations (RETIE) for photovoltaic systems. This system was installed with two panels of 375W, a load ratio system and a inverter of 1kW, corresponding to the design. [ABSTRACT FROM AUTHOR]

For centuries, herbarium specimens were the focus of exchange in global botanical networks. The aim was the 'complete' registration of the flora, for which 'complete' collections in botanical institutions worldwide were considered to be a necessary basis, although this ardently sought-after ideal was never achieved. The study of colonial plants became a special priority of botanical research in the metropolises. With knowledge of the many treasures of the plant world considered the key to securing wealth and power, political and economic interests influenced both the organization and the subject matter of scientific research. After the German Reich began annexing colonies in the 1880s, legal regulations established Berlin's botanical institutions as the research centre on colonial flora. They also became a clearing house for plant material from overseas. Berlin-based curators selected duplicates of herbarium specimens from the German colonies, distributing them to other botanical institutions throughout Germany. More importantly, duplicates became a form of currency in trans-imperial networks, which relied on reciprocity. In exchange for duplicate German colonial herbarium specimens, the Berlin institutions received vast quantities of botanical samples from their British, Dutch, French and American counterparts. [ABSTRACT FROM AUTHOR]

Currently, there are no free databases of 3D point clouds and images for seedling phenotyping. Therefore, this paper describes a platform for seedling scanning using 3D Lidar with which a database was acquired for use in plant phenotyping research. In total, 362 maize seedlings were recorded using an RGB camera and a SICK LMS4121R-13000 laser scanner with angular resolutions of 45° and 0.5° respectively. The scanned plants are diverse, with seedling captures ranging from less than 10 cm to 40 cm, and ranging from 7 to 24 days after planting in different light conditions in an indoor setting. The point clouds were processed to remove noise and imperfections with a mean absolute precision error of 0.03 cm, synchronized with the images, and time-stamped. The database includes the raw and processed data and manually assigned stem and leaf labels. As an example of a database application, a Random Forest classifier was employed to identify seedling parts based on morphological descriptors, with an accuracy of 89.41%. [ABSTRACT FROM AUTHOR]