ARTICLE | doi:10.20944/preprints202201.0067.v1
Subject: Biology, Agricultural Sciences & Agronomy Keywords: duckweed; meal; Lemnoideae,; Wolffioideae; aquaculture; carbohydrates; protein
Online: 6 January 2022 (10:24:50 CET)
Duckweeds are the smallest flowering plants on Earth. They grow fast on water's surface and produce large amounts of biomass. Further, duckweeds display high adaptability, and species are found around the globe growing under different environmental conditions. In this work, we report the composition of 21 ecotypes of fourteen species of duckweeds belonging to the two sub-families of the group (Lemnoideae and Wolffioideae). It is reported the presence of starch and the composition of soluble sugars, cell walls, amino acids, phenolics, and tannins. These data were combined with literature data recovered from 85 publications to produce a compiled analysis that affords the examination of duckweeds as possible food sources for human consumption. We compare duckweeds compositions with some of the most common food sources and conclude that duckweed, which is already in use as food in Asia, can be an interesting food source anywhere in the world.
ARTICLE | doi:10.20944/preprints202206.0408.v1
Subject: Life Sciences, Other Keywords: Duckweed; Machine learning; Image analysis; Machine training; Aquatic plants; Lemnaceae; Lemna
Online: 29 June 2022 (14:56:08 CEST)
Numerous new technologies have been implemented in image analysis methods that help researchers withdraw scientific conclusions from biological phenomena. Plants of the family Lemnaceae (duckweeds) are the smallest flowering plants in the world, and biometric measurements of single plants and their growth rate are highly challenging. Although the use of software for digital image analysis has changed the way scientists extract phenomenological data (also for studies on duckweeds), the procedure is often not wholly automated and sometimes relies on the intervention of a human operator. Such a constraint can limit the objectivity of the measurements and generally slows down the time required to produce scientific data. Here is the need to implement image analysis software with artificial intelligence that can substitute the human operator. In this paper, we present a new method to study the growth rates of the plants of the Lemnaceae family based on the application of machine learning procedures to digital image analysis. The method is compared to existing analogical and computer-operated procedures. Results showed that our method drastically reduces the time consumption of the human operator while retaining a high correlation in the growth rates measured with other procedures As expected, machine learning methods applied to digital image analysis can overtake the constraints of measuring growth rates of very small plants and might help duckweeds gain worldwide attention thanks to their great nutritional qualities and biological plasticity.
ARTICLE | doi:10.20944/preprints202009.0475.v1
Subject: Biology, Other Keywords: Nile tilapia; Oreochromis niloticus; liver; duckweed; Lemna minor; Cu; Zn; Glutathione Peroxidase; GPx; Glutathione-S-Transferase; GST; Superoxide dismutase; SOD; Catalase; CAT; remediation assessment
Online: 20 September 2020 (14:41:41 CEST)
A two-fold integrated research study was conducted; firstly, to understand effects of copper (Cu) and zinc (Zn) on the growth and oxidative stress in Nile tilapia, Oreochromis niloticus; secondly, to study the beneficial effects of the duckweed Lemna minor L. as a heavy metal remover from wastewater. Experiments were conducted in mesocosms with and without duckweed. Tilapia fingerlings were exposed to Cu (0.004 and 0.02 mg/L) and Zn (0.5 and 1.5 mg/L) and fish fed for four weeks. We evaluated the fish growth performance, the hepatic DNA structure using comet assay, the expression of antioxidative genes (superoxide dismutase, SOD; catalase, CAT; glutathione peroxidase, GPx and glutathione-S-transferase, GST) and GPx and GST enzymatic activity. The results showed that Zn exhibited more pronounced toxic effects than Cu. Low dose of Cu did not influence the growth whereas higher doses of Cu and Zn significantly reduced the growth rate of tilapia compared to control, but addition of duckweed prevented weight loss. Further, in the presence of a high dose of Cu and Zn, DNA damage decreased, antioxidant gene expressions and enzymatic activities increased. In conclusion, results suggest that duckweed and Nile tilapia can be suitable candidates in metal remediation wastewater assessment programs.