Vertical farming for lettuce production in limited space: a case study in Northern Thailand.

Background: Greenhouse vertical farming under natural sunlight is an alternative farming technique that grows crops in a stacking column and extends in a vertical direction. Sunlight availability is one of the crucial factors for crop development in vertical farming. Therefore, this investigation aimed to examine the effect of sunlight availability on lettuce growth and yields at different levels of vertical shelves. Methods: Six shelves were constructed with three levels: upper, middle and lower levels. Lettuces (Lactuca sativa L.) as 'Baby Cos' and 'Green Oak' at 14 days after sowing were planted on the three levels. The photosynthetic photon flux density (PPFD) was recorded, and the PPFD values were then converted to the daily light integral (DLI). Plant height and canopy width were measured three times at 14, 21 and 28 days after transplanting. At maturity, fresh weight (FW) was directly monitored after harvest. Results: The results showed that the highest PPFD and DLI values were found at the upper level (PPFD 697 µmol m-2 s-1 and DLI 29 mol m-2 d-1) in comparison to the middle (PPFD 391 µmol m-2 s-1 and DLI 16 mol m-2 d-1) and lower (PPFD 322 µmol m-2 s-1 and DLI 13 mol m-2 d-1) levels. The lowest plant height and canopy width values were observed on the upper levels for both lettuce varieties during the three measurement dates. The middle ('Baby Cos' = 123.8 g plant-1 and 'Green Oak' = 190.7 g plant-1) and lower ('Baby Cos' = 92.9 g plant-1 and 'Green Oak' = 203.7 g plant-1) levels had the higher values of FW in comparison to the upper level ('Baby Cos' = 84.5 g plant-1 and 'Green Oak' = 97.3 g plant-1). The values of light use efficiency (LUE) showed an increased trend from the upper to lower levels in both varieties, with values of 'Baby Cos' of 0.10 g mol-1 in the upper level, 0.28 g mol-1 in the middle level and 0.26 g mol-1 in the lower level and 'Green Oak' of 0.12 g mol-1 in the upper level, 0.44 g mol-1 in the middle level and 0.57 g mol-1 in the lower level. The findings of the study indicated the viability of utilizing vertical shelves for lettuce production.

The implementation of the SPAD-502 Chlorophyll meter for the quantification of nitrogen content in Arabica coffee leaves.

The utilization of a non-destructive SPAD-502 chlorophyll meter, which enables the measurement of nitrogen status in plant leaves, has gained popularity in agronomic crops. Its application to horticultural crops like coffee remains relatively uncommon. The device provides quick and real-time measurements, helping to provide on-time nitrogen fertilizer to coffee plants before deficiency signs occur. Coffee leaves are characterized by thick and waxy leaves, together with many layers of tree crown. Therefore, the objective of this study was to develop a method for measuring nitrogen levels in coffee plants using the SPAD-502 Chlorophyll meter for an appropriate nitrogen fertilizer application rate in Arabica coffee plants. •Coffee trees were separated into upper, middle and lower levels. Data on SPAD values and total nitrogen were analyzed.•Pearson Correlation Coefficient (R), Coefficient of Determination (R2) and linear regression were calculated for different three levels of both SPAD-502 and total nitrogen values.•The results revealed a strong correlation (R2 = 0.63) between the SPAD readings of coffee leaves obtained from the upper canopy and their nitrogen content. These findings can provide a good concept of which coffee crown level will be a better part for measuring N content using a SPAD-502 Chlorophyll meter.

Non-Intrusive Fish Weight Estimation in Turbid Water Using Deep Learning and Regression Models.

Underwater fish monitoring is the one of the most challenging problems for efficiently feeding and harvesting fish, while still being environmentally friendly. The proposed 2D computer vision method is aimed at non-intrusively estimating the weight of Tilapia fish in turbid water environments. Additionally, the proposed method avoids the issue of using high-cost stereo cameras and instead uses only a low-cost video camera to observe the underwater life through a single channel recording. An in-house curated Tilapia-image dataset and Tilapia-file dataset with various ages of Tilapia are used. The proposed method consists of a Tilapia detection step and Tilapia weight-estimation step. A Mask Recurrent-Convolutional Neural Network model is first trained for detecting and extracting the image dimensions (i.e., in terms of image pixels) of the fish. Secondly, is the Tilapia weight-estimation step, wherein the proposed method estimates the depth of the fish in the tanks and then converts the Tilapia's extracted image dimensions from pixels to centimeters. Subsequently, the Tilapia's weight is estimated by a trained model based on regression learning. Linear regression, random forest regression, and support vector regression have been developed to determine the best models for weight estimation. The achieved experimental results have demonstrated that the proposed method yields a Mean Absolute Error of 42.54 g, R2 of 0.70, and an average weight error of 30.30 (±23.09) grams in a turbid water environment, respectively, which show the practicality of the proposed framework.

Dual-bioaugmentation strategy to enhance the formation of algal-bacteria symbiosis biofloc in aquaculture wastewater supplemented with agricultural wastes as an alternative nutrient sources and biomass support materials.

This study performs an integrated evaluation of the formation and distribution of algal-bacterial bioflocs in aquaculture wastewater supplemented with agricultural waste, together with an assessment of their behavior in the microbial community and of the water quality of the system in which a new bioaugmentation strategy was applied. Results indicated that the dual bioaugmentation strategy via the consortium addition of bacteria and microalgae had the highest formation performance, providing the most compact biofloc structure (0.59 g/L), excellent settleability (71.91%), and a large particle diameter (4.25 mm). The fed-batch supplementation of molasses and rice bran, in terms of changes in the values of COD, NH4+, NO3-, and PO43-, stimulated the formation of biofloc through algal-bacterial bioflocs and microbe-rice bran complexes within a well-established microbial community. These findings provide new insight into the influence of bioaugmentation on the formation of an innovative algal-bacterial biofloc.

Influence of coal treatments on the Ni loading mechanism of Ni-loaded lignite char catalysts.

Many kinds of lignite coals have been used as catalyst supporters for preparing the Ni-loaded lignite char catalyst. However, these coals have different properties; especially ash content. The ash in coal affects the mechanism of Ni-loading on the position of the functional group structures in coal. In catalyst preparation, it is interesting that the difference in coal properties might directly influence the mechanism of Ni loading. To prove this point, the coal sample needed to be treated before the catalyst preparation. MM coal (original coal) was treated with acid (HClMM and AceMM coals), alkali (NaMM coal) and alkali followed by acid treatments (NaHClMM and NaAceMM coals). Then, Ni was loaded on the five treated coals by the ion-exchange technique. The Ni-loaded lignite coals were pyrolyzed at 650 °C under a N2 atmosphere to prepare the Ni-loaded lignite char catalysts. The Ni-loading mechanisms were studied via FTIR, XRD, AAS and SEM-EDS analyses. The results showed that the different treatments affected the ash content and the functional groups in the coals. The decreases in the ash contents of HClMM, AceMM, NaHClMM and NaAceMM coals indicated that the exchangeable metallic species were removed by transforming metal-carboxylates into carboxyl groups. The transformations of metal-carboxylates were confirmed by the increased Δϑ(COO-) value. For acid treatment, the ion exchange of Ni was controlled by carboxyl groups, while in alkali treatment it occurred through hydroxyl and metal-carboxyl groups. In alkali followed by acid treatment, Ni ions were exchanged with hydroxyl and carboxyl groups. The Ni ion forms, Ni(NH3)6 2+ and/or Ni(H2O)6 2+, appeared on the modified coals. Through pyrolysis, the Ni ion was reduced to Ni metal that was observed in the XRD patterns of the catalysts. The Ni contents of the catalysts were in the range of 16.51-20.07 wt%. The thermal behaviours of the catalysts were presented via TGA-DTG.

Quantitative analysis of methane and glycolate production from microalgae using undiluted wastewater obtained from chicken-manure biogas digester.

Microalgal biomass is often used as a raw material in methane production. Some microalgae possess a complex cell-wall structure which has a low degradability of microorganisms in anaerobic digestion. However, some microalgae produce glycolate, which is excreted outside the cell and can be used to produce methane under anaerobic condition. This research aims to investigate microalgal cultivation using wastewater to reduce nutrients and efficiently create glycolate. Two strains of microalgae (Acutodesmus sp. AARL G023, Chlorella sp. AARL G049) and two microalgal consortia were cultivated at dilutions of 0.5-fold (W50), 0.75-fold (W75) and undiluted wastewater (W100). The results showed that the microalgal consortium with undiluted wastewater (WCW100) consisted of Leptolyngbya sp. (30.4%), Chlorella sp. (16.1%) and Chlamydomonas sp. (52.2%), revealed the highest biomass productivity at 64.38 ± 14.54 mg·L-1·d-1 and the highest glycolate productivity at 5.12 ± 0.48 mmol·L-1·d-1. The cultivation of microalgae effectively reduced ammonium­nitrogen (NH4+-N) and soluble reactive phosphorus (SRP) levels in the wastewater at 43.5 ± 1.3% and 49.6 ± 6.9%. Furthermore, WCW100 showed the highest biogas productivity at 1.44 ± 0.07 mL·g-1·d-1 and the highest methane content at 58.3 ± 6.0% v/v. This study indicates that there is a definite potential of using undiluted wastewater for microalgal biomass production and glycolate production that can reduce the wastewater volume and be applied as a raw material for methane production.