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Intelligent equipment is necessary to ensure stable, high-quality, and efficient production of facility agriculture. Among them, intelligent harvesting equipment needs to be designed and developed according to the characteristics of fruits and vegetables, so there is little large-scale mechanization. The intelligent harvesting equipment in Japan has nearly 40 years of research and development history since the 1980s, and the review of its research and development products has specific inspiration and reference significance. First, the preferential policies that can be used for harvesting robots in the support policies of the government and banks to promote the development of facility agriculture were introduced. Then, the development of agricultural robots in Japan was reviewed. The top ten fruits and vegetables in the greenhouse were selected, and the harvesting research of tomato, eggplant, green pepper, cucumber, melon, asparagus, and strawberry harvesting robots based on the combination of agricultural machinery and agronomy was analyzed. Next, the commercialized solutions for tomato, green pepper, and strawberry harvesting system were detailed and reviewed. Among them, taking the green pepper harvesting robot developed by the start-up company AGRIST Ltd. in recent years as an example, the harvesting robot developed by the company based on the Internet of Things technology and artificial intelligence algorithms was explained . This harvesting robot can work 24 h a day and can control the robot's operation through the network. Then, the typical strawberry harvesting robot that had undergone four generations of prototype development were reviewed. The fourth-generation system was a systematic solution developed by the company and researchers. It consisted of high-density movable seedbeds and a harvesting robot with the advantages of high space utilization, all-day work, and intelligent quality grading. The strengths, weaknesses, challenges, and future trends of prototype and industrialized solutions developed by universities were also summarized. Finally, suggestions for accelerating the development of intelligent, smart, and industrialized harvesting robots in China's facility agriculture were provided.

Terpenoids, abundant and structurally diverse secondary metabolites in plants, especially in conifer species, play crucial roles in the plant defense mechanism and plant growth and development. In Pinus massoniana, terpenoids' biosynthesis relies on both the mevalonate (MVA) pathway and the 2-methyl-D-erythritol-4-phosphate (MEP) pathway, with 1-hydroxy-2-methyl-2-(E)-butenyl-4-diphosphate synthase (HDS) catalyzing the sixth step of the MEP pathway. In this study, we cloned and conducted bioinformatics analysis of the PmHDS gene from P. massoniana. The results showed that PmHDS shares homology with HDS proteins from other species. Analysis of tissue expression patterns indicated that PmHDS exhibits the highest expression level in xylem tissue, followed by stems, with significantly lowest expression in the apical meristem. Treatment with NaCl, abscisic acid (ABA), ethylene (ETH), methyl jasmonate (MeJA), and salicylic acid (SA) upregulated the expression of PmHDS. Furthermore, we successfully cloned the PmHDS promoter (about 2220 bp) and integrated it into a GUS reporter vector, which resulted in GUS activity being observed in various tissues of Arabidopsis thaliana. Overexpression of the PmHDS gene in A. thaliana significantly increased the content of carotenoids, chlorophylls a and b, and related enzyme activities, as well as the levels of terpenoid derivatives such as cytokinin (CTK), gibberellic acid (GA), and ABA, thereby enhancing the resistance to those abiotic stresses. These findings suggest that PmHDS plays an important role in the terpenoid synthesis pathway. This study provides a theoretical basis for understanding the biosynthesis of terpenoids and lays a foundation for future research on the regulation of terpene synthesis and resistance in molecular breeding. [ABSTRACT FROM AUTHOR]

A series of novel amphiphilic alternating CPEG copolymers were synthesized through an amine–epoxy click reaction comprising aliphatic amine and polyethylene glycol diglycidyl ether (PEGDE). These polymers were characterized in detail via nuclear magnetic resonance (NMR), gel permeation chromatography (GPC), Fourier-transform infrared spectroscopy (FTIR), and thermogravimetric analysis (TGA) to confirm the successful synthesis. Due to their amphiphilic structure, these polymers display thermoresponsiveness, with tunable cloud points (Tcps) that are adjustable from 20.8 °C to 46.8 °C by altering the side-chain length of the aliphatic amine, varying the mixing ratios of copolymers, the solution's pH, and salt additions. This tunable thermoresponsive behavior positions CPEG copolymers as promising candidates for a range of functional material applications. [ABSTRACT FROM AUTHOR]

Learning analytics has received increasing attention in the field of education. However, few studies have investigated the overall impact of learning analytics interventions on learning achievements. This study aims to close this research gap and examine the sizes of the overall effects of learning analytics interventions on learning achievements according to research conducted from 2012 to 2021. In total, 33 empirical studies including 3098 participants were synthesized in the present meta-analysis. The findings revealed that learning analytics interventions had a large effect size on learning achievements. Furthermore, the impacts of 13 moderator variables were analyzed in depth. The results indicated that sample levels, learning domains, learning approaches, learning analytics technologies, and learning analytics metrics significantly moderated the effectiveness of learning analytics interventions. These findings and their implications for the use of learning analytics interventions were discussed in depth. [ABSTRACT FROM AUTHOR]

Transcription factors refer to types of proteins that perform significant functions in the process of gene expression regulation. The ethylene insensitive 3/ethylene insensitive 3-like (EIN3/EIL) family, functioning as significant transcription factors regulating ethylene, plays a critical role in the growth and development of plants and participates in the plant's response to diverse environmental stresses. Pinus massoniana is an excellent native tree with high economic and ecological value. However, the study of EIN3/EIL genes in gymnosperms, for instance, P. massoniana, is still relatively limited. In this research, four putative EIN3/EIL genes were identified in the transcriptome of P. massoniana. Bioinformatics analysis showed that PmEIL genes contain a highly conserved EIN3 domain and other structural features of acidic, proline-rich and glutamine-rich sites. The molecular evolution tree analysis demonstrated that the EIN3/EIL family was partitioned into three categories (A, B, and C), and the number, type, and distribution of conserved motifs grouped in one category were similar. The results of qRT-PCR indicated that the expression levels of PmEIL genes were markedly elevated in needles compared to other tissues. Through the analysis of expression patterns of the PmEIL genes under various stress treatments, it was found that the PmEIL genes could participate in plant hormone stimulation induction, osmosis, drought and other response processes. In addition, PmEIL is a nuclear localization protein. PmEIL1, PmEIL3, and PmEIL4 are transcriptional activators, while PmEIL2 is a transcriptional suppressor. This research provides a basis for further elucidating the function of EIN3/EIL transcription factors in growth, development and stress response of P. massoniana. [ABSTRACT FROM AUTHOR]

The document discusses the integration of intelligent agricultural machinery and robots in modern agriculture to address global food demands, labor shortages, and sustainability concerns. It highlights advancements in path-planning, sensor-based monitoring, precision agriculture, and robotic systems for various agricultural functions. The studies emphasize the role of robotics, AI, and sensor technology in enhancing agricultural efficiency, precision, and sustainability, ultimately contributing to a resilient global food system. The authors underscore the importance of embracing these innovations for a sustainable and high-efficiency agricultural future. [Extracted from the article]

Saline‐alkali soil degradation is a significant environmental problem with a negative impact on sustainable agroforestry development. Therefore, efficient remediation methods are urgently required. A potential solution to this problem is using biochar produced from bamboo waste and inoculated with plant growth‐promoting microbes as cleaner production materials for saline‐alkali soil. The present study investigated the potential of combining biochar, microbes, and dwarf bamboo to improve saline‐alkali soil. Different application rates (1%, 3%, and 5% of soil mass) of biochar were added to coastal saline soil planted with dwarf bamboo (Pleioblastus argenteastriatus) in pot experiments. Soil physicochemical properties, microbial communities, and plant responses were systematically studied. Bamboo and microbial‐modified biochar effectively decreased soil pH and electrical conductivity and increased soil nutrient contents. Compared with untreated soil, the relative abundance of the dominant bacterial phyla Acidobacteria, Actinobacteria, and Chloroflexi, and dominant fungal phyla Basidiomycota increased after applying biochar and modified biochar. With the increase in application concentration, the antioxidant activities of modified biochar decreased, biochar peroxidase and catalase content decreased, and the malondialdehyde content of bamboo biochar and microbial‐modified bamboo biochar decreased. The biomass of bamboo with added biochar and modified biochar was significantly higher than that of untreated soil. Comprehensive correlation and redundancy analyses showed that the bacterial and fungal communities were greatly affected by soil factors, especially soil pH, electrical conductivity, total organic carbon, potassium, and sodium ions. The findings of this study suggest that 5% bamboo biochar and 3% modified biochar benefit soil remediation, improve the stress resistance of dwarf bamboo, and enhance plant growth. Therefore, combined biochar–microbe remediation has great potential for the sustainable improvement of saline‐alkali soil. [ABSTRACT FROM AUTHOR]

Remote sensing-based techniques have been widely used for chlorophyll content (Cab) estimations, while they are challenging when transferred across different species. Sun-induced chlorophyll fluorescence (SIF) provides a new approach to address these issues. This research explores whether SIF has transferability for Cab estimation and to enhance between-species transferability. Here, three rice datasets and a rapeseed dataset were collected. Initially, direct transfer models were constructed using partial least squares regression (PLSR) based on SIF yield (SIFY) and reflectance, respectively. Subsequently, methods were employed within the rice datasets to improve the models' transferability. Finally, the between-species transferability of two data sources was validated in the rapeseed dataset. Direct transfer models indicated that the reflectance-based model exhibited a higher accuracy in predicting Cab when the training dataset acquired sufficient features, whereas the SIFY-based model showed better performance with fewer features. Spectral preprocessing methods can enhance the transferability, especially for SIFY-based models. In addition, supplementing 10% of out-of-sample data significantly improved the transferability. The proposed methods only require a small amount of new data to extend the original model for predicting Cab in other species. Specifically, the new method reduced the average RMSE based on SIFY and reflectance models by 23.59% and 35.51%, respectively. [ABSTRACT FROM AUTHOR]

In Pinus massoniana, the methyl-D-erythritol-4-phosphate (MEP) pathway plays a crucial role in the biosynthesis of terpenoids. The fourth step of this pathway is specifically regulated by 4-(cytidine 5′-diphospho)-2-C-methyl-D-erythritol kinase (CMK). In this study, PmCMK (MW892445.1) was isolated. As a member of the GHMP kinase family, PmCMK exhibits homology with CMK genes across diverse species. The examination of relative expression patterns revealed that PmCMK exhibited higher expression levels in tissues of P. massoniana that are rich in resin. We successfully cloned the PmCMK promoter (1654 bp) and integrated it into a GUS reporter vector. This construct was then transformed into the leaves of tobacco (Nicotiana × sanderae) to assess transient expression patterns. The results demonstrated that the promoter was active not only in the roots, leaves, and stems of the tobacco plants but also exhibited varying expression levels in response to treatments with IAA, SA, MeJA, and PEG6000. This suggested that PmCMK expression was modulated by a variety of signals. It revealed that the expression of PmCMK was affected by different treatments. Further allogeneic expression studies showed that tobacco overexpressing PmCMK exhibited increased levels of chlorophyll and carotene compared to the wild type. This enhancement in content indicates that PmCMK has a significant role in isoprene biosynthesis. These findings provide valuable insights for future research aimed at elucidating the biosynthetic pathways of terpenoids and developing breeding strategies to enhance resin production in P. massoniana. [ABSTRACT FROM AUTHOR]

Background: Online collaborative learning has been widely adopted in the field of education. However, learners often find it difficult to engage in collaboratively building knowledge and jointly regulating online collaborative learning. Objectives: The study compared the impacts of the three learning approaches on collaborative knowledge building, group performance, socially shared regulation, behavioural engagement, and cognitive load in an online collaborative learning context. The first is the automatic construction of knowledge graphs (CKG) approach, the second is the automatic analysis of topic distribution (ATD) approach, and the third one is the traditional online collaborative learning (OCL) approach without any analytic feedback. Methods: A total of 144 college students participated in a quasi‐experimental study, where 48 students learned with the CKG approach, 48 students used the ATD approach, and the remaining 48 students adopted the OCL approach. Results and Conclusions: The findings revealed that the CKG approach could encourage collaborative knowledge building, socially shared regulation, and behavioural engagement in building knowledge better than the ATD and OCL approaches. Both the CKG and ATD approaches could better improve group performance than the OCL approach. Furthermore, the CKG approach did not increase learners' cognitive load, but the ATD approach did. Implications: This study has theoretical and practical implications for utilising learning analytics in online collaborative learning. Furthermore, deep neural network models are powerful for constructing knowledge graphs and analysing topic distribution. Lay Description: What is currently known about the subject matter: Online collaborative learning has been widely adopted in the field of education.Learners often find it difficult to engage in collaboratively building knowledge and jointly regulating collaborative learning. What the paper adds to this: This study compared the impacts of three learning approaches, namely, the automatic construction of knowledge graphs (CKG), the automatic analysis of topic distribution (ATD), and the traditional online collaborative learning (OCL) approach.The findings revealed that the CKG approach could encourage collaborative knowledge building, socially shared regulation, and behavioral engagement in building knowledge better than the ATD and OCL approaches. Both the CKG and ATD approaches could better improve group performance than the OCL approach. Furthermore, the CKG approach did not increase learners' cognitive load, but the ATD approach did. Implications of study findings for practitioners: It is strongly recommended that the CKG approach can be employed to enhance collaborative knowledge building, socially shared regulation, and behavioral engagement in building knowledge in an online collaborative learning context. Both the CKG and ATD approaches contribute to improving group performance.Deep neural network models are powerful for constructing knowledge graphs and analysing topic distribution. [ABSTRACT FROM AUTHOR]

Pinus massoniana is an important coniferous tree species for barren mountain afforestation with enormous ecological and economic significance. It has strong adaptability to the environment. TEOSINTE BRANCHED 1/CYCLOIDEA/PCF (TCP) transcription factors (TFs) play crucial roles in plant stress response, hormone signal transduction, and development processes. At present, TCP TFs have been widely studied in multiple plant species, but research in P. massoniana has not been carried out. In this study, 13 PmTCP TFs were identified from the transcriptomes of P. massoniana. The phylogenetic results revealed that these PmTCP members were divided into two categories: Class I and Class II. Each PmTCP TF contained a conserved TCP domain, and the conserved motif types and numbers were similar in the same subgroup. According to the transcriptional profiling analysis under drought stress conditions, it was found that seven PmTCP genes responded to drought treatment to varying degrees. The qRT-PCR results showed that the majority of PmTCP genes were significantly expressed in the needles and may play a role in the developmental stage. Meanwhile, the PmTCPs could respond to several stresses and hormone treatments at different levels, which may be important for stress resistance. In addition, PmTCP7 and PmTCP12 were nuclear localization proteins, and PmTCP7 was a transcriptional suppressor. These results will help to explore the regulatory factors related to the growth and development of P. massoniana, enhance its stress resistance, and lay the foundation for further exploration of the physiological effects on PmTCPs. [ABSTRACT FROM AUTHOR]

Cellulose synthase (CESA) is a key enzyme in the synthesis of cellulose, which plays an important role in cell wall construction and plant growth and development. In this study, seven CesA genes of P. massoniana were identified by searching the transcriptome data. Bioinformatics analysis showed that the putative CESA proteins were composed of 984–1101 amino acids, each containing the typical motifs of CESA proteins. Phylogenetic analysis showed that Transcript4609, Tran-script2643 and Transcript1263 were clustered into three groups with proteins related to regulating secondary wall synthesis, while Transcript691, Transcript1283, Transcript418 and Transcript556 were categorized into three clades with those associated with the formation of the primary cell walls. RT-qPCR analysis showed that the CesA genes were differentially expressed in different tissues, and most of the genes were induced by different abiotic stress and hormones. Transcript4609, Tran-script2643 and Transcript1263 were mainly expressed in the xylem and could respond to drought and salt stress induced by ABA, MeJA, ETH and SA hormones, indicating that these three CesA genes may play an important role in the response to abiotic stress in P. massoniana. This study revealed the possible biochemical and physiological functions of the CesA gene in P. massoniana, which can provide a basis for further exploration of the function of the CesA gene in cell wall formation and the response to external stress. [ABSTRACT FROM AUTHOR]

Basic leucine zipper (bZIP) transcription factors (TFs) are ubiquitous in eukaryotes. Members of this family play significant roles in the regulation of plant growth, signal transduction, and various stresses. To date, bZIP TFs have been extensively studied in various plants, but there is little information about them in Pinus massoniana Lamb. In this study, 55 bZIP TFs were identified based on data from four different P. massoniana transcriptomes, and a systematic analysis was performed. According to the phylogenetic results, P. massoniana bZIP TFs were divided into 11 groups. Each bZIP protein contained a highly conserved bZIP domain, and the numbers and types of motifs were similar in the same group. The PmbZIPs were nuclear localization proteins. Based on the pine wood nematode inoculation transcriptome, the transcriptional profiles revealed that 25 PmbZIP genes could respond to pine wood nematodes at different levels. Genes PmbZIP3, PmbZIP4, PmbZIP8, PmbZIP20, and PmbZIP23 were selected to be upregulated in the process of inoculation with pine wood nematodes. These five genes had different expression levels in different tissues and were responsive to the related treatment conditions. Transcriptional activity analysis showed that PmbZIP3 and PmbZIP8 were transcriptional activators; PmbZIP4, PmbZIP20 and PmbZIP23 were transcriptional repressors. These findings provide preliminary information on PmbZIP TFs, which is helpful for further study of other physiological functions of bZIP TFs in P. massoniana. [ABSTRACT FROM AUTHOR]

Transcription factors (TFs) are a class of proteins that play an important regulatory role in controlling the expression of plant target genes by interacting with downstream regulatory genes. The lateral organ boundary (LOB) structural domain (LBD) genes are a family of genes encoding plant-specific transcription factors that play important roles in regulating plant growth and development, nutrient metabolism, and environmental stresses. However, the LBD gene family has not been systematically identified in Pinus massoniana, one of the most important conifers in southern China. Therefore, in this study, we combined cell biology and bioinformatics approaches to identify the LBD gene family of P. massoniana by systematic gene structure and functional evolutionary analysis. We obtained 47 LBD gene family members, and all PmLBD members can be divided into two subfamilies, (Class I and Class II). By treating the plants with abiotic stress and growth hormone, etc., under qPCR-based analysis, we found that the expression of PmLBD genes was regulated by growth hormone and abiotic stress treatments, and thus this gene family in growth and development may be actively involved in plant growth and development and responses to adversity stress, etc. By subcellular localization analysis, PmLBD is a nuclear protein, and two of the genes, PmLBD44 and PmLBD45, were selected for functional characterization; secondly, yeast self-activation analysis showed that PmLBD44, PmLBD45, PmLBD46 and PmLBD47 had no self-activating activity. This study lays the foundation for an in-depth study of the role of the LBD gene family in other physiological activities of P. massoniana. [ABSTRACT FROM AUTHOR]

Tactile perception is an irreplaceable source of information for humans to explore the surrounding environment and has advantages over sight and hearing in processing the material properties and detailed shapes of objects. However, with the increasing uncertainty and complexity of tactile perception features, it is often difficult to collect highly available pure tactile datasets for research in the field of tactile perception. Here, we have proposed a method for object recognition on a purely tactile dataset and provide the original tactile dataset. First, we improved the differential evolution (DE) algorithm and then used the DE algorithm to optimize the important parameter of the Gaussian kernel function of the support vector machine (SVM) to improve the accuracy of pure tactile target recognition. The experimental comparison results show that our method has a better target recognition effect than the classical machine learning algorithm. We hope to further improve the generalizability of this method and provide an important reference for research in the field of tactile perception and recognition. [ABSTRACT FROM AUTHOR]

CCCH-type zinc finger proteins play an important role in multiple biotic and abiotic stresses. More and more reports about CCCH functions in plant development and stress responses have appeared over the past few years, focusing especially on tandem CCCH zinc finger proteins (TZFs). However, this has not been reported in Pinaceae. In this study, we identified 46 CCCH proteins, including 6 plant TZF members in Pinus massoniana, and performed bioinformatic analysis. According to RT-PCR analysis, we revealed the expression patterns of five RR-TZF genes under different abiotic stresses and hormone treatments. Meanwhile, tissue-specific expression analysis suggested that all genes were mainly expressed in needles. Additionally, RR-TZF genes showed transcriptional activation activity in yeast. The results in this study will be beneficial in improving the stress resistance of P. massoniana and facilitating further studies on the biological and molecular functions of CCCH zinc finger proteins. [ABSTRACT FROM AUTHOR]

Group awareness has received increasing attention in recent years. Most studies on this topic have focused on ways in which group awareness tools can be used to support collaborative learning. However, the overall impacts of group awareness tools on learning achievements, learning behaviors, and learning perceptions remain unknown. The present study attempted to address these research gaps and investigate the effects of group awareness tools on learning achievements, learning behaviors, and learning perceptions on the basis of a meta-analysis. A comprehensive analysis of 43 qualified articles that were published from 2010–2023 and that focused on 3700 participants was performed as part of the present study. The results revealed that group awareness tools strongly affected learning achievements and had medium-sized effects on learning behaviors and learning perceptions. Moreover, as part of this study, the impacts of 10 crucial moderators were analyzed. The findings revealed that participant level, learning area, research design, research context, intervention duration, group awareness type, and group awareness data source substantially moderated the effects of group awareness tools on learning achievements. These findings, which have technological, theoretical, and practical implications for efforts to take advantage of group awareness, were analyzed and discussed thoroughly. [ABSTRACT FROM AUTHOR]

The development of tuber-root models based on the physical properties of the root system of a plant is a prominent but complicated task. In this paper, a method for the construction of a 3D model of a potato tuber-root system is proposed, based on determining the characterization parameters of the potato tuber-root model. Three early maturing potato varieties, widely planted in Northeast China, were selected as the research objects. Their topological and geometric structures were analyzed to determine the model parameters. By actually digging potatoes in the field, field data measurement and statistical analysis of the parameters were performed, and a model parameter database was established. Based on the measured data, the root trajectory points were obtained by simulating the growth of the root tips. Then MATLAB was used to develop a system that would complete the construction of the potato tuber-root 3D visualization model. Finally, the accuracy of the model was verified experimentally. Case studies for the three different types indicated an acceptable performance of the proposed model, with a relative root mean square error of 6.81% and 15.32%, for the minimum and maximum values, respectively. The research results can be used to explore the interaction between the soil-tuber-root aggregates and the digging components, and provide a reference for the construction of root models of other tuber crops. [ABSTRACT FROM AUTHOR]

[Display omitted] • Fluorescence characteristics of 14 cultivars of sweet pepper were investigated. • Fluorescent compounds were evaluated by excitation-emission matrices. • Fluorescence images were taken in both macro and micro scales. • The basis for applying fluorescence imaging-based sensing techniques was proposed. Sweet peppers are a popular vegetable with various surface colors, such as green, purple, red, or yellow. To characterize the unique fluorescence properties associated with a broad range of sweet peppers of various colors (14 varieties), a fluorescence spectrofluorometer and imaging were used. The results showed that all cultivars in the experiment had blue fluorescence emissions when excited with light in the UV-A region, while chlorophyll fluorescence could be observed in green peppers. The emitted blue fluorescence originated from the epidermis (cuticle layer). The color distribution of these sweet peppers in the a* and b* color space were compared to the image obtained under white LED light. Yellow and red pepper cultivars have thicker, multiple cuticular wax layers and more distinct maturity stages than other sweet pepper varieties observed. With the establishment of this basic fluorescence database, further applications of fluorescence-based techniques and the unification of evaluation methods for pepper quality will be more easily established. [ABSTRACT FROM AUTHOR]

• Fluorescence images were used for early-stage detection of strawberry spoilage. • Firmness measurement was conducted to verify strawberry spoilage. • Excitation-emission matrices were measured to characterize fluorescence spectra. • The soon spoiled fruits were classified by fluorescence images in an early-stage. • The proposed method can provide a new indicator for evaluating strawberry quality. The soon spoiled strawberries need to be classified from healthy fruits in an early stage. In this research, a machine vision system is proposed for inspecting the quality of strawberries using ultraviolet (UV) light based on the excitation-emission matrix (EEM) results. Among the 100 fruits which were harvested and stored under 10 °C condition for 7 days, 7 fruits were confirmed to be spoiled by using a firmness meter. The EEM results show the fluorescence compound contributes to a whitish surface on the spoiled fruits. Based on the EEM results, UV fluorescence images from the bottom view of strawberries were used to classify the spoiled fruits and healthy fruits within 1 day after harvest. These results demonstrate the UV fluorescence imaging can be a fast, non-destructive, and low-cost method for inspecting the soon spoiled fruits. The proposed index related to the spoiling time can be a new indicator for qualifying strawberry. [ABSTRACT FROM AUTHOR]

Quadcopters are beginning to play an important role in precision agriculture. In order to localize and operate the quadcopter automatically in complex agricultural settings, such as a greenhouse, a robust positioning system is needed. In previous research, we developed a spread spectrum sound-based local positioning system (SSSLPS) with a 20 mm accuracy within a 30 × 30 m greenhouse area. In this research, a noise tolerant SSSLPS was developed and evaluated. First, the acoustic noise spectrum emitted by the quadcopter was documented, and then the noise tolerance properties of SSSounds were examined and tested. This was done in a greenhouse with a fixed quadcopter (9.75 N thrust) with the positioning system mounted on it. The recorded quadcopter noise had a broadband noise compared to the SSSound. Taking these SSSound properties into account, the noise tolerance of the SSSLPS was improved, achieving a positioning accuracy of 23.2 mm and 31.6 mm accuracy within 12 × 6 m for both Time-division Multiple Access (TDMA) and Frequency-division Multiple Access (FDMA) modulation. The results demonstrate that the SSSLPS is an accurate, robust positioning system that is noise tolerant and can used for quadcopter operation even within a small greenhouse. [ABSTRACT FROM AUTHOR]