Search Results (3,439)

This study analyzed the planting characteristics and spatial patterns of public-type private gardens in urban areas. Five gardens in Daejeon and Ulsan were surveyed using quadrats to record tree locations and sizes and were digitized for layout mapping. Planting and analysis units were defined, and spatial patterns were examined using degree centrality. The gardens were classified into one site under mixed artificial–natural management and four sites under artificial management with commercial linkage. The mixed site featured both canopy and shrub layers, with spontaneous vegetation surrounding Pinus thunbergii, Pinus densiflora, and Prunus yedoensis. The commercial sites included either canopy-only or canopy-shrub structures. Lagerstroemia indica, P. densiflora, and Euonymus japonicus. were predominant in the temperate central region, while P. densiflora and Diospyros kaki. dominated in the southern region. This study identified the potential of public-type private gardens as planting models and their capacity to contribute to urban environmental improvement. Full article

With the development of electricity spot markets, the integrated renewable-storage plant (IRSP) has emerged as a crucial entity in real-time energy markets due to its flexible regulation capability. However, traditional methods face computational inefficiency in high-dimensional bidding scenarios caused by expansive decision spaces, limiting online generation of multi-segment optimal quotation curves. This paper proposes a policy migration-based optimization framework for high-dimensional IRSP bidding: First, a real-time market clearing model with IRSP participation and an operational constraint-integrated bidding model are established. Second, we rigorously prove the monotonic mapping relationship between the cleared output and the real-time locational marginal price (LMP) under the market clearing condition and establish mathematical foundations for migrating the self-dispatch policy to the quotation curve based on value function concavity theory. Finally, a generalized inverse construction method is proposed to decompose the high-dimensional quotation curve optimization into optimal power response subproblems within price parameter space, substantially reducing decision space dimensionality. The case study validates the framework effectiveness through performance evaluation of policy migration for a wind-dual energy storage plant, demonstrating that the proposed method achieves 90% of the ideal revenue with a 5% prediction error and enables reinforcement learning algorithms to increase their performance from 65.1% to 84.2% of the optimal revenue. The research provides theoretical support for resolving the “dimensionality–efficiency–revenue” dilemma in high-dimensional bidding and expands policy possibilities for IRSP participation in real-time markets. Full article

Lavender is a plant widely used in the cosmetic, pharmaceutical, and food industries, and it is also well known for producing nectar and pollen that bees use to make honey. However, due to increasingly adverse atmospheric conditions in recent years, characterized by prolonged dry spells or intense rainfall focused in short periods, the production of monofloral honey, such as lavender honey, has become increasingly challenging. Therefore, accurate mapping of monofloral zones in order to support beekeepers in placing their beehives in the best location is required. In this context, the town of Kuyucak in Isparta Province (Turkey), renowned for its extensive lavender fields, was selected. Using true orthophoto images from 2020 with a ground sampling distance (GSD) of 30 cm, machine learning classification methods and deep learning techniques were applied to identify and map the correspondent lavender fields. Lavender plants within the region were detected using Maximum Likelihood (ML), Support Vector Machine (SVM), and Random Forest (RF) classifiers, as well as the Mask R-CNN deep learning method. The classification achieved an overall accuracy of 95% and a kappa coefficient of 0.94. Subsequently, assuming a bee foraging range of 3 km, a moving squared window (sizing 3 × 3 km) was used to estimate local areas with potential forage resources and the corresponding honey production potential. The resulting honey potential production maps then used to identify optimal location for beekeepers’ hives in order to maximize lavender honey production. Full article

Medicinal plant production is essential for global health, yet how temperature, precipitation, and soil properties influence yield responses to fertilization remains poorly understood. Here, we conducted a meta-analysis of 668 observations from 79 studies, focusing on a wide range of plant species, to evaluate how nutrient inputs and environmental factors interact to shape medicinal plant productivity. We found that latitude, MAT, and MAP jointly determine global medicinal plant yield patterns. Yield increased with latitude and MAT but declined under prolonged fertilization and higher MAP. Optimal cultivation regions were identified between 15° and 35° absolute latitude, where temperature and precipitation conditions were most favorable. Compared with the arid environment of desertic climates, other regions, especially those with higher MAP in tropical areas, show a higher increase in yield. Our findings highlight that shifting precipitation-temperature regimes under climate change will affect fertilization outcomes on medicinal plant yield, emphasizing the need for spatiotemporally adaptive nutrient management strategies to ensure the sustainable yield of medicinal plants. Full article

Cannabis is a strictly regulated plant in China, and its illegal cultivation presents significant challenges for social governance. Traditional manual patrol methods suffer from low coverage efficiency, while satellite imagery struggles to identify illicit plantations due to its limited spatial resolution, particularly for sparsely distributed and concealed cultivation. UAV remote sensing technology, with its high resolution and mobility, provides a promising solution for cannabis monitoring. However, existing detection methods still face challenges in terms of accuracy and robustness, particularly due to varying target scales, severe occlusion, and background interference. In this paper, we propose AMS-YOLO, a cannabis detection model tailored for UAV imagery. The model incorporates an asymmetric backbone network to improve texture perception by directing the model’s focus towards directional information. Additionally, it features a multi-scale fusion neck structure, incorporating partial convolution mechanisms to effectively improve cannabis detection in small target and complex background scenarios. To evaluate the model’s performance, we constructed a cannabis remote sensing dataset consisting of 1972 images. Experimental results show that AMS-YOLO achieves an mAP of 90.7% while maintaining efficient inference speed, outperforming existing state-of-the-art detection algorithms. This method demonstrates strong adaptability and practicality in complex environments, offering robust technical support for monitoring illegal cannabis cultivation. Full article

Regulation of the phenylpropanoid pathway is critical for plant development and defense. This research investigates the transcriptional control of six Phenylalanine Ammonia-Lyase (PAL) gene homologs identified in the mulberry genome. A comprehensive in silico pipeline was employed to analyze the promoter architecture of these genes. Using the MEME suite, we identified three statistically significant conserved motifs within the 2000 bp upstream region. Subsequent TF binding prediction with FootprintDB for these motifs implicated the TCP, NAC, AP2/ERF, B3, and BBR-BPC families as potential regulators. A parallel analysis with PlantRegMap highlighted a high density of binding sites for the BBR-BPC and AP2/ERF families in the core promoter regions. A comparative analysis showed a weak correlation between the databases, underscoring the necessity of a multi-faceted predictive approach. Transcriptomic profiling under chitosan-induced conditions validated our in silico framework, suggesting the involvement of these TF families. Specifically, the data support NAC083 as a putative transcriptional activator and suggest a repressive function for members of the AP2/ERF and BBR-BPC families, providing a robust, experimentally supported model of PAL regulation. Full article

Glutathione S-transferases (GSTs) are key enzymes in plant defences involved in detoxification, redox regulation, and the modulation of secondary metabolism, playing essential roles in the response to pathogen infections. Despite prior genome-wide predictions of GSTs in potato, little is known about their specific roles in defending against Spongospora subterranea. This study re-analyses our previously generated transcriptomics and proteomics datasets to explore the role of GSTs in two contrasting potato cultivars, ‘Iwa’ (susceptible) and ‘Gladiator’ (resistant), after inoculation with S. subterranea. A total of 69 and 41 GSTs were identified in the transcriptomics and proteomics data, respectively. The majority of these GSTs were upregulated in the resistant cultivar but not in the susceptible cultivar. The upregulation of GSTs in ‘Gladiator’ suggests a more efficient antioxidant and detoxification response following S. subterranea infection. Chromosomal mapping revealed a high number of GSTs on chromosome 9, suggesting a hotspot for GSTs in the potato genome. This research provides direct evidence of the potential involvement of GSTs in resistance to S. subterranea, offering insights into potential targets for breeding resistant potato cultivars. Full article

Rice is a staple crop for over half the world’s population, and accurate, timely information on its planted area and production is crucial for food security and agricultural policy, particularly in developing nations like Sri Lanka. However, reliable rice monitoring in regions like Sri Lanka faces significant challenges due to frequent cloud cover and the fragmented nature of smallholder farms. This research introduces a novel, cost-effective method for mapping rice-planted area and yield at field scales in Sri Lanka using optical satellite data. The rice-planted fields were identified and mapped using a phenologically tuned image classification algorithm that highlights rice presence by observing water occurrence during transplanting and vegetation activity during subsequent crop growth. To estimate yields, a random forest regression model was trained at the district level by incorporating a satellite-derived chlorophyll index and environmental variables and subsequently applied at the field level. The approach has enabled the creation of two decades (2000–2022) of reliable, field-scale rice area and yield estimates, achieving map accuracies between 70% and over 90% and yield estimates with less than 20% error. These highly granular results, which are not available through traditional surveys, show a strong correlation with government statistics. They also demonstrate the advantages of a rule-based, phenology-driven classification over purely statistical machine learning models for long-term consistency in dynamic agricultural environments. This work highlights the significant potential of remote sensing to provide accurate and detailed insights into rice cultivation, supporting policy decisions and enhancing food security in Sri Lanka and other cloud-prone regions. Full article

PYR/PYL (pyrroloquinoline quinone resistance/PYR1-like) are receptors for abscisic acid (ABA) in plants and play a crucial role in responses to abiotic stress. In this study, we identified 63 members of the StPYL gene family at the tetraploid whole-genome level in potatoes. We analyzed the physicochemical properties of these 63 StPYLs and constructed a phylogenetic tree using Arabidopsis thaliana and potato (Solanum tuberosum L.) cultivar ‘DM’ as the reference. By examining gene structure, conserved protein motifs, and collinearity, we found that StPYLs are highly conserved throughout evolution. The gene expression heat map under salt stress revealed that 57 StPYL genes are involved in the salt stress response. Among them, the expression level of StPYL9a-like changed significantly under salt stress. Through genetic transformation, we observed that overexpression of StPYL9a-like enhanced the growth and survival of potato plants under salt stress compared to the wild type. The contents of proline (Pro), superoxide dismutase (SOD), and chlorophyll in the leaves of overexpressing plants increased, while malondialdehyde (MDA) levels decreased. This suggests that StPYL9a-like positively regulates salt tolerance by affecting antioxidant enzyme activity and osmotic adjustment substances in potatoes. Subcellular localization demonstrated that StPYL9a-like is localized in the nucleus. This study provides a reference for the functional research of PYLs in potatoes, offers a basis for screening potato genes related to salt stress, and lays a foundation for developing salt-tolerant potato varieties. Full article

Lance nematodes, Hoplolaimus spp., feed on the roots of many kinds of plants, including agronomic crops. In this study, morphological and molecular analyses of several Hoplolaimus species and populations are provided. We were able to collect and characterize the topotype materials of H. galeatus from Arlington, Virginia; H. stephanus syn. n. from Nichols, South Carolina; and H. concaudajuvencus from Pensacola, Florida, and several additional populations and species from the United States, Israel, and India. Phylogenetic analyses of several hundred sequences of the D2–D3 expansion regions of 28S rRNA, ITS rRNA, and COI genes of Hoplolaimus species obtained from published and original datasets were given. Fifty-three new D2–D3 of 28S rRNA, 43 new ITS rRNA, and 47 new COI sequences from 23 isolates of Hoplolaimus spp. and one isolate of Peltamigratus christiei were obtained in this study. New molecular identities for H. concaudajuvencus and H. galeatus were proposed. Hoplolaimus stephanus syn. n. was considered a synonym of H. galeatus based on the morphological and molecular similarity of these two species. Analysis of morphology and molecular data did not reveal significant differences among H. columbus syn. n., H. indicus syn. n., and H. seinhorsti, and the first two species were synonymized with H. seinhorsti. A new species, H. floridensis sp. n., was described from many locations in Florida, USA. It was separated from other representatives of the genus Hoplolaimus by its morphological and molecular characteristics. Maps with geographical distribution of several lance nematode species in North America were reconstructed based on published and original molecular identification of samples. Full article

In this study, we aimed to evaluate physiological and agronomic traits in 120 sugarcane genotypes under early drought stress conditions in a field trial across various soil types. The experiment used a split-plot arrangement, with a randomized complete block design and two replications. Two different water regimes were assigned to the main plot: (1) non-water stress (CT) and (2) drought (DT) at the early growth stage, during which sugarcane was subjected to drought stress by withholding water for 4 months. The subplot consisted of 120 sugarcane genotypes. The stalk height, stalk diameter, number of stalks, photosynthetic traits including SPAD chlorophyll meter reading (SCMR) and maximum quantum efficiency of photosystem II photochemistry (Fv/Fm), and normalized difference vegetation index (NDVI) were measured at 3, 6, and 9 months after planting (MAP). Yield and yield component parameters were measured at 12 MAP. Drought treatments lead to significant changes in various physiological traits in the sugarcane. Clustering analysis classified 36 sugarcane varieties grown in sandy loam soil and 15 genotypes in loam soil into two main clusters. In sandy loam soils, Biotec4 and CO1287 exhibited outstanding performance in drought conditions, delivering high cane yields. Meanwhile, in loam soil, MPT13-118, MPT07-1, Q47, F174, MPT14-1-902, and UT1 exhibited the best drought tolerance. Under drought conditions, cluster 1 showed higher values for SCMR, NDVI, height growth rate (HGR), cane yield, and drought tolerance index compared to cluster 2. These findings suggest that breeders can utilize these genotypes to enhance drought resistance, and the identified physiological traits can assist in selecting stronger candidates for drought tolerance. Full article

Plants grow, develop, and reproduce within a rhythmic environment. Environmental cues—such as light, temperature, nutrition, water—initiate, sustain, or terminate basic physiological processes within the plant, such as photosynthesis, respiration, nutrient uptake, water management, transpiration, growth, and hormone regulation. Simultaneously, inside the plant, internal “living clocks” are ticking and helping plants to synchronize internal processes with environmental cues and defend themselves against stressful conditions. These clock-regulated processes underlie a variety of plant traits, such as germination capability, growth and development rate, time of flowering, fruiting and yielding, development of plant shape, and size and biomass production. Most of these physiological traits are important attributes of crop plants. In recent years, the growing understanding of environmental rhythms as environmental cues and the mechanisms underlying plant internal clocks has begun to play an increasingly important role in agricultural practices. This is an emerging area of research that integrates insights from chronobiology with practices in plant agriculture. In this review, this new research area is studied and mapped using Scopus, Web of Science, Google Scholar, Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA protocol), and VOSviewer1.6.20 software. The analyses were carried out on 18 July–27 August 2025. For the VOSviewer author keywords co-occurrence analysis, all 1022 documents covering the time range of the last 7.5–2.5 years (2018–July 2025) were included and three maps were generated. Additionally, 59 review documents covering the last 27 years (1988–July 2025) were extracted by relevance using Google Scholar. In this review, recent advances and topics in plant chronobiology were examined. The issue of how these advances respond to key challenges in plant agriculture was explored. The bidirectional influence between chronobiology and practices in plant agriculture were also considered. Full article

NIN-like proteins (NLPs) are conserved, plant-specific transcription factors that play crucial roles in the nitrate signaling response, plant growth and development, and abiotic stress responses. However, their functions have not been explored in sweet potato. In this study, we identified 7 NLPs in cultivated hexaploid sweet potato (Ipomoea batatas, 2n = 6x = 90), 9 NLPs in the diploid relative Ipomoea trifida (2n = 2x = 30), and 12 NLPs in Ipomoea triloba (2n = 2x = 30) via genome structure analysis and phylogenetic characterization, respectively. The protein physiological properties, chromosome localization, phylogenetic relationships, syntenic analysis maps, gene structure, promoter cis-acting regulatory elements, and protein interaction networks were systematically investigated to explore the possible roles of homologous NLPs in the nitrate signaling response, growth and development, and abiotic stress responses in sweet potato. The expression profiles of the identified NLPs in different tissues and treatments revealed tissue specificity and various expression patterns in sweet potato and its two diploid relatives, supporting differences in the evolutionary trajectories of the hexaploid sweet potato. These results are a critical first step in understanding the functions of sweet potato NLPs and offer more candidate genes for improving nitrogen use efficiency and increasing yield in cultivated sweet potato. Full article

BASIC PENTACYSTEINE (BPC) is a small family of plant-specific transcription factors that play crucial roles in plant growth, development processes, and response to abiotic stresses. However, the specific roles of Nicotiana tabacum BPCs (NtBPCs) remain ambiguous. Here, we identified 12 NtBPC genes, 5 of which were mapped to four chromosomes. Phylogenetic analysis classified these genes into three subfamilies. Collinearity was observed among BPC genes of N. tabacum, Capsicum annuum, and Solanum lycopersicum. Moreover, polypeptides encoded by NtBPC genes within the same subfamily shared similar conserved motifs and protein domains. Subcellular localization showed that 10 NtBPC proteins are localized in the nucleus. Promoter analysis revealed the presence of abiotic stress response elements in the promoters of NtBPCs. Further tissue-specific expression analysis using RT-qPCR revealed that NtBPCs are highly expressed in stems and leaves. After drought, NaCl, and cold treatments, NtBPCs exhibited varied expression patterns. These findings provide valuable insights into the evolutionary dynamics of the NtBPC gene family and lay the groundwork for subsequent investigations into the functions of NtBPC genes. Full article

Electromagnetic induction (EMI) devices have become increasingly popular for their soil bulk properties, soil nutrient status, and use in taking non-invasive soil salinity measurements. However, the high cost of data acquisition (DAQ) systems has been a significant barrier to the widespread adoption of these devices. In this study, we addressed this challenge by developing a cost-effective, easy-to-use, open-source DAQ system, transferable to the end user. This system employs a Raspberry Pi 4 model, paired with various components, to monitor the speed and position of the EM38 (Geonics Ltd, Mississauga, ON, Canada) and compare these with a proprietary CR1000 system. Through our results, we demonstrate that the low-cost DAQ system can successfully extract the analogical signal from the device, which is strongly responsive to the variation in the soil’s physical properties. This cost-effective system is characterized by increased flexibility in software processes and provides performance comparable to the proprietary system in terms of its geospatial data and ECb measurements. This was validated by the strong correlation (R² = 0.98) observed between the data collected from both systems. With our zoning analysis, performed using the Kriging technique, we revealed not only similar patterns in the ECb data but also similar patterns to the Normalized Difference Vegetation Index (NDVI) map, suggesting that soil physical characteristics contribute to variability in crop vigor. Furthermore, the developed web application enabled real-time data monitoring and visualization. These findings highlight that the open-source DAQ system is a viable, cost-effective alternative for soil property monitoring in precision farming. Future enhancements will focus on integrating additional sensors for plant vigor and soil temperature, as well as refining the web application, supporting zone classification based on the use of multiple parameters. Full article