Graph and download economic data for Producer Price Index by Commodity: Farm Products: Blueberries (WPU01110227) from Dec 1991 to Sep 2024 about agriculture, commodities, PPI, inflation, price index, indexes, price, and USA.

United States - Producer Price Index by Commodity: Farm Products: Blueberries was 43.06800 Index Dec 1991=100 in September of 2024, according to the United States Federal Reserve. Historically, United States - Producer Price Index by Commodity: Farm Products: Blueberries reached a record high of 100.00000 in December of 1991 and a record low of 10.00000 in July of 1998. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Producer Price Index by Commodity: Farm Products: Blueberries - last updated from the United States Federal Reserve on July of 2025.

Graph and download economic data for Producer Price Index by Commodity: Farm Products: Other Fruits and Berries (WPU011102) from Jan 1947 to May 2025 about agriculture, commodities, PPI, inflation, price index, indexes, price, and USA.

United Kingdom OFBPI: Fruit: Blueberries data was reported at 101.000 01Jun2020=100 in 22 Mar 2021. This records an increase from the previous number of 100.600 01Jun2020=100 for 15 Mar 2021. United Kingdom OFBPI: Fruit: Blueberries data is updated weekly, averaging 100.900 01Jun2020=100 from Jun 2020 (Median) to 22 Mar 2021, with 43 observations. The data reached an all-time high of 104.800 01Jun2020=100 in 14 Sep 2020 and a record low of 98.000 01Jun2020=100 in 15 Feb 2021. United Kingdom OFBPI: Fruit: Blueberries data remains active status in CEIC and is reported by Office for National Statistics. The data is categorized under Global Database’s United Kingdom – Table UK.I037: Online Food and Beverages Price Index: 1 June 2020=100.

The BlueberryDCM dataset consists of 140 RGB images of blueberry canopies captured at varied spatial scales. All the images were acquired using smartphones in natural field light conditions in different orchards in the season of 2022, with 134 images in Mississippi and 6 images in Michigan. A total of 17,955 bounding box annotations were manually done in the VGG Image Annotator (VIA) (v2.0.12) for the blueberry instances of two fruit maturity classes, "Blue" and "Unblue", representing ripe and unripe fruit, respectively. In addition, for each maturity class, there are two sub-categories in the annotation, "visible", and "occluded", to indicate whether the fruit is fully visible in the canopy or partially occluded. The original annotation format exported from the VGG is VIA .json. The derived annotation files in two other formats, .xml (Pascal VOC format) and .txt (YOLO format with noralized xywh, with 0, 1, 2, and 3 denoting the four categories of "Unblue_visible", "Unblue_occluded", "Blue_visible", and "Blue_occluded" bluerries, respectively) are provided in the dataset for the compatibility of a wide range of object detectors. Hence, the dataset contains both the raw images (.jpg) and three corresponding annotations files (.json, .xml, and .txt) with the same file names, totaling about 107 MB in file size.

The dataset was used for in a study (see below) on the evaluation of YOLOv8 and YOLOv9 models for blueberry detection, counting, and maturity assessment. The detection accuracy of 93% mAP@50 was achieved by YOLOv8l, with an error of about 10 blueberries in fruit counting and an error of 3.6% in estimating the "Blue" fruit percentage. Software programs for the modeling work are made publicly available at: https://github.com/vicdxxx/BlueberryDetectionAndCounting. In addition, the blueberry dataset was also used as a preliminary database for developing an iOS-based mobile application, which is described in Deng, B., Lu, Y., WanderWeide, J., 2024. Development and preliminary evaluation of a deep learning-based fruit counting mobile application for highbush Blueberries. 2024 ASABE Annual International Meeting 2401022

Details about the dataset curation and statistics as well as modeling experiments are described in the journal article: Deng, B., Lu, Y., 2024. Detection, Counting, and Maturity Assessment of Blueberries in Canopy Images using YOLOv8 and YOLOv9. Smart Agricultural Technology. https://doi.org/10.1016/j.atech.2024.100620. If you use the dataset in published research, please consider citing the dataset or the journal article. Hopefully, you find the dataset useful.

The Uzbek market for raspberries, blackberries, blueberries, and cranberries soared to $7.3M in 2024, picking up by 20% against the previous year. Over the period under review, the total consumption indicated a pronounced increase from 2012 to 2024: its value increased at an average annual rate of +4.6% over the last twelve years. The trend pattern, however, indicated some noticeable fluctuations being recorded throughout the analyzed period.

Introduction: Endothelial dysfunction indicates blood vessel injury and is a risk factor for cardiovascular diseases. Blueberry has been approved for its benefits on human health, especially on cardiovascular function. However, its effect on endothelial function remains unclear. We conducted a systematic review and meta-analysis to explore the impact of blueberries on endothelial function in adults.Methods: We searched PubMed, Web of Science, Embase, and the Cochrane Library, 16 studies were included in the systematic review, and 11 were used for the meta-analysis. Data associated with endothelial function were extracted and pooled as mean differences (MD) with 95% confidence intervals (CI).Results: Blueberry consumption significantly improved flow-mediated dilation (FMD) by 1.50% (95% CI: 0.81, 2.20; I2 = 87%) and reactive hyperemia index (RHI) by 0.26 (95% CI: 0.09, 0.42; I2 = 72%). A significant decrease in diastolic blood pressure (DBP) was also observed (MD: −2.20 mm Hg; 95% CI: −4.13, −0.27; I2 = 11%). Subgroup analysis indicated a significant decrease in blood pressure (Systolic blood pressure [SBP]: −3.92 mmHg; 95% CI: −6.88, −0.97; I2 = 20% and DBP: −2.20 mmHg; 95% CI: −4.13, −0.27; I2 = 11%) in the smoking population. However, SBP levels (MD: −1.43 mm Hg; 95% CI: −3.11, 0.26; I2 = 20%) and lipid status (high-density lipoprotein cholesterol [HDL-C]: 0.06; 95% CI: −0.04, 0.16; I2 = 77%; low-density lipoprotein cholesterol [LDL-C]: 0.05; 95% CI: −0.14, 0.24; I2 = 0%) did not significantly improve.Conclusion: Blueberry intervention improved endothelial function and DBP. Subgroup analysis revealed a notable improvement in blood pressure among the smoking population. However, no significant effects were observed on SBP, HDL-C, and LDL-C levels. Future research should delve into the mechanisms of endothelial improvement and verify blood pressure reduction in specific subpopulations through large-scale trials.Clinical Trial Registration:https://www.crd.york.ac.uk/PROSPERO/, Identifier CRD42023491277.

Korea Consumer Price Index (CPI): Weight: Commodities: AM: AP: Fruits: Blueberry data was reported at 0.200 Per 1000 in Jun 2018. This stayed constant from the previous number of 0.200 Per 1000 for May 2018. Korea Consumer Price Index (CPI): Weight: Commodities: AM: AP: Fruits: Blueberry data is updated monthly, averaging 0.200 Per 1000 from Jan 2015 (Median) to Jun 2018, with 42 observations. The data reached an all-time high of 0.200 Per 1000 in Jun 2018 and a record low of 0.200 Per 1000 in Jun 2018. Korea Consumer Price Index (CPI): Weight: Commodities: AM: AP: Fruits: Blueberry data remains active status in CEIC and is reported by Statistics Korea. The data is categorized under Global Database’s Korea – Table KR.I022: Consumer Price Index: Special Groups: 2015=100: Weights.

This data represents the UAV image acquisition from August 2022 in blueberry orchards located in Babe, Serbia.

This is the first part of larger dataset, that contains raw images and orthomosaics generated using these images. Raw images are in 100FPLAN, 101FPLAN, and 102PLAN, while generated orthomosaics are in folder Raw orthomosaics August.

Another dataset will be uploaded with preprocessed data titled in the similar manner.

Timeseries data from 'Blueberry Hill (Imiq: 962)' (imiq_uaf_atlas_blueberryhill) cdm_data_type=TimeSeries cdm_timeseries_variables=station,longitude,latitude contributor_email=satellite@gina.alaska.edu,,,,feedback@axiomdatascience.com contributor_name=Geographic Information Network of Alaska (GINA),US Fish and Wildlife Service (US FWS),Arctic Landscape Conservation Cooperative (Arctic LCC, defunded 2019),North Slope Science Initiative (NSSI),Axiom Data Science contributor_role=contributor,sponsor,sponsor,sponsor,processor contributor_role_vocabulary=NERC contributor_url=https://gina.alaska.edu/,https://www.fws.gov/,https://lccnetwork.org/lcc/arctic,https://northslopescience.org/,https://www.axiomdatascience.com Conventions=IOOS-1.2, CF-1.6, ACDD-1.3, NCCSV-1.2 defaultDataQuery=wind_speed_qc_agg,relative_humidity_qc_agg,wind_from_direction,air_temperature_qc_agg,wind_from_direction_qc_agg,lwe_thickness_of_precipitation_amount_cm_time_sum_over_pt1h,air_temperature,lwe_thickness_of_precipitation_amount_cm_time_sum_over_pt1h_qc_agg,z,wind_speed,time,relative_humidity,surface_snow_thickness_qc_agg,surface_snow_thickness&time>=max(time)-3days Easternmost_Easting=-163.644 featureType=TimeSeries geospatial_lat_max=64.891 geospatial_lat_min=64.891 geospatial_lat_units=degrees_north geospatial_lon_max=-163.644 geospatial_lon_min=-163.644 geospatial_lon_units=degrees_east geospatial_vertical_max=0.0 geospatial_vertical_min=0.0 geospatial_vertical_positive=up geospatial_vertical_units=m history=Downloaded from Imiq - Hydroclimate Database and Data Portal at id=111523 infoUrl=https://sensors.ioos.us/#metadata/111523/station institution=UAF Water and Environmental Research Center (WERC) naming_authority=com.axiomdatascience Northernmost_Northing=64.891 platform=fixed platform_name=Blueberry Hill (Imiq: 962) platform_vocabulary=http://mmisw.org/ont/ioos/platform processing_level=Level 2 references=http://ine.uaf.edu/werc/,, sourceUrl=http://ine.uaf.edu/werc/ Southernmost_Northing=64.891 standard_name_vocabulary=CF Standard Name Table v72 station_id=111523 time_coverage_end=2013-07-09T12:00:00Z time_coverage_start=1999-07-28T23:00:00Z Westernmost_Easting=-163.644

The East Asian market for raspberries, blackberries, blueberries, and cranberries was estimated at $651M in 2024, rising by 13% against the previous year. The total consumption indicated resilient growth from 2012 to 2024: its value increased at an average annual rate of +6.4% over the last twelve years. The trend pattern, however, indicated some noticeable fluctuations being recorded throughout the analyzed period. Based on 2024 figures, consumption increased by +109.4% against 2012 indices.

About this dataset

Context

The dataset illustrates the median household income in Blueberry township, spanning the years from 2010 to 2021, with all figures adjusted to 2022 inflation-adjusted dollars. Based on the latest 2017-2021 5-Year Estimates from the American Community Survey, it displays how income varied over the last decade. The dataset can be utilized to gain insights into median household income trends and explore income variations.

Key observations:

From 2010 to 2021, the median household income for Blueberry township increased by $9,929 (16.10%), as per the American Community Survey estimates. In comparison, median household income for the United States increased by $4,559 (6.51%) between 2010 and 2021.

Analyzing the trend in median household income between the years 2010 and 2021, spanning 11 annual cycles, we observed that median household income, when adjusted for 2022 inflation using the Consumer Price Index retroactive series (R-CPI-U-RS), experienced growth year by year for 5 years and declined for 6 years.

https://i.neilsberg.com/ch/blueberry-township-mn-median-household-income-trend.jpeg" alt="Blueberry Township, Minnesota median household income trend (2010-2021, in 2022 inflation-adjusted dollars)">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

Years for which data is available:

• 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021

Variables / Data Columns

• Year: This column presents the data year from 2010 to 2021
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific year
• YOY Change($): Change in median household income between the current and the previous year, in 2022 inflation-adjusted dollars
• YOY Change(%): Percent change in median household income between current and the previous year

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Blueberry township median household income. You can refer the same here

Korea Consumer Price Index (CPI): Commodities: AM: AP: Fruits: Blueberry data was reported at 95.760 2015=100 in Jun 2018. This records an increase from the previous number of 94.980 2015=100 for May 2018. Korea Consumer Price Index (CPI): Commodities: AM: AP: Fruits: Blueberry data is updated monthly, averaging 97.660 2015=100 from Jan 2015 (Median) to Jun 2018, with 42 observations. The data reached an all-time high of 103.890 2015=100 in Jan 2016 and a record low of 88.170 2015=100 in Jul 2016. Korea Consumer Price Index (CPI): Commodities: AM: AP: Fruits: Blueberry data remains active status in CEIC and is reported by Statistics Korea. The data is categorized under Global Database’s Korea – Table KR.I021: Consumer Price Index: Special Groups: 2015=100.

The Kazakh market for raspberries, blackberries, blueberries, and cranberries shrank to $51M in 2024, remaining constant against the previous year. In general, the total consumption indicated a temperate increase from 2012 to 2024: its value increased at an average annual rate of +3.2% over the last twelve years. The trend pattern, however, indicated some noticeable fluctuations being recorded throughout the analyzed period. Based on 2024 figures, consumption increased by +59.0% against 2015 indices.

In phytophagous insects, adult attraction and oviposition preference for a host plant is often positively correlated with their immature performance; however, little is known how this preference-performance relationship changes within insect populations utilizing different host plants. Here, we investigated differences in the preference and performance of two populations of a native North American frugivorous insect pest, the plum curculio (Conotrachelus nenuphar) ‒ one that utilizes peaches and another that utilizes blueberries as hosts ‒ in the Mid-Atlantic United States. For this, we collected C. nenuphar adult populations from peach and blueberry farms and found that they exhibited a clear preference for the odors of, as well as an ovipositional preference for, the hosts they were collected from, laying 67-83% of their eggs in their respective natal hosts. To measure C. nenuphar larval performance, a fitness index was calculated using data on larval weights, development, and survival rate from egg to fourth instars when reared on the parent’s natal and novel hosts. Larvae of C. nenuphar adults collected from peach had high fitness on peach but low fitness when reared on blueberry. In contrast, larvae from C. nenuphar adults collected in blueberry had high fitness regardless of the host they were reared on. In this study, we show that utilizing a novel host such as blueberry incurs a fitness cost for C. nenuphar from peaches, but this cost was not observed for C. nenuphar from blueberries, indicating that the preference-performance relationship depends on the particular insect population-host plant association.

Methods Insect and fruit sources In early spring of 2019 and 2021, overwintered C. nenuphar adults utilizing peach as their host were collected from peach orchards at the Rutgers Agricultural Research and Extension Center (RAREC) (latitude 39°31'7.99"N, longitude 75°12'21.99"W) in Bridgeton, New Jersey (USA) (Figure 1B). Peach orchards were located in an ecosystem largely consisting of managed agricultural land (primarily apple, peach, soy, and corn), deciduous forest, and hedgerows. Surrounding forest edges were home to several Rosaceous hosts such as crabapple and wild cherry, as well as wild blueberry, potential wild hosts of C. nenuphar (Maier, 1990). Similarly, overwintered C. nenuphar adults utilizing blueberries as their host were collected from blueberry fields at an organic blueberry farm in Hammonton, New Jersey (USA) (latitude 39°39’37.53”N, longitude 74°45’14.75”W) (Figure 1B). These blueberry fields were located in the New Jersey Pinelands National Reserve, an environment dominated by several species of pine trees. Wild blueberry, huckleberry, and wild cherry occur in the forested areas adjacent to the crop plantings and could potentially be used as wild hosts by C. nenuphar. Overall, the area surrounding the blueberry fields contained mostly Ericaceous wild hosts and other blueberry plantings. The peach and blueberry sites were separated by 41.39 km (Figure 1B). Conotrachelus nenuphar adults collected from these sites were used for all the following experiments. The collected adults were exclusively fed on the host plant of their origin. As a result, we collected adults from two populations with distinct origins (peach or blueberry). We chose to collect feral adults rather than adults reared from the laboratory because we were interested in the host preferences of the overwintered C. nenuphar adults, which would be difficult to produce under laboratory conditions. Overwintered adults are most ecologically relevant to our study than later generations because of their movement into the crop, which indicate that these adults make critical foraging decisions when choosing a host plant. All insects were collected using beat sheets or unbaited trunk traps (Lampasona et al., 2020), and kept in incubators at 25±1°C, 70±10% relative humidity and 16:8 light:dark cycle until used. Adult age was indeterminate since all insects were field collected, but based on the timing of captures, most insects were likely to be of the overwintered generation, and thus eclosed the previous year. All peach and blueberry flowers and fruits used for rearing insects and in experiments were collected from RAREC and the organic blueberry farm, as they were not sprayed with conventional insecticides. All samples were collected the week of experiments.

Olfactory preference of Conotrachelus nenuphar In 2019 and 2020, we collected 30 male and 30 female C. nenuphar adults from peaches and 30 male and 30 female C. nenuphar adults from blueberries from our two New Jersey locations (see above); for a total of 60 individuals for each sex and host plant. Collected insects were placed in incubators under the conditions described above for at least 72 h before olfactory trials began. Insects were additionally subjected to a 24-h starvation period with no food and only distilled water prior to testing. Olfactory bioassays were conducted in a 40-mm-diameter × 36-cm-long glass Y-tube olfactometer that had a 50° inside angle (Sigma Scientific LLC, Florida, USA) (Figure 2). The Y-tube was placed in a particle board box in a dark room lit only with a 20-W red LED light and maintained at approximately 25° during the insect’s scotophase. Incoming laboratory-grade air (Airgas Company, Vineland, New Jersey, USA) was pushed through one of two customized 4.5-L stainless steel crock pots, each with two openings allowing air to flow in and out of a glass chamber (Figure 2). Each pot held fresh cuttings of either peach or blueberry plants (odor source). Each odor source consisted of 300 g of flowers and leaves or 600 g of fruit and leaves (all leaves collected from same plant as flowers or fruit) for each testing period and subsequently connected by tubing to an arm of the Y-tube. The airflow was modulated by an inline flowmeter (Gilmont Instr., Barnant Co., Barrington, Illinois, USA) set to 12 L/min to deliver 6 L/min to the olfactometer arm. Glass components of the Y-tube were cleaned with 70% ethanol and air dried between each replicate, and the left/right position of each basin was swapped to mitigate potential directional bias. Individual C. nenuphar adults were transferred using featherweight forceps and placed in the Y-tube specimen adapter, which was then attached to the Y-tube. After attachment, a stopwatch was started. If the insect spent 60 seconds in either arm, or after 12 minutes had elapsed (whichever came first), the timer was stopped. If the insect spent 60 seconds in an arm, it was considered a “choice” for the odor proximal to that arm and was recorded as such. If, after 12 minutes the insect did not spend 60 seconds in either arm, the insect was placed in a “no choice” category and removed. Insects that did not make a choice were excluded from the statistical analysis. All individuals were used only once for an experiment and new plant material was used for each experiment.

2.3 Oviposition preference of Conotrachelus nenuphar In 2020, we used fresh fruit to test for C. nenuphar oviposition preference between peach and blueberry in the laboratory. Small sections of peach and blueberry branches were thinned to one peach or five blueberries free of visible insect damage. Each branch section was then cut, inserted into soaked floral foam, and placed inside a mesh 30.5 × 30.5 × 30.5-cm insect rearing cage (BioQuip Products Inc., Rancho Dominguez, California, USA). In each cage, we alternated the left/right placement of the fruit between an equal number of replicates to mitigate directional bias. Insects were collected from our New Jersey sites and maintained in the laboratory as described above. Twenty-three C. nenuphar male/female pairs collected from peach, and 23 pairs collected from blueberry were placed inside the cages (one pair per cage). Each caged pair was provided with both one peach cutting and one blueberry cutting as a choice test. In addition, 10 pairs were provided only with one host as a no-choice check and 10 extra fruit cuttings were held in cages with no insects as “untreated” controls to determine if field oviposition had occurred but had gone unnoticed. Prior to the experiment, individual male/female pairs were given a 24-hour starvation period in microcentrifuge tubes. Following, C. nenuphar pairs were introduced into the cages and allowed 48 hours to oviposit freely on either host, after which all insects and fruit were removed, and the number of oviposition scars on each fruit was counted.

Offspring performance of Conotrachelus nenupharIn 2019, we thinned 60 blueberry and 60 peach branches down in the field so that each branch held only three peaches or 10 blueberries each. These branches were covered with a sleeve netting made of 5-gallon paint strainer bags and secured at the base of the branch to prevent wild insects from colonizing the fruit before we introduced the C. nenuphar adults. Conotrachelus nenuphar adults were collected from peach trees and blueberry bushes during the week of 20 May 2019, as described above, and kept in 946-ml plastic deli containers with fruit collected from blueberry fields or peach orchards. Insects collected from peach and blueberry were not co-mingled and were grouped into male/female pairs and placed in microcentrifuge tubes for a 24-hour starvation period. Insects were then moved to the sleeve cages on their respective outdoor hosts. Mating occurred at any point after introduction of males and females, although since they were wild-caught, it was possible they had already mated. As such, inclusion of the males was only to ensure mated status during the experiment. A total of 60 C. nenuphar adult pairs collected from blueberry were individually placed on blueberry branches (1 pair per branch), and 60 pairs were placed individually on peach branches. This was done over a 3-week period using 20 pairs/week for the first

Abbreviations used: WC  =  WKY corn-fed, WBB  =  WKY blueberry-fed, SC  =  SHRSP corn fed, SBB  =  SHRSP blueberry-fed, GFR  =  glomerular filtration rate, RBF  =  renal blood flow, RVR  =  renal vascular resistance, KW  =  kidney weight, Cr  =  creatinine, FENa  =  fractional excretion of sodium.*p≤0.05 vs. WC;#p≤0.05 vs. SC;$p≤0.05 vs. SBB.

The Central Asian market for raspberries, blackberries, blueberries, and cranberries rose modestly to $79M in 2024, surging by 2.4% against the previous year. The total consumption indicated notable growth from 2012 to 2024: its value increased at an average annual rate of +3.1% over the last twelve years. The trend pattern, however, indicated some noticeable fluctuations being recorded throughout the analyzed period. Based on 2024 figures, consumption increased by +18.5% against 2022 indices.

After three years of growth, the West African market for raspberries, blackberries, blueberries, and cranberries decreased by -5.4% to $8.7M in 2024. The total consumption indicated a moderate expansion from 2012 to 2024: its value increased at an average annual rate of +4.5% over the last twelve years. The trend pattern, however, indicated some noticeable fluctuations being recorded throughout the analyzed period. Based on 2024 figures, consumption increased by +79.9% against 2016 indices.

This study demonstrates the application of multi-temporal Normalized Difference Vegetation Index (NDVI) analysis and red-band spectral signatures from Sentinel-2 imagery to map the distribution of invasive highbush blueberry (Vaccinium corymbosum) within Richmond Nature Park, British Columbia. Located in the Lulu Island Bog, this critical peat ecosystem faces significant ecological threats from invasive species that disrupt native vegetation communities and alter hydrological processes. By analyzing seasonal NDVI variations across multiple time periods (February-November 2023) and incorporating red-band dominance filters to capture characteristic fall senescence patterns. In this study a habitat suitability model is developed that effectively predicts blueberry presence within the study area. The methodology yielded a strong positive correlation between predicted suitability scores and field-verified blueberry coverage (r = 0.81, p < 0.001), with the model explaining 65.5% of the variance in blueberry distribution patterns (adjusted R² = 0.64). September-October NDVI differences emerged as particularly powerful indicators of blueberry presence, capitalizing on distinctive fall coloration absent in native bog species. This cost-effective approach using freely available medium-resolution satellite imagery offers conservation managers a valuable tool for identifying priority intervention areas without requiring expensive high-resolution data sources. This study’s findings contribute to broader conservation efforts aimed at preserving endangered peat bog ecosystems and their critical carbon sequestration functions in the face of increasing climate change concerns.

The market for raspberries, blackberries, blueberries, and cranberries in Australia and Oceania stood at $1.2B in 2024, picking up by 7% against the previous year. The total consumption indicated a buoyant expansion from 2012 to 2024: its value increased at an average annual rate of +5.3% over the last twelve years. The trend pattern, however, indicated some noticeable fluctuations being recorded throughout the analyzed period. Based on 2024 figures, consumption increased by +86.0% against 2012 indices.