Market potential and value‐added opportunities of cold‐hardy berries and small fruits in the Intermountain West, USA
Bibliographic record
Abstract
Novel cold-hardy berries and small fruits represent an opportunity for growers in the Intermountain West, USA, as the harsh environment is not suited for other common berries and small fruits. This study analyzed the fresh market and value-added potential of haskap berries (Lonicera caerulea), saskatoon berries (Amelenchier alnifolia), and dwarf sour cherry (DSC) fruit (Prunus x kerrasis) by instrumental and consumer studies. Fresh and 2-week stored haskap (cv. Aurora), saskatoon (Lee 3), and DSC (Romeo) were measured for fruit weight, flesh firmness, bulk titratable acidity, pH, and soluble solid content. Participants (n = 115) in at-home sensory tests scored these fruits for overall liking (OL, 9-point hedonic scale), purchase intent (PI, 5-point scale), and willingness-to-pay (WTP, 5-point scale). Ten participants further shared insight on these fruits in focus groups. Instrumental testing found a significant decrease in flesh firmness for 2-week stored haskap, but the consumers' OL was still comparable to fresh haskap. The fresh and 2-week stored haskap received significantly higher OL, PI, and WTP scores (7.7 ± 1.0, 3.8 ± 1.0, and $3.7 ± 1.0; 7.7 ± 1.2, 3.8 ± 1.1, and $3.7 ± 1.0, respectively) compared to saskatoon (6.1 ± 1.8, 2.8 ± 1.1, and $3.0 ± 0.9, respectively) and DSC (5.6 ± 2.2, 2.5 ± 1.2, and $3.1 ± 1.0, respectively) (α = 0.05). The focus groups indicated that participants want to support local produce. The participants expressed interest in fresh unprocessed haskap berries, but preferred saskatoon and DSC in different value-added formats. Hence, this study concluded that there is an untapped fresh-market potential for haskap berries and there are value-added opportunities to extend the sale season and improve the palatability of saskatoon and DSC. PRACTICAL APPLICATION: This research has examined consumer perception of three species of novel small fruits by determining fresh-market potential and linking this to the opportunity for value-added product development. For haskap berries, the study not only indicated fresh market potential, but for the cultivar Aurora, consumer liking was not meaningfully altered by 2 weeks of cold storage. These results are meaningful because they will assist growers in the Intermountain West with market planning, including the possibility of formulating products that utilize these novel crops. This study provides growers the opportunity to diversify their income stream by utilizing local produce.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".