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Record W2281266512 · doi:10.14288/1.0106797

The economic structure of tree fruit farms in the South Okanagan Valley, British Columbia

2012· article· en· W2281266512 on OpenAlexaboutno aff
Dennis William Ware

Bibliographic record

VenuecIRcle (University of British Columbia) · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyTree (set theory)AgroforestryForestryBiologyMathematics

Abstract

fetched live from OpenAlex

Tree fruit farms in the south Okanagan Valley are characterized by a high degree of specialization. Over 95 per cent of the irrigated land of these farms is in orchard. The farms are small in area and few livestock are kept. Depending on their location, the orchards may be classified into three main "types, namely, apple, stone fruit and combination fruit farms. To provide an insight into the structure, production techniques, and problems of the orchardists, 165 farm business records which had been obtained from the growers in the years 1949 and 1950, were studied and analysed. Also an endeavour was made to answer the question, do the majority of the orchards supply full employment and an adequate income for the operators?. The average capital investment on these farms was over $21,000. On each type of farm, orchard land accounted for more than 65 per cent of the total farm investment. Excluding the value of the farm dwelling, machinery and equipment made up the second largest capital investment. Apple farms in the south Okanagan Valley averaged 17 acres in area, of which 15 acres were in orchard; stone fruit farms averaged 11 acres, of which 9 acres were in orchard; and combination fruit farms had an average total acreage of 14 acres, of which approximately 12 acres were in orchard. The average total cash receipts for these years were $7,276 for the apple farmers; $5,551 for the stone fruit farmer; and $6,953 for the combination fruit farmer. On the apple farms 69 per cent of the total cash receipts were derived from the sale of apples; on the stone fruit farms 75 per cent derived from the sale of stone fruits; and on the combination fruit farms, stone fruits provided per cent, and apples 34 per cent of the total cash receipts. Labour was the largest single item of expense on each type of orchard, varying from 49 per cent to 54 per cent of the total current expenses. The average net income on the apple farms was $2,346; on the stone fruit farms, $2,783; and on the combination fruit farms, $2,720. The factors determining the total output of fruit in any one year include the number of trees, their age distribution, the variety of fruit grown, the amount of cultural care, the prevalence of disease and pests, and the weather. Although the year to year production of all fruits in the valley is erratic, the trend in total production has been upward. The average output of apricots for the three year period, 1947-1949, was 110 per cent greater than the average output for the three year period, 1939-1941. Comparing the same periods, the total yield of cherries increased by 110 per cent, peaches by 141 per cent, pears by 89 per cent, and apples by 44 per cent. Since 1930 the average yield per acre of apple, pear, plum and prune trees has shown a steady increase, whereas the yield per acre of apricot, cherry and peach trees has varied widely from year to year. The tree population of the south Okanagan has been steadily increasing, but the relative position of the various kinds of tree fruits has changed. In 1925 apple trees made up 66 per cent of the total number of trees; in 1950 they accounted for 33 per cent of the total tree inventory. On the farms studied, the majority of the apple trees were over 20 years of age. Most of the apricot, peach, plum, prune, and pear trees were less than 15 years of age. On 94 orchards 16 per cent of the apricot, 15 per cent of the cherry, 31 per cent of the peach, 10 per cent of the plum and prune, and 4 per cent of the pears were killed in the winter of 1949-50. Considering acreage trends, the number of non-bearing trees, and the number of trees to be removed, as well as the average yield, it would appear that for the next few years the general trend in south Okanagan Valley apple, apricot, plum, prune, and pear production will be upward, while the trend of peach and cherry production will be downward. In general the domestic market takes the Okanagan stone fruit and pear crop but the apple grower is dependent to a large extent upon the export market. Present deterioration of the apple market presages a trend to further increases in the plantings of stone fruit and pear trees. Volume of production, yield, and the degree of diversification appear to influence the size of labour earnings. The average total amount of labour required to produce an acre of apples was 253 hours, an acre of apricots 469 hours, an acre of cherries 608 hours, an acre of peaches 386 hours, an acre of prunes 222 hours, and an acre of pears 350 hours per annum. Although the labour prior to harvest was spread over many months, the total pre-harvest time was less than that required for harvesting the fruit, except in the cases of peach, apple and pear trees. On studying the influence of yield on labour requirements, it was found that a doubling of the yield per acre of peaches resulted in an increase of the harvesting time required by 57 per cent. For pear trees doubling of the yield increased the harvest requirements by 75 per cent. From an economic and social viewpoint, it is suggested that a desireable farm organization for the area would be the two family farm. Such a unit, under long run yield expectations and 1949 cost-price relationships, would fully employ two men and provide them with labour earnings of over $3,000 per man, yearly.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.006
Science and technology studies0.0020.001
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.006
GPT teacher head0.162
Teacher spread0.156 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

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