The Effect of Deficit Irrigation and Crop Load on Leaf and Fruit Nutrition of Fertigated ‘Ambrosia’/‘M.9’ Apple
Bibliographic record
Abstract
Mature, fruiting ‘Ambrosia’/‘M.9’ apple [ Malus × sylvestris (L.) Mill. var. domestica (Borkh.) Mansf.] trees were subjected over three growing seasons to a split-plot experimental design involving four irrigation main plot treatments and three subplot crop load treatments with six replicates. This semiarid production region is traditionally irrigated 01 May to 01 Oct. during which time an average of ≈ 15 cm of precipitation occurs. Irrigation treatments were applied through 2 × 4 L⋅h −1 emitters per tree and included I1: daily application of 100% evapotranspiration (ET); or I2: 50% daily ET; or I3: 50% ET applied to one side; and I4: 50%, 25%, or 18% ET-application, applied every second day, 2007–09, respectively. Crop load treatments were imposed annually ≈4 to 5 weeks after full bloom to create low (2.5, 3, and 3.75 fruits/cm 2 trunk cross-sectional area (TCSA), medium (4.5, 6, and 7.5 fruits/cm 2 TCSA), and high crop loads (9, 12, and 15 fruits/cm 2 TCSA), 2007–09, respectively. Leaf and fruit nutrient concentration was affected more by crop load than by any deficit irrigation strategy. Increased crop load increased concentrations of leaf nitrogen (N), calcium (Ca), and fruit Ca in 2 of 3 years and consistently decreased concentrations of leaf and fruit phosphorus (P) and potassium (K) and, in 2 of 3 years, fruit boron (B). Reductions in seasonal water applications (as with I4) reduced leaf P in 2 of 3 years. But, when significant, (usually only 1 of 3 year) increased fruit Ca, magnesium (Mg), P, K, and B concentrations. Crop load also had a dominant effect on fruit nutrient removal rates expressed as kilograms per hectare. High crop load increased removal of all measured nutrients in most years. In contrast, imposition of deficit irrigation strategies often (2 of 3 years) reduced fruit P, Mg, and B removal rates but had little effect on N, Ca, and K. Cumulative evidence suggests that deficit irrigation applied to N, P, K, and B fertigated high density ‘Ambrosia’ apple orchards in combination with crop load reduction to maintain fruit size should usually not create additional nutrient problems. However, low fruit Ca concentrations may occur if the crop is very low. Fertigation of 20 g K/tree/year was insufficient for older trees because inadequate K occurred in all treatments by the third year.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".