Pemangkasan dan pemupukan tanaman buah jeruk siam dan buah naga sebagai fungsi perawatan tanaman dan pengendalian hama di Desa Pajagan, Kabupaten Sumedang, Jawa Barat
Bibliographic record
Abstract
Perawatan tanaman buah merupakan salah satu hal penting yang harus dilakukan untuk menjaga kesehatan dan produktivitas tanaman. Pemangkasan termasuk salah satu teknik pemeliharaan yang penting untuk dilakukan. Pemupukan berimbang dan mencukupi kebutuhan nutrisi tanaman juga termasuk salah satu cara menjaga kesehatan tanaman. Artikel ini membahas mengenai pemangkasan dan pemupukan dalam perannya sebagai cara perawatan tanaman dan dalam kontek pengendalian hama pada tanaman buah di Desa Pajagan, Kabupaten Sumedang, Jawa Barat. Materi disampaikan secara informatif dengan awalan teoritis dan dilanjutkan dengan praktik langsung pada tanaman. Pemangkasan dilakukan untuk mengontrol ukuran dan bentuk tanaman, mengoptimalkan penetrasi cahaya dan sirkulasi udara hingga dapat mengurangi kelembaban dan kepadatan bagian tanaman yang memiliki populasi hama tinggi atau bagian tanaman sakit. Pemupukan berdasarkan dosis rekomendasi dan tepat waktu aplikasi dilakukan untuk memenuhi kebutuhan nutrisi tanaman untuk proses pertumbuhan dan perkembangan. Pendampingan petani di Desa Pajagan harus dilakukan secara berkelanjutan agar dapat secara mandiri melaksanakan budidaya tanaman secara baik dan benar.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.026 | 0.007 |
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".