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Record W4403137496 · doi:10.3389/fagro.2024.1378339

Productivity of sorghum and millets under different in-field rainwater management options on soils of varying fertility status in Zimbabwe

2024· article· en· W4403137496 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFrontiers in Agronomy · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRice Cultivation and Yield Improvement
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSorghumRainwater harvestingProductivityAgronomySoil waterSoil fertilityEnvironmental scienceAgricultureFertilityAgricultural economicsAgroforestryBusinessAgricultural engineeringGeographyEconomicsBiologySoil scienceEngineeringEconomic growthEcologyPopulation

Abstract

fetched live from OpenAlex

Traditional cereal crops are important for food and nutrition security in rural communities of southern Africa, but their productivity is often constrained by low soil water largely linked to low seasonal rainfall and long intra-seasonal dry spells. Planting basins (PB), tied ridges (TR), and conventional ploughing (CP) were evaluated, over two cropping seasons (2020/2021 and 2021/2022), for their effects on sorghum [ Sorghum bicolor (L.), Moench], pearl millet [ Pennisetum glaucum (L.) R.Br.], and finger millet [ Eleusine coracana (L.) Gaertn] productivity on degraded (<0.4% soil organic carbon) and productive (>0.6% soil organic carbon) fields under rainfed conditions in Mbire (<450 mm rainfall year −1 ) and Mutasa (>800 mm rainfall year −1 ) districts in Zimbabwe. Field trials were established on degraded and productive field sites in each district, with sorghum, pearl millet, and finger millet either sown as monocrops or intercropped with cowpea. The experiments were laid out in a 2 × 3 × 3 factorial in a randomized complete block design (RCBD). The highest sorghum grain yield response of 2100 kg ha −1 was attained under PB on productive soils. Overall, PB and TR increased sorghum, finger millet, and pearl millet grain yields by 43% to 58% compared with CP. Growing sorghum, finger millet, and pearl millet on productive soils increased grain yields by 64%, 33%, and 43%, respectively, compared with degraded soils. Intercropping sorghum, pearl millet, and finger millet with cowpea increased cereal yields by between 23% and 42% over the sole crops. Rainwater use efficiency averaged 1 kg grain mm −1 on productive fields and 0.4 kg grain mm −1 on degraded fields. PB produced the highest net profit of $US408 on a productive field. Overall, production of sorghum and millets on productive soils gave positive economic returns irrespective of rainwater management option and cropping system. Conversely, 63% of the treatments on degraded soils recorded negative economic returns in both districts. We conclude that in-field rainwater management technologies combined with other agronomic practices like intercropping increase the productivity of sorghum and millets under rainfed conditions. However, degraded soils remain a challenge for the increased productivity of traditional cereal crops.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.429
Threshold uncertainty score0.154

Codex and Gemma teacher scores by category

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

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 head0.017
GPT teacher head0.225
Teacher spread0.208 · 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