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Record W4229445809 · doi:10.5539/jas.v14n6p206

The Assessment of Four Crop-Based Cropping System Productivity, Nutrient Uptake and Soil Fertility With Existing Cropping Systems

2022· article· en· W4229445809 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Agricultural Science · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Science and Fertilization
Canadian institutionsnot available
Fundersnot available
KeywordsCroppingCropping systemAgronomySoil fertilityRandomized block designCropIrrigationNutrient managementFertilizerProductivityMathematicsAgricultural scienceAgricultureAgroforestryEnvironmental scienceBiologySoil waterEconomics

Abstract

fetched live from OpenAlex

Sustainable crop production through intensification of crops in cropping system is a global important issue to ensure food security, human and soil nutrition, poverty alleviation, and job opportunity creation. Rabi crop (mustard/lentil)-Jute cropping system and transplanted (T) Aman rice-Boro (T. Boro) rice cropping system are the traditional cropping systems in Low Ganges River Floodplain (AEZ-12) soils of Bangladesh. Jute and T. Aman rice are usually cultivated in summer season, but the T. Boro rice is cultivated in winter season. Jute and T. Boro rice are highly cost consuming crops due to need more irrigation, labors and fertilizer etc. T. Boro rice and jute are easily replaced by a short duration of mungbean and T. Aus rice in the existing cropping system. Hence field trial on different cropping systems were conducted in Regional pulses Research Station (RPRS), BARI, Madaripur and the adjacent farmers’ field of RPRS during 2013-14 and 2014-15 to compare and evaluate the four crop-based cropping systems with existing cropping systems based on system productivity, nutrient uptake and balance, profitability and sustaining soil fertility. The experiment was planned with six treatments comprising three of four crop-based cropping systems and three existing traditional cropping systems. The treatments were FCS1 (Mustard-Mungbean-T. Aus rice-T. Aman rice), FCS2 (Lentil-Mungbean-T. Aus rice-T. Aman rice), FCS3 (Fieldpea-Mungbean-T. Aus rice-T. Aman rice), ECS1 (Mustard-Jute), ECS2 (Lentil-Jute) and ECS3 (T. Boro rice-T. Aman rice) following randomized complete block design with three dispersed replications. As per results, the greater system productivity (rice equivalent yield: 16368 kg ha-1) was significantly obtained from FCS2 than the other system treatments. The FCS2 treatment exhibited the highest percent increment of rice equivalent yield (REY) over existing cropping system ECS1, ECS2 and ECS3 was 322%, 234% and 84.1%, respectively. Also higher %REY increment of FCS2 was 20.3% and 14.5% over the other four crop-based cropping systems FCS1 and FCS3. Production efficiency was highest in same FCS2 treatment. Land use efficiency increment was observed higher in Fieldpea-Mungbean-T. Aus rice-T. Aman rice cropping system. Total nutrient (N, P, K, S, Zn, B) uptakes and nutrient balance were positively influenced among the cropping systems, but both were showed inconsistent trends. The result of postharvest soil exhibited higher organic carbon (8.78 g kg-1) and total N content (0.74 g kg-1) was in FCS2 treatment. The FCS2 was also economically profitable and viable as compared to other cropping systems due to having higher gross return, gross margin and benefit cost ratio (2.48). The FCS3 was the second economically profitable and viable system as compared to other cropping systems. Intensification and diversification of crops from two to four crop-based cropping systems lead to increase the system productivity, profitability, and sustaining soil fertility. Results suggest that lentil-Mungbean-T. Aus rice-T. Aman rice followed by Fieldpea-Mungbean-T. Aus rice-T. Aman rice cropping system can practice in the experimental area for positive change the farmers’ livelihoods. This finding may be potential for the area where there is no practice of improving four crop-based cropping systems.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.971
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0030.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.035
GPT teacher head0.247
Teacher spread0.212 · 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