Results 61 to 70 of about 9,471 (259)
Testing the Marketing Performance of German Wheat Farmers
Agribusiness, EarlyView.ABSTRACT This paper analyses the marketing performance of wheat farmers in Germany. Wheat sales data from 465 individual farms over a 12‐year period are used to test against different market benchmarks. Market benchmarks are constructed by simulating passive trading agents using regional wheat prices.
Franziska Potts, Jens‐Peter Loy
wiley +1 more source
Does Participating in Agricultural Global Value Chains Promote Agricultural Growth?
Agribusiness, EarlyView.ABSTRACT This study examines the relationship between GVC participation and agricultural value‐added growth in 43 countries over the period 1995–2022. In contrast to prior literature, we disaggregate the agricultural sector into four sub‐sectors namely crop cultivation, animal production, forestry and fishing.
Taner Turan +2 more
wiley +1 more source
Stock assessment of Huso huso (Linnaeus, 1754) in the south Caspian Sea
Majallah-i ̒Ilmī-i Shīlāt-i Īrān, 2018 We evaluated the stocks of Huso huso in the south Caspian Sea along Iranian coasts using data on different population parameters such as length, age, weight, catch and catch per unit effort changes. The study covered data from 1971 to 2003.
M. Moghim; H. Fazli; D. Ghaninezhad
doaj
Ciencias Marinas, 2001 We analyzed the catch and effort data for the brown shrimp (Farfantepenaeus californiensis) fishery over 22 years. We used a biomass dynamic model in a stochastic version to analyze the catch-per-unit effort of the trawl fishery in the Gulf of ...
E Morales-Bojórquez +2 more
doaj +1 more source
STUDIES ON THE FORMATION OF SHOAL OF KIDAI (TAIUS TUMIFRONS) BY THE CATCH PER UNIT OF EFFORT
NIPPON SUISAN GAKKAISHI, 1960 Distribution of catch per unit of effort does not fit in Poisson distribution premised the independent action of individual, because many fishes seem to form their shoals respectively. But, it is asumed that the shoal constructed with individuals of fish will fluctuate itself and we are able to estimate that the distribution of number of shoal in some ...
openaire +2 more sources
Advanced Intelligent Discovery, EarlyView.This paper presents a computer vision (deep learning) pipeline integrating YOLOv8 and YOLOv9 for automated detection, segmentation, and analysis of rosette cellulose synthase complexes in freeze‐fracture electron microscopy images. The study explores curated dataset expansion for model improvement and highlights pipeline accuracy, speed ...
Siri Mudunuri +6 more
wiley +1 more source
Fishery knowledge-guided machine learning for spatial prediction of catch-per-unit-effort
Ecological IndicatorsCatch per unit effort (CPUE) is a key indicator of fish stock abundance. However, CPUE estimates derived from fishery logbooks are highly susceptible to noise and missing entries, leading to systematic bias in abundance estimation. To address this issue,
Runze Shi +5 more
doaj +1 more source
Demeter: Journal of Farming and AgricultureMotor and outboard boats are the main means by which fishersmen exploit the fisheries resources in these waters. The success of the catch and the efficiency of the fishermen's efforts are strongly influenced by various factors related to the characteristics of the boat, the fishing gear and the condition of the aquatic environment.
null Nurasri Mulyani +3 more
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Advanced Intelligent Discovery, EarlyView.Machine learning serves as a central engine for the intelligent characterization of two‐dimensional materials by integrating multimodal techniques, including optical microscopy, spectroscopy, electron microscopy, and scanning probe microscopy (SPM). This unified framework enables automated, high‐throughput, and quantitative extraction of structural ...
Zhi‐Long Cao, Jia‐Xu Yan
wiley +1 more source