Path Analysis for Factor Affecting the 305- Day Milk Yield of Holstein Cows

Akıllı, Aslı; Kul, Ertuğrul; Atil, Hülya

doi:10.55507/gopzfd.1195147

Cited by 1 publication

(1 citation statement)

References 24 publications

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“…Furthermore, it contributes to a comprehensive understanding of adaptive thermal comfort in dynamic environments [43]. (4) Animal Husbandry Studies: in the realm of animal husbandry, path analysis proves beneficial for exploring direct and indirect effects within the context of lactation number, calving season, dry period, service period, and insemination number in Holstein cows [44]. (5) Agricultural Studies: in agricultural research, path analysis plays a pivotal role in establishing causal relationships between vegetation indices and soybean grain yield based on in situ observations [45].…”

Section: Introductionmentioning

confidence: 99%

Application of Path Analysis and Remote Sensing to Assess the Interrelationships between Meteorological Variables and Vegetation Indices in the State of Espírito Santo, Southeastern Brazil

Senhorelo,

Sousa,

Santos

et al. 2024

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Utilizing path analysis, we examined the interconnectedness among six meteorological variables. Among these, three pertain to energy conditions—air temperature, net solar radiation, and reference evapotranspiration (ET0)—while the others are associated with hydrological conditions: precipitation, relative humidity, and water deficiency. These variables were assessed across five distinct temporal delay levels to understand their influences on the normalized difference vegetation Index (NDVI) and enhanced vegetation index (EVI) within grassland areas situated in the state of Espírito Santo, southeastern Brazil. The images underwent processing using analytical algorithms and a geographic information system (GIS). The direct and indirect impacts of these variables on the NDVI and EVI exhibited remarkable similarity across varying temporal delays and geographic regions. Meteorological variables explained over 50% of the observed variation in both indices, occasionally even reaching levels of 70%. Temperature and relative humidity primarily exerted direct effects on the indices. Conversely, precipitation exhibited indirect effects on the indices, often in conjunction with other hydrological variables. ET0 demonstrated a direct effect on the vegetation indices, particularly after a delay of 32 days. Solar radiation and water deficiency displayed direct effects up to the 32-day mark, implying that vegetation responds more promptly to these variables. The proposed methodology enabled a consistent and stable assessment of the direct and indirect effects of meteorological variables on vegetation indices.

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