Análise conjunta de regressões : ajustamento e zonagem agrícola

A Análise conjunta de regressões, ACR, é uma técnica utitilizada para estudar a interação gentipo x ambiente baseada em regressões. Nesta técnica ajusta-se uma regressão linear por cultivar. Nestas regressões a variável controlada é o índice ambiental que mede a produtividade dos vários ambientes. Nas culturas anuais, os ambientes compreendem aos pares (local, ano). Os valores dos índices ambientais e dos coeficientes das regressões são ajustados simultaneamente. Até agora a ACR tem sido aplicada a uma única cultura de cada vez. Neste trabalho vamos procurar ultrapassar essa limitação através da modelação dos logaritmos dos índices ambientais tendo-se desenvolvido um modelo da forma: zi, j  v  l j  j , i  1,...,n, J  1,...,n onde zi , j é o logaritmo do índice ambiental para o i-essimo ambiente na j  essima cultura , v um valor médio geral , li j  essimo cultivar. o efeito do i  essimo local e  j o efeito do Ao utilizar esta modelação, os locais corresponderão a estações experimentais de forma a poder-se ter várias culturas no mesmo local. Ora, as estações experimentais são escolhidas por forma a serem representativas das regiões onde estão implantadas. Assim, os índices ambientais correspondentes às várias estações experimentais e, consequentemente, às respetivas regiões, pudesse ser utilizados para agrupar regiões contíguas com índices semelhantes obtendo-se assim, um elemento interessante para a Zonagem agrícola no que diz respeito às culturas que se trabalha. Pode-se ainda procurar uma Zonagem para grupos de cultivares. Por exemplo, adiante trabalharemos com dados da cevada e trigo os quais são cereais. ABSTRACT: Joint Regression Analysis, JRA, is one of the techniques for the study of genotypeXenvironment interaction based on the use of regressions .In JRA a linear regression of the yields of each cultivar on a controlled variable, the environment index ,is adjusted .The index miss erasures the productivity of each environment .In yearly cultures the environments correspond to the pairs (location ,years) .These indexes and the correlation coefficients are adjusted simultaneously. Up to now JRA has been applied to single crops .Now we try to overcome this restriction through modeling of the logarithms of the environmental indexes .We developed a model τ i , j = v + l j +λ j , i = 1,..., b, J = 1,...J where τ i , j is the logarithm of the environmental index for the i-th environment and the j-th crop , v is the general mean , li is the effect of the i-th environment and λ j is the effect of the j-th crop . When applying this model the location will correspond to experimental situations in order to have several crops in the same locations .Now experimental stations are chosen to be representative of the regions in which they are located .Then the l1 ,..., lb can be used to group contiguous regions with similar location effects .We thus get an useful tool for Agricultural Zoning for the crops we used or, even, for the group to which those crops belong . For instance we worked with barley and wheat that are cereals.

Effects of pitch area-restrictions on tactical behavior, physical and physiological performances in soccer large-sided games

The aim of this study was to identify how pitch area-restrictions affects the tactical behavior, physical and physiological performances of players during soccer large-sided games. A 10 vs. 9 large-sided game was performed under three experimental conditions: (i) restricted-spacing, the pitch was divided into specific areas where players were assigned and they should not leave it; (ii) contiguous-spacing, the pitch was divided into specific areas where the players were only allowed to move to a neighboring one; (iii) free-spacing, the players had no restrictions in space occupation. The positional data were used to compute players’ spatial exploration index and also the distance, coefficient of variation, approximate entropy and frequency of near-in-phase displacements synchronization of players’ dyads formed by the outfield teammates. Players’ physical and physiological performances were assessed by the distance covered at different speed categories, game pace and heart rate. Most likely higher values were found in players’ spatial exploration index under free-spacing conditions. The synchronization between dyads’ displacements showed higher values for contiguous-spacing and free-spacing conditions. In contrast, for the jogging and running intensity zones, restricted-spacing demanded a moderate effect and most likely decrease compared to other scenarios (~20-50% to jogging and ~60-90% to running). Overall, the effects of limiting players’ spatial exploration greatly impaired the co-adaptation between teammates’ positioning while decreasing the physical and physiological performances. These results allow for a better understanding of players’ decision-making process according to specific task rules and can be relevant to enrich practice task design, such that coaches acknowledge the differential effect by using specific pitch-position areas restrictions.

Provenance of Holocene beach sand in the Western Iberian

Detrital zircons from Holocene beach sand and igneous zircons from the Cretaceous syenite forming Cape Sines (Western Iberian margin) were dated using laser ablation – inductively coupled plasma – mass spectrometry. The U–Pb ages obtained were used for comparison with previous radiometric data from Carboniferous greywacke, Pliocene–Pleistocene sand and Cretaceous syenite forming the sea cliff at Cape Sines and the contiguous coast. New U–Pb dating of igneous morphologically simple and complex zircons from the syenite of the Sines pluton suggests that the history of zircon crystallization was more extensive (ca 87 to 74 Ma), in contrast to the findings of previous geochronology studies (ca 76 to 74 Ma). The U–Pb ages obtained in Holocene sand revealed a wide interval, ranging from the Cretaceous to the Archean, with predominance of Cretaceous (37%), Palaeozoic (35%) and Neoproterozoic (19%) detrital-zircon ages. The paucity of round to subrounded grains seems to indicate a short transportation history for most of the Cretaceous zircons (ca 95 to 73 Ma) which are more abundant in the beach sand that was sampled south of Cape Sines. Comparative analysis using the Kolmogorov–Smirnov statistical method, analysing sub-populations separately, suggests that the zircon populations of the Carboniferous and Cretaceous rocks forming the sea cliff were reproduced faithfully in Quaternary sand, indicating sediment recycling. The similarity of the pre- Cretaceous ages (>ca 280 Ma) of detrital zircons found in Holocene sand, as compared with Carboniferous greywacke and Pliocene–Pleistocene sand, provides support for the hypothesis that detritus was reworked into the beach from older sedimentary rocks exposed along the sea cliff. The largest percentage of Cretaceous zircons (