Spatial variability of rainfall and yield of maize in a semiarid region

Gurovich, Luis; Ramos, R.

doi:10.1016/0378-3774(85)90032-0

Cited by 3 publications

(2 citation statements)

References 25 publications

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“…Agricultural production in northern Iraq was investigated to be very much dependent on the occurrence of rainfall during October, November and December (Yussif & Farok, 1979). The effect of non-uniform distribution of rainfall on corn production was investigated in a semi-arid region of Chile (Gurovich & Ramos, 1985).…”

Section: Introductionmentioning

confidence: 99%

Regional classification for dryland agriculture in southern Iran

Sadeghi

Kamgar-Haghighi

Sepaskhah

et al. 2002

Journal of Arid Environments

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Section: Introductionmentioning

confidence: 99%

Regional classification for dryland agriculture in southern Iran

Sadeghi

Kamgar-Haghighi

Sepaskhah

et al. 2002

Journal of Arid Environments

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“…Similarly, the use of auto-covariance functions (WEBER and STAM 1988) assumes stationarity in the distributions of the data which is a strong assumption and difficuh to fulfill or even verify under actual situations. On the other hand, several examples of stochastical spatial dependence in the distributions of soil properties, crop yield, and their intervariable relations have been reported (BRESIFR et al 1981, GUROVICII and RAMOS 1985, CASSEL et al 1988, MORKOC et al 1985, DANCY and WEBSTER 1986, TRANGMAR et al 1987, SAMRA et al 1988a, b, 1989, 1990 It is evident from the above account that some alternative stochastie-eum-deterministie approach of exercising local control is required. In this paper, the application of such a method based on regionalized variable theory of intrinsic random functions of MATHERON (1973) is presented.…”

mentioning

confidence: 99%

Spatial Dependence of Check Plot Yield and Local Control

Samra

Anlauf²,

Richter³

1989

Plant Breeding

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For maximizing genetic gains, -with given resources, plant breeders generally conduct large but un-or inadequately-replicated field trials especially during early generation evaluations and population improvement programmes. Checks are often used to improve the precision of test plot comparisons. Ad-)ustn-ients by moving or weighted means etc. are, however, empirical or based on assumptions too diflicult to verily. An alternative stochastically best linear unbiased optimal locally weighted n-iethod of spatial prediction of micro-environmental heterogeneity indices of treatment plots was examined. Two checks used in an unreplicated evaluation of 1560 test lines of winter wheat expressed the micro-environmental variation in similar ways. About 46, 38 and 16 percent of the total variation in yield was a simple row and column effects, spatially dependent, and random errors, respectively. Optimal weights derived to simulate the micro-environmental heterogeneity indices were sensitive to the position of the test plot and thus provided a better local control. The model was validated, and prediction standard deviations of simulations computed.

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Spatial variability of groundwater solute concentrations at the water table under arable land and coniferous forest. Part 3: Field data for a coniferous forest and statistical analysis

Böttcher¹,

Strebel²

1988

J Plant Nutrition & Soil

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The spatial variability of groundwater solute concentrations at the water table beneath a fine to medium sandy soil (Gleyic Podzol) under a 45‐years old pine stand was investigated. Samples were taken within the first decimeter below the groundwater table at horizontal intervals of 0.5 m along a 30 m transect in between two rows of trees. Nitrate, sulfate, and aluminum concentrations and pH were determined and analyzed by geostatistical and spectral analysis methods. Semivariance analysis shows spatial dependence in the data (except for nitrate) up to ranges of between 1.7 and 3 m. Spectral analysis indicates periodic variations with a period of 4 ‐ 5 m. The periods for sulfate and aluminum are synchronous and 180° out‐of‐phase with the pH curve. The sulfate and aluminum maxima and pH minima correspond to areas within edges of the tree canopies (canopy drip). Differences in the acid input into the weakly buffering soil caused by the interception deposition of atmospheric constituents at the canopy result in a regular pattern in the concentrations of certain solutes in the uppermost groundwater. The variogram and spectrogram of the nitrate concentration indicate the presence of a trend. The cospectrogram for nitrate and pH has a peak that corresponds to synchronous short‐range (about 2 m) variations, i.e. a small‐scale correlation between nitrate concentration and pH.

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Spatial variability of rainfall and yield of maize in a semiarid region

Cited by 3 publications

References 25 publications

Regional classification for dryland agriculture in southern Iran

Regional classification for dryland agriculture in southern Iran

Spatial Dependence of Check Plot Yield and Local Control

Spatial variability of groundwater solute concentrations at the water table under arable land and coniferous forest. Part 3: Field data for a coniferous forest and statistical analysis

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