2020
DOI: 10.3390/agronomy10081150
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Feeding Emitters for Microirrigation with a Digestate Liquid Fraction up to 25% Dilution Did Not Reduce Their Performance

Abstract: Irrigation with wastewater can strongly contribute to the reduction of water abstraction in agriculture with an especial interest in arid and semiarid areas. However, its use can have drawbacks to both soil and micro-irrigation systems, especially when the total solids in the wastewater are high, such as in digestate liquid fractions (DLF) from plant material. The aim of this study was thus to evaluate the performances of a serpentine shaped micro-emitter injected with a hydrocyclone filtered DLF (HF-DLF) from… Show more

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Cited by 4 publications
(3 citation statements)
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References 30 publications
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“…To overcome these issues, statistical analyses was conducted through a generalized linear mixed model (Glimmix procedure in SAS/STAT 9.; SAS Institute Inc., Cary, NC, USA). The model used was built for unbalanced designs (see Suardi et al, 2020 ; Bergonzoli et al, 2020 for details on procedure). Fixed factors were Age and Month nested within the Age (hereafter expressed as ‘M(A)’ or ‘Month (Age)’); random factors included Year of sampling.…”
Section: Methodsmentioning
confidence: 99%
“…To overcome these issues, statistical analyses was conducted through a generalized linear mixed model (Glimmix procedure in SAS/STAT 9.; SAS Institute Inc., Cary, NC, USA). The model used was built for unbalanced designs (see Suardi et al, 2020 ; Bergonzoli et al, 2020 for details on procedure). Fixed factors were Age and Month nested within the Age (hereafter expressed as ‘M(A)’ or ‘Month (Age)’); random factors included Year of sampling.…”
Section: Methodsmentioning
confidence: 99%
“…Data on cumulative germination at increasing the time from sowing in plate were treated with a GLIMMIX procedure as above. In the Glimmix procedures, Strategy 1 included the inclusion of the effect of time as a class variable with no parameter estimation after application of a heterogeneous autoregressive covariance structure to the time of sampling to take into account the repeated measurements as applied in [41]. Strategy 2 included the inclusion of time as a continuous variable with all treatments (either continuous or class) parameter estimation through the application of the 'solution' option in the model statement.…”
Section: Computations and Statistical Analysesmentioning
confidence: 99%
“…In particular, the N fertilization was nested into the mixture ratio and the replicate in the plant species was added as a random factor. Additionally, a heterogeneous autoregressive covariance structure was applied to the time of sampling to take into account the repeated measurements, as applied in [49]. The dates of sampling were considered ordinal (i.e., first, second and third) without taking into account the variation of the growing degree days or time between each pair of data, since the biomass traits (and especially the dry matter content) strongly varied among the sampling moments, and 3 temporal moments do not allow one to correct for the temporal structure of the design.…”
Section: Computations and Statistical Analysesmentioning
confidence: 99%