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    Microbial Community and Enzyme Activity of Forest Plantation, Natural Forests, and Agricultural Land in Chilean Coastal Cordillera Soils
    (2023)
    Yessica Rivas
    ;
    Humberto Aponte
    ;
    RIVERA SALAZAR, DIEGO ANDRÉS  
    ;
    Francisco Matus
    ;
    Oscar Martínez
    <jats:p>Despite the global expansion of forest plantations in Chile, their effect on biology properties of soil has still been only scarcely studied. Land use change in the Chilean Coastal Cordillera (36° to 40° S) is mainly attributed to the conversion of native forest to agriculture and forest plantations (Eucalyptus globulus and Pinus radiata de Don). The aim of this paper was to evaluate the changes in microbial composition (PCR-DGGE) and enzyme activity after the substitution of a native forest (e.g., Nothofagus spp.) by fast-growing exotic species and cropping. The most important factors that influence the abundance and diversity of bacteria and the fungi community were the soil organic matter (SOM) content, phosphorous (P-Olsen), calcium (Ca), boron (B), and water-holding capacity. These variables can better predict the microbial community composition and its enzymatic activity in the surface Ah horizon. Land use change also affected chemical soil properties of biogeochemical cycles. However, to deeply understand the connection between chemical and physical soil factors and microbial community composition, more research is needed. On the other hand, the expansion of forest plantations in Chile should be subject to legislation aimed to protect the biological legacy as a strategy for forest productivity as well as the soil microbial biodiversity.</jats:p>
      2Scopus© Citations 5
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    A satellite-based ex post analysis of water management in a blueberry orchard
    (2020)
    Eduardo Holzapfel
    ;
    Mario Lillo-Saavedra
    ;
    RIVERA SALAZAR, DIEGO ANDRÉS  
    ;
    Viviana Gavilán
    ;
    Angel García-Pedrero
      1Scopus© Citations 6  2
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    Simulation of Water-Use Efficiency of Crops under Different Irrigation Strategies
    (2020)
    Mathias Kuschel-Otárola
    ;
    RIVERA SALAZAR, DIEGO ANDRÉS  
    ;
    Eduardo Holzapfel
    ;
    Niels Schütze
    ;
    Patricio Neumann
    <jats:p>Irrigation management is a key factor in attaining optimal yields, as different irrigation strategies lead to different yields even when using the same amount of water or under the same weather conditions. Our research aimed to simulate the water-use efficiency (WUE) of crops considering different irrigation strategies in the Central Valley of Chile. By means of AquaCrop-OS, we simulated expected yields for combinations of crops (maize, sugar beet, wheat), soil (clay loam, loam, silty clay loam, and silty loam), and bulk density. Thus, we tested four watering strategies: rainfed, soil moisture-based irrigation, irrigation with a fixed interval every 1, 3, 5, and 7 days, and an algorithm for optimal irrigation scheduling under water supply constraints (GET-OPTIS). The results showed that an efficient irrigation strategy must account for soil and crop characteristics. Among the tested strategies, GET-OPTIS led to the best performance for crop yield, water use, water-use efficiency, and profit, followed by the soil moisture-based strategy. Thus, soil type has an important influence on the yield and performance of different irrigation strategies, as it provides a significant storage and buffer for plants, making it possible to produce “more crop per drop”. This work can serve as a methodological guide for simulating the water-use efficiency of crops and can be used alongside evidence from the field.</jats:p>
      20Scopus© Citations 12
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    Estimation of Yield Response Factor for Each Growth Stage under Local Conditions Using AquaCrop-OS
    (2020)
    Mathias Kuschel-Otárola
    ;
    Niels Schütze
    ;
    Eduardo Holzapfel
    ;
    GODOY FAUNDEZ, ALEX ORIEL  
    ;
    Oleksandr Mialyk
    We propose a methodology to estimate the yield response factor (i.e., the slope of the water-yield function) under local conditions for a given crop, weather, sowing date, and management at each growth stage using AquaCrop-OS. The methodology was applied to three crops (maize, sugar beet, and wheat) and four soil types (clay loam, loam, silty clay loam, and silty loam), considering three levels of bulk density: low, medium, and high. Yields are estimated for different weather and management scenarios using a problem-specific algorithm for optimal irrigation scheduling with limited water supply (GET-OPTIS). Our results show a good agreement between benchmarking (mathematical approach) and benchmark (estimated by AquaCrop-OS) using the Normalised Root Mean Square Error (NRMSE), allowing us to estimate reliable yield response factors ( K y ) under local conditions and to dispose of the typical simple mathematical approach, which estimates the yield reduction as a result of water scarcity at each growth stage.
    Scopus© Citations 10  1