Characterization of soil chemical properties of strawberry fields using principal component analysis

• Main Authors: Gláucia Oliveira Islabão, Marília Alves Brito Pinto, Lisiane Priscila Roldão Selau, Ledemar Carlos Vahl, Luís Carlos Timm
• Format: Article
• Language: English
• Published: Sociedade Brasileira de Ciência do Solo 2013-02-01
• Series: Revista Brasileira de Ciência do Solo
• Subjects: Fragaria x ananassa Duch; fertilidade do solo; análise multivariada; variabilidade temporal
• Online Access: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832013000100017&lng=en&tlng=en

One of the largest strawberry-producing municipalities of Rio Grande do Sul (RS) is Turuçu, in the South of the State. The strawberry production system adopted by farmers is similar to that used in other regions in Brazil and in the world. The main difference is related to the soil management, which can change the soil chemical properties during the strawberry cycle. This study had the objective of assessing the spatial and temporal distribution of soil fertility parameters using principal component analysis (PCA). Soil sampling was based on topography, dividing the field in three thirds: upper, middle and lower. From each of these thirds, five soil samples were randomly collected in the 0-0.20 m layer, to form a composite sample for each third. Four samples were taken during the strawberry cycle and the following properties were determined: soil organic matter (OM), soil total nitrogen (N), available phosphorus (P) and potassium (K), exchangeable calcium (Ca) and magnesium (Mg), soil pH (pH), cation exchange capacity (CEC) at pH 7.0, soil base (V%) and soil aluminum saturation(m%). No spatial variation was observed for any of the studied soil fertility parameters in the strawberry fields and temporal variation was only detected for available K. Phosphorus and K contents were always high or very high from the beginning of the strawberry cycle, while pH values ranged from very low to very high. Principal component analysis allowed the clustering of all strawberry fields based on variables related to soil acidity and organic matter content.