Soil physical and hydraulic changes in different yielding zones under no-tillage in Brazil

Abstract

Soil physical and structural degradation may influence crop productivity over time in long-term notillage system areas. A field study was conducted at two sites, Palmeira das Missões and Não-Me-Toque, in southern Brazil to quantify soil physical/hydraulic and structural changes in zones with different yield potentials. The sites have been managed under no-tillage system without soil disturbance for more than 10 years. Soils were classified as Oxisols (Hapludox). Each site was divided into three zones with low, medium and high yield potentials based on overlapping of yield maps obtained from harvesters with precision agriculture tools. Within each yielding zone soil samples were collected to determine bulk density, porosity and aggregate stability. In addition, water infiltration rate and initial time for starting surface runoff were measured using a sprinkler infiltrometer (Cornell Sprinkler infiltrometer). Our findings showed that soils under low-yielding zones presented higher bulk density, lower macro-aggregate stability and water infiltration rate as well as shorter time for starting surface runoff compared to high-yielding zones. Therefore, these results suggest that soil physical and structural degradations have induced crop yield losses under long-term no-tillage areas. Macroaggregate stability (>4.76 mm) and water infiltration rate were efficient parameters for distinguishing yielding zones in Oxisols managed under long-term no-tillage system in southern Brazil.

Use of supervised and unsupervised approaches to make zonal application maps for variable-rate application of crop growth regulators in commercial cotton fields

“…(Pedersen and Lind, 2017). At the same time, many studies explore the importance of delineating zones for input management (Plant 2001;Taylor et al 2003;Nawar et al 2017;Ouazaa et al 2022), what field information to use to delineate the maps (Santi et al 2016;Ortuani et al 2019;Mazur et al 2022), the profitability of applications (Roberts et al, 2006;Boyer et al 2010) and statistical frameworks (Whelan and McBratney, 2000;Buttafuoco et al 2010).…”

“…The inputs for which these MZ are used to guide applications are usually N, P, K, lime, seeds and cultivars (Doerge, 1999). In general, MZ are used to represent the productive potential of areas and can change considerably from year to year (Plant, 2001) or remain relatively stable when delineated based on a longer history and understanding of the area (Santi et al, 2016;Damian et al 2020). Within-field areas allocated to site-specific management of an input, a common implementation of PA, and their inter-and intra-annual variability can be associated with climate variability (Alesso and Martin, 2023), as also with the management of dynamic factors in the field, such as pests and diseases (Méndez-Vazquez et al 2019).…”

Precision Agriculture in Brazil: The Trajectory of 25 Years of Scientific Research

“…Site-specific soil management in Brazil is strongly reliant on soil mapping using systematic georeferenced soil sampling (grid sampling) followed by the interpolation of the results obtained from soil laboratory analysis. Since the early years of PA, several studies have investigated the characteristics of spatial variability of the chemical [43][44][45][46], physical [43,47], and, more recently, biological [48,49] attributes in Brazilian soils. Still, in the 2010s, some authors sought to define an "optimum" grid size (i.e., sampling density) for mapping the spatial variability of soil fertility attributes using geostatistical methods, in view of the expansion of this approach on Brazilian farms [50,51].…”