No abstract

The cover crop straw may cause changes in the microbial activity and population, with repercussions on environmental changes and on the C and N dynamics, providing important information for the planning of adequate land use in the Cerrado. The objective of this study was to evaluate the effect of straw of cover crops on the soil microbial attributes and quality of organic matter. Experimental units consisted of 100 g of sieved soil placed in small plastic cups mixed with straw from cover plants. Treatments were distributed in a CRD, in a factorial scheme of 7 x 7 + 1, with seven types of straw, evaluated at 7, 14, 21, 28, 42, 63 and 105 days after incubation, and control without straw, with three replicates. The qCO2 ranged from 0.1 (Crotalaria spectabilis at 14 days) to 5.1% (Cajanus cajan ‘IAPAR 43’ at 42 days). The organic carbon and nitrogen reservoir are differently affected by straw of legumes and grasses on the dates. The incorporation of Brachiaria brizantha and Mucuna aterrima had a positive impact on the microbial attributes until the 21st incubation (qCO2, Cmic and Nmic), with little loss of carbon dioxide and growth of the microbial population. All the evaluated species presented a potential to be used in crop rotation systems, enabling no-tillage systems in the Cerrado of Piauí. However, it is recommended to select species according to specific purposes. Thus, the use of cover crops is an important tool for increasing the biological quality of Brazilian northeastern cerrado soils.

No abstract

Soil chemical and physical analyses are the major sources of data for agriculture. However, traditional soil analyses are time-consuming, not cost-efficient, and not environmentally friendly. An alternative to traditional soil analyses is soil spectroscopy. This technique is a low-cost and quick analytical method, which can be implemented in a laboratory and/or in-situ. Nevertheless, some spectrometers are expensive and do not contemplate the entire spectrum. Despite this limitation, the main objective of the study was to create a soil spectral library of the Piauí State using only the 1000-2500 nm range. In this sense, it was evaluated and standardized the soil spectral library by accessing the combination of smoothing, standard normal variate, continuum removal, and Savitzky-Golay derivative spectral preprocessing procedures with partial least squares, random forest, and cubist machine learning algorithms. It was collected 262 geo-referenced soil samples at the layer of 0.00-0.20 m across the entire Piauí State, representing most of its soil variability. The soil properties evaluated were pH(H 2 O), sand, clay, and soil organic carbon (SOC) contents. This study demonstrated that the Standard Normal Variate was one of the most promising preprocessing procedures to improve model predictions for pH(H 2 O), sand, and clay. For SOC and pH, the best overall results were without preprocessing the soil spectra. Moreover, the cubist model was the most accurate in predicting soil properties. Finally, our study showed evidence of the potential and feasibility of using this soil spectral library to estimate soil properties such as pH(H 2 O), sand, clay, and SOC.

Growth and quality of Handroanthus serratifolius seedlings in soils incorporating amendments...