Dias trabalháveis para o manejo do solo em função da chuva e da disponibilidade hídrica do solo em diferentes regiões brasileiras

Abstract

The use of machinery in agriculture is increasing. This leads to soil compaction or degradation when the machinery is operated under inappropriate soil conditions, which in turn results in decreasing crop yields. Therefore, the aim of this study was to identify the periods of the year when it is appropriate to use machinery for soil management, as a function of rainfall and soil moisture, in traditional agricultural regions in southern Brazil. The study used daily rainfall and air temperature data from Piracicaba, SP, Passo Fundo, RS, Londrina, PR and Dourados, MS, Brazil. Favorable conditions were calculated considering daily rainfall lower than 5 mm and soil moisture between 40 and 90% of soil water holding capacity. Daily soil water balance was calculated by the Thornthwaite and Mather (1955) method, for a soil water holding capacity of 100 mm, which represents the main soils of the studied regions. The Markov chain was applied and used to calculate the conditional probabilities which were used for estimating the sequential working days in each ten-day period throughout the year. The working days technique is an important tool for determining the most appropriate periods of the year for soil management. The annual rainfall and soil moisture variability was used to identify the periods of the year with low, medium and high suitability for soil management. For the assessed locations, there was a predominance of 11 to 20 working days per month, except for Londrina where up to 10 working days per month predominated.

Agrometeorological and Soil Criteria for Defining Workable Days for Rational Mechanized Sugarcane Harvest in Southern Brazil

“…In order to assure a better understanding of the impact of each one of the criteria proposed in the current study for determining NWD, MAE related to each Such a result turns out to be similar to that obtained by [21] who in turn made use of a threshold of PREC of 5 mm and SM/SWHC of 90%. Similar thresholds for PREC and SM/SWHC were also adopted by [11] to define the interruption of soil preparation operations with agricultural machinery. In this case, the aforementioned authors assumed that under PREC > 5 mm and SM/SWHC > 90% non-favorable conditions for soil management were established as also assumed by [21], since risks associated with compaction of soil layers right underneath tillage depth were eminent.…”

“…The criteria for the determination of the number of workable days vary in ac- cordance with the field operation to be carried out. The following criteria were used by [11] for assessing workable days for soil preparation and management:…”

“…According to these authors, the number of workable days varied from place to place and also from season to season, with a predominance of 11 to 20 workable days per month at Piracicaba, SP, Passo Fundo, RS, and Dourados, MS, whereas at Londrina, PR, a lower number of workable days of up to 10 days per month throughout the year prevailed. Similar criteria to those employed by [11] were utilized by [6] for determination of the probability of workable days for rice cultivation in Southern Brazil. On the other hand, [12] just used the ratio between SM and SWHC of 80% in a computational system to predict workable days for several field operations in Sudan.…”

Sequence of Workable Days for Mechanized Harvest of Sugarcane in Southern Brazil

“…Field agricultural operations are highly dependent on local meteorological conditions along with soil moisture, which define whether a given operation might be adopted or not at a given specific-site (Monteiro et al, 2014). One of the ways of determining the probability of the sequence of suitable days for a particular field operation based on weather conditions is by means of a method known as Markov chain (Mandal et al, 2015;Sanchez-Cohen et al, 2015;Manikandan et al, 2017;Griffin et al, 2017).…”

“…Another pivotal work was the one published by Stern and Coe (1982), which proposed a simulation model for daily precipitation based on the occurrence of rainfall generated from Markov chain, as well as on the amount of rainfall generated by a gamma distribution approach. In the sequence, several authors have been using the Markov chain approach for different purposes in hydrology (Yang et al, 2016;Sonnadara & Jayewardene, 2015) and precision agriculture (Monteiro et al, 2014;Sanchez-Cohen et al, 2015;Mandal et al, 2015;Manikandan et al, 2017;Griffin et al, 2017).…”