Carlos Sérgio Tiritan’s research while affiliated with University of Western São Paulo and other places

The need for sugarcane field reform has driven the expansion of soybean cultivation in rotation with sugarcane. Weeds are one of the main reasons for this reform, requiring specific management in rotation. The use of pre-emergence herbicides in soybean is a viable option, but its effectiveness in sandy soils requires further study. In this experiment, we evaluated the performance of pre-emergence herbicides on sugarcane straw, focusing on the control of Digitaria horizontalis. We conducted a field experiment with 11 treatments and four replications, applying herbicides immediately after soybean sowing. All herbicides, except diclosulam, provided efficient control of D. horizontalis, with over 80% control in all evaluated periods. The clomazone+sulfentrazone association showed the highest residual effect, keeping the area clean for up to 21 days after application. Weed-free control resulted in productivity equivalent to 66% of the maximum obtained. The use of cell division inhibitors allowed soybean cultivation to grow without weed competition. We conclude that the use of pre-emergence herbicides in soybean under sugarcane straw resulted in productivity gains due to effective D. horizontalis control. Poaceae plants may have a higher competitive capacity with crops compared to other families; therefore, even with few plants per square meter, species like D. horizontalis can reduce crop productivity. The use of cell division inhibitor molecules, either alone or combined with PROTOX inhibitors, allowed the soybean crop to remain free of weed competition.

The objective was to verify the performance of spectral techniques as well as validation models in the prediction of nitrogen, total organic carbon, and humic fractions under different cultivation conditions. Chemical analyses for the determination of nitrate, total nitrogen, total organic carbon, and the chemical fractionation of soil organic matter were performed, as well as spectral analyses by Vis-NIR-SWIR and X-ray fluorescence. The results of the spectroscopy were processed using RStudio v. 4.1.3, and PLSR and support vector machine learning algorithms were applied to validate the models. The Vis-NIR-SWIR and XRF spectroscopic techniques showed high performance and are indicated for the prediction of nitrogen, total organic carbon, and humic fractions in Ferralsols of medium sandy texture. However, it is important to highlight that each technique has its own characteristic mechanism of action: Vis-NIR-SWIR detects the element based on harmonic tones, while XRF is based on the atomic number of the element or elemental association. The PLSR and SVM models showed excellent validation results, allowing them to fit the experimental data, emphasizing that they are different statistical methods.

This work aimed to develop suitable predictive models for ammonium, nitrate, total nitrogen, total organic carbon and soil humic fractions, for Ferralsols, using Vis-NIR-SWIR, MIR and X-ray fluorescence spectroscopic techniques in conjunction with machine learning algorithms, Cubist, PLSR, Random Forest and Support Vector Machine. Chemical analyzes were carried out to determine nitrate, total nitrogen, total organic carbon and chemical fractionation of soil organic matter, as well as spectral analyzes using Vis-NIR-SWIR spectroscopy, MIR and X-ray fluorescence. The spectroscopy results were processed using RStudio v. 4.1.3, applying Cusbist, PLSR, Random Forest and Support Vector Machine machine learning algorithms to create predictive models and describe spectral curves and Pearson correlation. Of the prediction models developed for nitrogen, total organic carbon and humic fractions, the PLSR and Support Vector Machine algorithms presented the best predictive performances. The descriptive analysis of the spectra identified the main absorption bands and the location of the bands sensitive to the attributes of interest. The correlation analysis proposed that the use of Vis-NIR-SWIR, MIR and XRF spectroscopic techniques were effective in predicting the contents of nitrogen, total organic carbon and humic fractions in soil with a medium sandy texture. However, it is important to highlight that each technique has its characteristic mechanism of action, Vis-NIR-SWIR and MIR detect the element based on overtones and fundamental tones, while XRF is based on the atomic number of the elements or elemental association.

O produtor de cana-de-açúcar é remunerado em função da produtividade de colmos e através do preço do açúcar total recuperável (ATR), parâmetro este que representa a qualidade da cana-de-açúcar, ou seja, a capacidade da cana ser transformada em etanol e açúcar. A análise do ATR envolve diversos equipamentos e reagentes, e são realizados em laboratórios localizados nas usinas. Tais procedimentos acabam dificultando o monitoramento da qualidade da cana-de-açúcar no campo. Portanto, a elaboração de métodos de estimativas do ATR no campo pode auxiliar o produtor no monitoramento da qualidade da cultura da cana-de-açúcar.

In humid tropical regions, intense weathering extensively depletes soil nutrients. However, soils in the Araguaia River Valley, Brazil, are not responsive to potassium (K) fertilization. To explore the reasons for this lack of responsiveness, an extensive exploratory soil sampling campaign was performed in areas of the valley with different land uses and soil management practices. Soil was sampled at depths of 0–20 cm and 20–40 cm, and exchangeable K (Ke) and non-exchangeable K (Kne) were assessed. The average soil Ke content in the region was 66.3 mg kg− 1, above the minimum required value for crop growth. The soil Kne content ranged from one to five times the soil Ke content and was greater in the 20- to 40-cm layer than in the 0- to 20-cm layer. The linear correlation between Ke and Kne was significant only in the silt fraction. Mineralogical analysis of the clay and silt fractions of selected samples showed that the dominant minerals in the clay fraction were kaolinite, vermiculite with or without interlayer hydroxy-Al (HIV), illite, goethite, and gibbsite. Mica and feldspar were found in the silt fraction of several samples. In the silt and clay fractions, the main source of Kne was 2:1 phyllosilicates, which may be interstratifications of illite/vermiculite-hydroxy and illite/vermiculite. The results indicated that Urochloa spp. functions as a K scavenger in deep layers and promotes K biocycling in the system. An equation for predicting Kne extracted with nitric acid on the basis of soil Ke and silt contents was developed.

Understanding factors that contribute to carbon dioxide (CO 2 ) losses and ammonia (NH 3 ) volatilization in agricultural soils, mainly in sandy soils, is essential for determining strategies to decrease emissions of these gases and improving carbon (C) and nitrogen (N) stocks in the soil. The objective of this study was to quantify C and N inputs to the soil and CO 2 and NH 3 emissions in a crop-livestock integration system composed of pastures with grass-legume intercropping and N fertilizer application. The experiment was carried out in a Typic Hapludox, evaluating three consecutive soybean crops grown in rotation with the following pasture systems: mombaca grass ( Panicum maximum cv. Mombaca) with N fertilizer (M + N); mombaca grass without N fertilizer (M-N); mombaca grass intercropped with the forage legume pigeon pea ( Cajanus cajan ) (M + G); and mombaca grass intercropped with the forage legume java ( Macrotyloma axillare cv. Java) (M + J). Soil samples were collected at the beginning and end of each crop and analyzed for total C (TCS) and N (TNS) stocks. NH 3 volatilization and CO 2 emissions were evaluated every 15 days, with simultaneous evaluations of soil moisture and temperature. Soybean rotation with grass-legume intercropping or grass with mineral fertilizer application improved N and C inputs to the agricultural systems, although there were losses in CO 2 and NH 3 . The M + G and M + J intercrops after soybean crops increased NH 3 volatilization, whereas the use of M + N tended to decrease it. The soil moisture affected the C and N input-output balance in the production systems evaluated.

Soybean production in sandy soils under the recovery process presents risks that can be mitigated by growing crops between crop seasons, focused on silage production, which can assist in environmental improvement, accelerating soil recovery, in addition to improvement in soybean grain yield. The objective of this study was to evaluate soybean grain yield, silage yield and soil fertility in an area converted from degraded pasture to soybean production. The study was conducted a sandy soil, in Presidente Bernardes, São Paulo, Brazil, from 2015 to 2018. The treatments consisted of six silage crops (maize, sorghum, sunflower, palisade grass, millet, and pigeon pea) and a control with fallow (March-July) between soybean crop seasons (October-March). The mean soybean grain yield in the soybean-millet system (4400 kg ha⁻¹) was, on average, 42% higher than that in the soybean-fallow (3100 Mg ha⁻¹). The mean soybean grain yield (three crop seasons) in the systems with maize, sorghum, and sunflower was similar to that in the soybean-fallow system. The mean palisade grass silage yield was higher in two of the three crop seasons (16.8 Mg ha⁻¹); maize also presented a good performance in the second crop seasons (10200 kg ha⁻¹). The higher palisade grass silage production resulted in higher mean (three crop seasons) extraction of macronutrients (136, 129, 65, 54, 13.2 9.6 kg ha⁻¹, for K, N, Ca, Mg, P, and S, respectively). The growth of millet and palisade grass crops between soybean crop seasons improved the soil fertility, but the effect of millet was faster (first harvest). The main soil fertility attributes affected were: phosphorus, potassium, organic matter, cation exchange capacity, and base saturation. The best crop option to be grown between soybean crop seasons are millet and palisade grass for silage when focused on improvements in soil fertility and grain yield of the following soybean crop, and the choice between these two species depends on the farmer's priority.

This study aimed to evaluate the grain yield of soybean cultivars as a function of different sowing seasons and soil types, in the Western region of São Paulo state. Two experiments were performed in the district of Gardênia, municipality of Rancharia-SP in two types of soil (Red Argisol with medium sandy texture and Red Nitosol with very clayey texture). For both studies, a randomized block design in a 5 x 2 factorial scheme arranged in strips was adopted. The factors consisted of five sowing seasons (October 21st; November 4th; November 18th; December 2nd and December 16th) and two soybean cultivars (TMG 7060 IPRO and TMG 7062 IPRO). The sowing seasons performed on October 21th and November 4th showed the highest rates of plant growth and grain yield, regardless of soil texture. Grain yield was similar among the cultivars studied in the Red Argisol with medium sandy texture. In the very clayey Red Nitosol, the TMG 7062 cultivar had higher productivity in the sowing of November 4th and the TMG 7060 cultivar in the sowings of November 18th and December 2nd.

Among the plant nutrients, potassium (K) plays a fundamental role in plant physiology and the soil-plant dynamics of various nutrients. Careful rate recommendations for K are needed to ensure that the balance between cationic nutrients and micronutrients is maintained, especially in sandy soils. The current research aimed to evaluate the absorption dynamic of several nutrients by soybean (Glycine max. Merrill.) growing in sandy soil under the application of five rates of K (0, 25, 50, 75, and 100 kg ha⁻¹) via potassium chloride (KCl) with five replications. The concentrations of K⁺ in the diagnostic leaves of the soybean plants presented quadratic behavior with the increase in K rate and reached a maximum of 17.74 mg kg⁻¹ at a rate of approximately 81 kg ha⁻¹ K, which was found through a regression test. The leaf concentrations of calcium (Ca²⁺) and magnesium (Mg²⁺) decreased linearly with increasing K rate. By contrast, the leaf concentrations of the micronutrients; boron (B) and iron (Fe²⁺) decreased with increasing K rate. Soybean productivity was not influenced by the application of K. Principal component analysis (PCA) showed a clear influence of increasing K rates on the leaf nutritional parameters of soybean plants. The results confirm that the high application of K in sandy soils can disrupt the balance of nutrient uptake by soybean plants.