The objective was to investigate the effects of increasing levels of extruded urea (EU) in the supplementation of lambs grazing. Crossbred Texel lambs ( n = 45) were used and kept in continuous grazing in paddocks with Brachiaria spp. The design used was completely randomised, with five of EU replacing soybean meal (0; 6; 12; 18 and 24 g/kg) and two sexes (male and female). The animals were slaughtered, and qualitative and quantitative evaluations of the carcass, non‐carcass components, meat quality and chemical composition were carried out. There was an interaction between level*sex for ether extract (EE) and crude protein (CP), so than the meat of the females from the treatment without EU had a higher content of EE than that used EU and the meat of the males from the treatments with 12 g and 24 g 100 kg ⁻¹ LW higher levels of CP than other treatments. For all measurements performed up to 18 g 100 kg ⁻¹ LW of EU replacing bran and soy, the results were promising, and can be fed to finishing lambs under grazing, without negatively influencing most of the carcass characteristics, components non‐carcass, meat quality and chemical composition.

Panicum maximum cultivars have distinct characteristics, especially morphological ones related to the leaf structure and coloration, and there may be differences in the spectral behavior captured by sensors. These differences can be used in classification using machine learning (ML) algorithms to differentiate biodiversity within the same species. The objectives of this study were to identify ML models able to differentiate P. maximum cultivars and determine which is the best spectral input for these algorithms and whether reducing the sample size improves the response of the algorithms. The experiment was carried out at the experimental area of the Forage Sector of the School Farm belonging to the Federal University of Mato Grosso do Sul (UFMS). The leaf samples of the cultivars Massai, Mombaça, Tamani, Quênia, and Zuri were collected from experimental plots in the field. Analysis was carried out on 120 leaf samples from the P. maximum cultivars using a VIS/NIR hyperspectral sensor. After obtaining the spectral data and separating them into bands, the data were submitted for ML analysis to classify the cultivars based on the spectral variables. The algorithms tested were artificial neural networks (ANNs), REPTree and J48 decision trees, random forest (RF), and support vector machine (SVM). A logistic regression (LR) was used as a traditional classification method. Two input models were evaluated in the algorithms: the entire spectrum band provided by the sensor (ALL) and another input configuration using the calculated bands. The reflectances from the P. maximum cultivars showed different behavior, especially in the green and NIR regions. RL and ANN algorithms using all information in the spectrum are able to accurately classify the cultivars, reaching accuracies above 70 for CC and above 0.6 for kappa and F-score. VIS/NIR leaf reflectance can be a powerful tool for low-cost, non-destructive, and high-performance analysis to distinguish P. maximum cultivars. Here, we achieved better model accuracy using only 40 leaf samples. In the present study, the J48 decision tree model proved to have good classification performance regardless of the sample size used, which makes it a strategic model for forage cultivar classification studies in smaller or larger datasets.

This study evaluated the phosphorus use efficiency (PUE) in two genotypes and one cultivar of Brachiaria decumbens (HD1, HD4, and Basilisk) and the productive, morphogenic, and structural responses. The experimental design used was randomized blocks with five P rates (0, 13, 26, 52, and 104 mg dm⁻³). There was no forage × P rate interaction (p > 0.05), but the P rates affected the leaf appearance rate (TAR; p = 0.0314), leaf life span (LLS; p = 0.0207), phyllochron (PC; p = 0.0207), leaf elongation rate (LER; p = 0.0350), stem elongation rate (SER; p = 0.0109), and the number of live leaves (NLL; p = 0.0033). The LAR, LLS, and PC followed quadratic trends, increasing up to 52 mg dm⁻³, while the PC declined. The FLL, SER, and NLL increased linearly. HD1 had the highest final leaf length, LER, and NLL, while Basilisk had the lowest. There was an interaction for tiller population density (p = 0.0431), with increases of 0.26, 0.28, and 0.24 tillers for HD4, HD1, and Basilisk, respectively. Forage production (FP) increased with P, gaining 0.51 g of DM for each mg dm⁻³ of P added. The HD1 genotype showed higher FLL, LER, NLL, FP, and higher PUE than the HD4 genotype and the Basilisk cultivar. HD1 was more responsive to higher P rates for root production, indicating a greater need for nutrients to reach its productive potential. Phosphate fertilization positively influenced morphogenesis and forage production in the evaluated genotypes and cultivars. The HD1 genotype stood out in relation to the others, showed superiority in forage and root production, and demonstrated greater efficiency in the use of P, at a dose of 13 mg dm⁻³.

The study evaluated the severity of leaf spots caused by Bipolaris maydis and Cercospora fusimaculans in Panicum maximum subjected to different liming and phosphate fertilization levels. A randomized block design was used in a 6 × 2 × 5 factorial arrangement, considering six genetic materials of P. maximum, two cultivars (BRS Tamani and BRS Zuri) and four genotypes (PM422, PM408, PM414 and PM406), two phosphorus (P) doses (P19 and P116 mg dm³) and five limestone doses (0, 326, 653, 1306 and 2612 mg dm³). A significant interaction between Forage and P doses was observed for both pathogens (p < 0.0001 and p = 0.0001, respectively). The severity of C. fusimaculans decreased at P116 in the genotypes PM406, PM408, PM422 and Tamani. A P × Limestone interaction was detected for both pathogens (p = 0.0270 and p = 0.0077), with lower severity at P116. For B. maydis, limestone doses did not significantly differ. For C. fusimaculans, at P19, lower severity was observed at 1306 mg dm⁻³ limestone, while at P116, the lowest severity occurred at 2612 mg dm⁻³. No significant Forage × Limestone interaction was found. The Forage × P doses × Days interaction (p = 0.0005) influenced B. maydis severity, while the Forage × Days interaction (p < 0.0001) affected C. fusimaculans. Phosphate fertilization and liming reduce the severity of Bipolaris maydis and Cercospora fusimacula in different genotypes on Panicum maximum.

Soil nutrient availability affects economically significant crops, yet its influence on forage sorghum remains poorly understood. This study aimed to assess the impact of soil fertility on Bolivian Giant Sorghum AGRI 002E (Sorghum bicolor) across morphological, sanitary, yield, chemical, and nutritional attributes. A completely randomized experimental design was employed, comprising two treatments and ten replicates, representing two soil fertility conditions: A (fertile) and B (low fertility). The experiment was conducted in the Brazilian savanna. Soils A and B differed mainly in potassium (K), phosphorus (P), base saturation, manganese (Mn), and zinc (Zn) (0.00-0.20 m), and potassium (K), phosphorus (P), sulfur (S), and Al ³⁺ saturation (0.00-0.40 m). Sorghum cultivated in soil A exhibited a remarkable 64.83 % increase in green forage mass compared to soil B, translating to a difference of 24.04 Mg ha ^-1 in dry matter. Furthermore, sorghum in soil A maintained a significantly higher number of live leaves, approximately 5.6 more than soil B, albeit experiencing a 33.59 % reduction in estimated leaf area under the lower soil fertility condition. Significantly, a conspicuous negative correlation emerged between the severity of anthracnose and morphological and yield traits. Under conditions of low soil fertility, the severity of anthracnose was six times higher, the dry forage yield was 13.04 Mg ha ^-1 , and this hindered structural development, increased fibrous structures, diminished crude protein, and reduced digestibility.