The objective was to evaluate the effects of potassium fertilization on the morphogenetic, structural, and productive characteristics of Panicum maximum (cvs. Tanzania, Quênia, Mombaça, Zuri, Massai, and Tamani). The design was in randomized blocks with four doses of potassium (K) 0, 205, 410, and 820 mg dm⁻³, divided into 5 applications. The analyzed variables were leaf appearance rate (LAR), leaf elongation rate (LER), stem elongation rate (SER), leaf senescence rate (LSR), leaf life span (LLS), phyllochron (PC), number of live leaves (NLL), final leaf length (FLL), tiller population density (TPD), and forage mass (FM). LAR increased by 0.00216 leaves tiller on day-1 (p = 0.0354) and LER increased by 0.00980 cm tiller on day-1 for each milligram of K (p = 0.0402). There was an increase in FLL of 0.16, 0.08, and 0.07 days for the cultivars Mombaça, Massai, and Tamani, respectively, for each milligram of K applied (p = 0.0034). The TPD of the cultivar Tamani increased linearly by 0.074 tillers/pot for each milligram of K (p = 0.0226), and the cultivar Massai showed a quadratic behavior. The TPD of the other cultivars was not influenced by the increase in the K doses. For forage mass (FM), the cultivars Mombaça and Quênia increased by 0.16 and 0.39 g DM/pot for each milligram of K added to the soil. The cultivars Tanzânia, Zuri, Massai, and Tamani showed maximum point at doses of 261.35, 279.45, 300.57, and 275.86 mg dm⁻³ K, respectively. Potassium fertilization linearly increased leaf appearance and elongation, with maximum productivity reached at a K dose of 430 mg dm⁻³, except for the cultivars Mombaça and Quênia, which responded up to a K dose of 820 mg dm⁻³.

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.

Accurate prediction of forage digestibility is essential for efficient livestock management and feed formulation. This study evaluated the performance of machine learning (ML) models to estimate the in vitro digestibility of leaf and stem components of Brachiaria hybrid cv. Ipyporã, using three datasets composed of pasture management variables, chemical composition variables, and their combination. Artificial neural network (Multilayer Perceptron, MLP), decision trees (REPTree and M5P), Random Forest (RF), and Multiple Linear Regression (LR) were tested. The principal component analysis revealed that 61.3% of the total variance was explained by two components, highlighting a strong association between digestibility and crude protein content and an opposite relationship with lignin and neutral detergent fiber. Among the evaluated models, MLP, LR, and RF achieved the best performance for leaf digestibility (r = 0.76), while for stem digestibility the highest accuracy was obtained with the LR model (r = 0.79; MAE = 2.42; RMAE = 2.87). The REPTree algorithm presented the lowest predictive performance regardless of the input data. The results indicate that chemical composition variables alone are sufficient to develop reliable prediction models. These findings demonstrate the potential of ML techniques as a non-destructive and cost-effective approach to predict the nutritional quality of tropical forage grasses and support precision livestock management.

The objective of this study was to evaluate the effects of potassium (K) on disease severity and the chemical composition of Megathyrsus maximus cultivars. The experiment was conducted in a randomized block design in a 6 × 4 factorial arrangement, consisting of six Megathyrsus maximus cultivars (Massai, Mombaça, Tamani, Tanzânia, Quênia, and Zuri) and four K doses (0, 205, 410, and 820 mg dm⁻³). The severity of the leaf spot complex, caused by Bipolaris maydis and B. yamadae, was assessed using a diagrammatic scale. A significant interaction between K doses and cultivars was observed for all evaluated diseases. At K doses of 0 and 205 mg dm⁻³, the Tanzânia cultivar showed lower leaf spot severity compared with the other cultivars, whereas at higher doses, no disease symptoms were observed in any cultivar. The area under the disease progress curve (AUDPC) for mosaic followed a linear model only for the Tanzânia cultivar, whereas quadratic regression models best described the response for the remaining cultivars, with maximum mosaic severity values of 67.74% for Quênia, 72.34% for Mombaça, 76.99% for Zuri, 74.88% for Massai, and 68.93% for Tamani. Increasing K doses reduced the severity of both the leaf spot complex and mosaic. However, the leaf spot complex did not affect the nutritional value of the evaluated cultivars.