The use of entomopathogenic nematodes (EPN) in the management of the notorious coffee insect pest, coffee berry borer (CBB) Hypothenemus hampei, remains poorly explored, especially in the Philippines. Three Philippine EPN isolates of Heterorhabditis indica (HiMAP, HiPBCB, and HiBSDS), and two Steinernema abbasi isolates (SaMBLB and SaBSU16) were evaluated against the adult females of H. hampei under laboratory conditions using a Petri dish assay. For the virulence and penetration bioassay, 40 adult female CBB were inoculated with 1,000 newly harvested infective juveniles (IJ) of each EPN isolate. The three isolates of H. indica were more virulent, with mortality ranging from 49.00–73.00%, than the two isolates of S. abbasi, with only 8.00–14.00% mortality; thus, only the H. indica isolates were further evaluated. HiMAP (73.00%) and HiPBCB (64.00%) recorded mortality rates significantly higher than HiBSDS (49.00%). To estimate the LT50, 30 adult female CBB were inoculated with 1,000 IJ of H. indica isolates, and results showed that HiMAP has a significantly shorter LT50 (32.50 h) than the two H. indica isolates. Similarly, 30 adult female CBB were inoculated with different concentrations of H. indica isolates to determine the LC50. HiPBCB has the lowest LC50 (20.82 IJ/CBB) but is not significantly different from HiMAP (25.47 IJ/CBB) and HiBSDS (37.37 IJ/ CBB). The results suggest that of the three H. indica isolates, HiMAP is a good biological control agent candidate that can be incorporated in the integrated pest management of H. hampei and is recommended for greenhouse or small-scale field trials to determine its adaptability to environmental conditions, effectiveness in the natural setting, and the appropriate method and timing of its application.

Understanding the composition, diversity, ecological classification, and conservation status of plant species is crucial for effective biodiversity conservation. However, existing studies in Benguet, the Philippines, primarily focus on communal forests, forest reservations, and national parks characterized by pine and mossy forests. There is a notable gap in research within other biodiversity-rich forest formations in the province. To address this, this paper investigated plant species composition and biodiversity dynamics in the Nangalisan Agroforest Sanctuary (NAS) – a 43-ha forest over limestone in Tuba, Benguet, managed and conserved through public-private partnerships. The findings identified 118 species across 95 genera and 54 families, showcasing a high floral diversity with a Shannon-Weiner diversity index (H’) of 4.42, and a Margalef species richness index (R) of 117.84, which is higher compared with similar ecosystems in other parts of the country. Based on the IUCN categories, three threatened and one near-threatened plant species were identified. Additionally, six species from the National List of Threatened Species (DAO 2017-11) were also identified as priorities for conservation. Of the documented samples, 69% were native, 11% endemic, and 20% exotic – including six (6) alien invasive plant species, which are very detrimental to the ecological health of the agroforestry sanctuary. This study enhances the understanding of plant diversity dynamics in agroforestry areas in Benguet while also highlighting the crucial role of public-private partnerships in conservation.

Eggplant (Solanum melongena L.) is an economically important solanaceous crop with orthodox seeds. Seed germination potential decreases due to prolonged storage resulting in delayed germination, which can consequently cause production lossess; thus, seed priming is practiced. In this study, the effect of various KNO3 concentrations (0.0625, 0.25, 1, and 4%) and priming durations (6, 12, 24, and 48 h) on eggplant seed germination was assessed using a between-paper germination test. The experiment followed a completely randomized design with four replicates per treatment, each consisting of 50 seeds. The results showed that germination was affected by the KNO3 concentration and the priming duration. The final germination percentage (FGP) revealed that priming significantly improved eggplant seed germination, but the differences for many priming treatments were non-significant (p ≥ 0.05) except in 0.0625% KNO3 applied for 24 and 48 h, which resulted in lower FGP than the non-primed seeds (87%). The germination index (GI) and germination rate index (GRI) index revealed that priming with 0.25–4% KNO3 for 6, 12, and 24 h can lead to significantly improved germination pattern (GI = 59.5–124.75 vs. control GI = 50; GRI = 9.17–11.82 vs. control GI = 8.88). The mean germination time (MGT) also revealed that KNO3 priming hastened seed germination, especially with 24-h priming duration (MGT = 8.50–9.60 d vs. control MGT = 10.08 d), whereas 6-h priming had no significant difference. Among the treatments, priming with 4% KNO₃ for 24 h resulted in the highest germination performance across all measured parameters. Moreover, priming with water and 0.0625% KNO3 was most effective when applied for 6 h, whereas prolonged exposure (≥ 24 h) can lead to slow and delayed germination. These results can be the basis for more efficient and effective seed priming using KNO3 in eggplant.

Tillage systems play a vital role in increasing the yield of sweetpotato. The study was conducted to determine the growth and yield response of sweetpotato as influenced by different tillage systems and variety; assess the extent of weed population; determine their interaction effects; and evaluate the marginal cost and return of growing sweetpotato varieties in different tillage systems. The experiment was laid out in a split plot arranged in a randomized complete block design with three replications. The different tillage systems [zero tillage (M1), reduced tillage (M2), and conventional tillage (M3)] served as the main plots, and the different sweetpotato varieties [Minani (T1), Minamon (T2), NSIC Sp 25 (T3), and NSIC Sp 30 (T4)] were the subplots. Tillage systems did not significantly influence all of the gathered agronomic characteristics of sweetpotato. In terms of yield characteristics, the number of marketable roots and total root yield were significantly higher under conventional tillage. Minani sweetpotato variety produced the most numerous and heaviest marketable and non-marketable roots, whereas NSIC Sp 25 had the least. The prevalent weed species found in the area were grasses and broadleaves, particularly in zero tillage. Minani obtained the highest gross margin, followed by Minamon, whereas the least was achieved in NSIC Sp 30 and NSIC Sp 25.

Methanogenesis is the formation of methane facilitated by a group of organisms from the phylum Archaea. There are three types of methanogenic Archaea depending on the substrate they use as input metabolite. The hydrogenotrophic (use H2), methylotrophic (use methylated compound), and acetoclastic (utilize acetate) methanogens. These are a biological process where rumen methanogens consume a substrate from fermentation mainly H2 to obtain energy where CH4 is the by-product. This enteric methane emission from livestock is both an environmental concern (greenhouse gases) and a production inefficiency as methane output is considered an energy loss. This paper reviews an understanding of methanogenesis and the application of approaches that could maximize production and reduce the release of pollutants under animal agriculture. The type and ratio of carbohydrates could alter the number and presence of microbes due to variations in rumen pH and substrates contained, such structural carbohydrates favor the growth of propionate-forming microbes that affect the rate of methanogenesis. An increase in the propionate ratio indicates a low methane emission as H2 is redirected away from the creation of methane. Phytochemicals from plants (oil, tannins, saponins) have direct and indirect effects on methanogens, while they also lower the numbers of protozoa that play a significant role in transferring molecular hydrogen, which will be utilized for methanogenesis. Novel rumen modulators like 3-nitrooxypropanol inhibit the methyl coenzyme M reductase (MCR) necessary for methane synthesis and have a remarkable potential to mitigate CH4. Other strategies include breeding performance, food waste minimization, change in diet preferences, housing and culling, etc. are also ways to decrease methane output. However, there is still a need to validate its effects on animal performance, residues in food, feasibility, availability, and economic grounds.

Velvet tamarind residue (VTR), a secondary product of velvet tamarind (VT) juice production, is predominantly found in the southernmost provinces of Thailand. This study explored the impact of incorporating VTR at 0, 3, 6, 9, 12, and 15% on the characteristics of mackerel fish crackers. The findings demonstrated that VTR addition significantly (p ≤ 0.05) altered the fish cracker’s color parameters (L*, a*, and b*). The hardness of the crackers increased significantly (p ≤ 0.05) with higher VTR inclusion. Sensory evaluations revealed that crackers with 3% VTR scored the highest (7.86, moderately like) in panelist preference. Notably, VTR- enhanced crackers exhibited reduced total energy (550.70 vs. 486.16 kcal) and total fat (34.38 g/ 100 g vs. 22.16 g/ 100 g) compared to non-VTR fish crackers. The VTR fish crackers were also enriched with minerals – including calcium (70.39 mg/ 100 g), sodium (1180.46 mg/ 100 g), and iron (0.79 mg/ 100 g). Additionally, the cross-sectional analysis of VTR fish crackers had larger pores than non-VTR fish crackers. In summary, VTR is potentially beneficial as a novel healthy dietary supplement.

Electromyography (EMG) signals hold critical significance in biomedical research, capturing muscle electrical activity during rest and contraction in the upper limb. Their versatility in applications, particularly in human-assisting robotic tools, drives ongoing exploration and research. This paper presents an original study focusing on leveraging machine learning techniques to classify EMG datasets and efficiently control a robotic arm based on predicted gestures. Data acquisition involves strategically placing an EMG muscle sensor on the forearm to ensure precise measurement of signals associated with hand gestures and movements. Diverse classifiers including random forest, support vector machine (SVM), K-nearest neighbors (KNN), Gaussian naïve Bayes, gated recurrent unit (GRU), long short-term memory (LSTM), artificial neural network (ANN), recurrent neural network (RNN), convolutional neural network (CNN), and vision transformer (ViT) are employed. Performance results are meticulously analyzed and presented in tabular format, showcasing the ViT classifier as the most successful, achieving an impressive 97.7% accuracy in robotic arm control. Notably, ANN, RNN, and CNN also exhibit high accuracy exceeding 90%. Furthermore, this work is comprehensively compared with existing literature, laying the groundwork for future advancements in human-robot interaction and cutting-edge assistive technologies that markedly enhance the quality of life for individuals with motor impairments or disabilities. The findings carry significant implications for designing and implementing intuitive, responsive robotic systems based on EMG signals.

The genus Prionispa Chapuis, 1875 (Coleoptera: Chrysomelidae: Cassidinae: Oncocephalini) is reviewed in the Philippines. Four species from the Philippines are treated. Keys to the genera and species of Prionispa is provided.

The white grubs of the genus Leucopholis Dejean are the most devastating insect pests of areca nut and coconut palms in south India. To date, three species, L. lepidophora Blanchard, 1851, L. coneophora Burmeister, 1855, and Leucopholis burmeisteri Brenske, 1894 have been reported from Karnataka. Leucopholis lepidophora is distinct from the two species based on their genitalia male and molecular markers. An average of 3.43–15.4% genetic distances were observed among L. coneophora and L. burmeisteri species based on the mitochondrial COI gene DNA barcode region. These results imply that they belong to distinct species. A key to the species of Leucopholis in south India is also provided.

In a previous paper, we proposed the next bar predictor (NBP) model for algorithmically composing melodies. The NBP is much simpler than existing algorithms, yet it fared competitively with the best ones in all criteria (how realistic, how interesting, and how pleasing). In this paper, we propose a further improvement to the NBP by incorporating a melody post-processing technique that would generate a melody that better satisfies music theory and practice. The proposed technique ensures that all sufficiently long notes (based on a predefined threshold) align with a current chord while the shorter notes align with the given scale. As the proposed adjustment technique depends on the note duration threshold, we experimented with various thresholds and eventually decided to use quarter notes. We then compared the outputs of the standard NBP with the modified NBP (MNBP), and the results showed a significant improvement based on actual human evaluations involving music experts and enthusiasts alike. The result in MNBP improved by 9.33, 11.88, and 7.37% using the evaluation criteria of how realistic, how interesting, and how pleasing, respectively. A paired t-test using the 0.05 threshold shows that the improvement in the scores is statistically significant. Finally, since the post-processing technique can, in theory, be applied to the melody generated by any music composition algorithm, the algorithm was applied to Midinet, and surprisingly, even if the output of the Midinet is conditioned using the chord progression, results show that human evaluators prefer the adjusted melody of the Midinet than the original one, from the three criteria – realistic, interesting, and pleasing – the results improved by 20.82, 24.48, and 29.39% respectively. This is further validated to be statistically significant using the 0.05 threshold across all evaluators. Overall, the proposed technique does exhibit good potential for further improving algorithm- composed melodies.