A review of dairy cattle heat stress mitigation in Indonesia.

Indonesia is a tropical country with a hot climate. In tropical nations such as Indonesia, heat stress is a key reason for the reduced productivity of dairy cattle. Heat stress is a combination of internal and external stimuli that affects an animal, raises its body temperature, and causes it to react physiologically. Most Indonesian dairy cattle are Friesian Holstein (FH), imported from European nations with a temperate environment with low temperatures in the range of 5°C-25°C. Indonesia has a tropical climate with a high ambient temperature that can reach 34°C during the day and the local relative humidity varies between 70% and 90%. Temperature and humidity are two microenvironment factors that may impact the production and heat release in FH cattle. More than 98% of the entire dairy cattle population in Indonesia is found on Java Island. On Java Island, there are between 534.22 and 543.55 thousand heads of cattle, while the dairy cattle population outside Java Island is just 6.59 thousand heads of cattle. The milk output climbs by an average of 3.34% per year, or approximately 909.64 thousand tons and the average annual growth in whole milk consumption was 0.19 L/capita. Indonesian cow milk output has been unable to keep pace with the country's increasing demand. This study aimed to review the strategies to mitigate heat stress in FH dairy cattle in Indonesia.

The effects of heat-moisture treatment on resistant starch levels in cassava and on fermentation, methanogenesis, and microbial populations in ruminants.

Background and Aim: Resistant starch (RS) is difficult to digest in the digestive tract. This study aimed to evaluate the effects of heat-moisture treatment (HMT) on RS in cassava and examined its impact on rumen fermentation. Materials and Methods: Cassava flour was used as a raw material and used in a randomized block design with four different cycles of HMT as the treatments and four different rumen incubations in vitro as blocks. Treatments included: HMT0: without HMT (control), HMT1: one HMT cycle, HMT2: two HMT cycles, and HMT3: three HMT cycles. Heat-moisture treatment processes were performed at 121°C for 15 min and then freezing at -20°C for 6 h. Analyzed HMT cassava starch characteristics included components, digestibility, and physicochemical properties. In in vitro rumen fermentation studies (48 h incubation) using HMT cassava, digestibility, gas production, methane, fermentation profiles, and microbial population assessments were performed. Results: Heat-moisture treatment significantly reduced (p < 0.05) starch, amylopectin, rapidly digestible starch (RDS), and slowly digestible starch levels. In contrast, amylose, reducing sugars, very RDS, RS, and protein digestion levels were significantly increased (p < 0.05). Additionally, a reduced crystallinity index and an increased amorphous index were observed in starch using Fourier-transform infrared analyses, while a change in crystalline type from type A to type B, along with a reduction in crystallinity degree, was observed in X-ray diffraction analyses. Heat-moisture treatment significantly (p < 0.05) reduced rumen dry matter (DM) degradation, gas production, methane (CH4 for 12 h), volatile fatty acid (VFA), and propionate levels. In addition, acetate, butyrate, and acetate/propionate ratios, as well as population of Streptococcus bovis and Bacteroides were significantly increased (p < 0.05). However, pH, ammonia, and organic matter digestibility were unaffected (p > 0.05) by HMT. Conclusion: Cassava HMT altered starch characteristics, significantly increased RS, which appeared to limit rumen digestion activity, decreased rumen DM degradation, gas production, VFAs, and CH4 production for 12 h, but increased S. bovis and Bacteroides levels.

Heterochely and handedness in the orange mud crab Scylla olivacea: implication for future culture practice optimisation.

Asymmetric body traits in bilateral organisms are common and serve a range of different functions. In crustaceans, specifically among brachyuran crabs, heterochely and handedness in some species are known to aid in behavioural responses such as food acquisition, and sexual and territorial displays. However, the heterochely of the intertidal mud crab genus Scylla is still poorly understood. This study investigated the cheliped morphometric characteristics of orange mud crab Scylla olivacea and the relation of heterochely and handedness to sex. Scylla olivacea is heterochelous, with predominant right-handed (70.2%). Three morphometric variables, i.e., propodus length (PL), propodus depth (PD), and propodus width (PW) were significantly larger in the right cheliped and the estimated handedness based on these three variables were consistent with the presence of molariform teeth. The effect of sex had no influence on the occurrence of heterochely or handedness. The frequency of left-handedness increased with size, especially in males. We postulate that handedness reversal, a phenomenon seen in other crab species when the dominant hand is lost, also occurs in S. olivacea, thereby resulting in a change in left-handedness frequency. The use of chelipeds by males in mate and territorial defenses might provide an explanation for the higher risk of losing a dominant cheliped and thus, higher left-handedness frequency compared to females. Future behavioural research could shed light on the selective forces that affect the handedness distribution in mud crabs. Knowledge on heterochely and handedness of mud crabs could be useful for future development of less aggressive crab populations by claw reversal and the optimisation of limb autotomy techniques.

Improving the Accuracy of Rainfall Prediction Using Bias-Corrected NMME Outputs: A Case Study of Surabaya City, Indonesia.

Generating an accurate rainfall prediction is a challenging work due to the complexity of the climate system. Numerous efforts have been conducted to generate reliable prediction such as through ensemble forecasts, the North Multi-Model Ensemble (NMME). The performance of NMME globally has been investigated in many studies. However, its performance in a specific location has not been much validated. This paper investigates the performance of NMME to forecast rainfall in Surabaya, Indonesia. Our study showed that the rainfall prediction from NMME tends to be underdispersive, which thus requires a bias correction. We proposed a new bias correction method based on gamma regression to model the asymmetric pattern of rainfall distribution and further compared the results with the average ratio method and linear regression. This study showed that the NMME performance can be improved significantly after bias correction using the gamma regression method. This can be seen from the smaller RMSE and MAE values, as well as higher R 2 values compared with the results from linear regression and average ratio methods. Gamma regression improved the R 2 value by about 30% higher than raw data, and it is about 20% higher than the linear regression approach. This research showed that NMME can be used to improve the accuracy of rainfall forecast in Surabaya.