No abstract

Unmanned aerial vehicle (UAV) remote sensing technology can be used for fast and efficient monitoring of plant diseases and pests, but these techniques are qualitative expressions of plant diseases. However, the yellow leaf disease of arecanut in Hainan Province is similar to a plague, with an incidence rate of up to 90% in severely affected areas, and a qualitative expression is not conducive to the assessment of its severity and yield. Additionally, there exists a clear correlation between the damage caused by plant diseases and pests and the change in the living vegetation volume (LVV). However, the correlation between the severity of the yellow leaf disease of arecanut and LVV must be demonstrated through research. Therefore, this study aims to apply the multispectral data obtained by the UAV along with the high-resolution UAV remote sensing images to obtain five vegetation indexes such as the normalized difference vegetation index (NDVI), optimized soil adjusted vegetation index (OSAVI), leaf chlorophyll index (LCI), green normalized difference vegetation index (GNDVI), and normalized difference red edge (NDRE) index, and establish five algorithm models such as the back-propagation neural network (BPNN), decision tree, naïve Bayes, support vector machine (SVM), and k-nearest-neighbor classification to determine the severity of the yellow leaf disease of arecanut, which is expressed by the proportion of the yellowing area of a single areca crown (in percentage). The traditional qualitative expression of this disease is transformed into the quantitative expression of the yellow leaf disease of arecanut per plant. The results demonstrate that the classification accuracy of the test set of the BPNN algorithm and SVM algorithm is the highest, at 86.57% and 86.30%, respectively. Additionally, the UAV structure from motion technology is used to measure the LVV of a single areca tree and establish a model of the correlation between the LVV and the severity of the yellow leaf disease of arecanut. The results show that the relative root mean square error is between 34.763% and 39.324%. This study presents the novel quantitative expression of the severity of the yellow leaf disease of arecanut, along with the correlation between the LVV of areca and the severity of the yellow leaf disease of arecanut. Significant development is expected in the degree of integration of multispectral software and hardware, observation accuracy, and ease of use of UAVs owing to the rapid progress of spectral sensing technology and the image processing and analysis algorithms.

Ruminal acidosis is a prevalent disorder in ruminants such as dairy cows and feedlot beef cattle, caused primarily by the inclusion of a high percentage of readily fermentable concentrates in the diet. The disorder presents as an accumulation of lactic acid, a decrease of pH in the rumen and a subsequent imbalance of the rumen fermentation process with detrimental impacts on the animal's health and productivity. Dairy propionibacteria, a group of bacteria characterised by utilization of lactic acid as the favoured carbon source, with propionic acid produced as a by-product, were evaluated in this study as potential direct-fed microbials for use in controlling ruminal acidosis. Acidosis was simulated by introduction of high concentrations of lactic acid into rumen fluid samples and a multi-strain in vitro analysis was conducted, whereby changes in pH and lactic acid metabolism were compared in identical acidified rumen samples, following inoculation with various propionibacteria. This was followed by a study to evaluate the effect of bacterial inoculation dosage on acid metabolism. The results indicated that lactic acid levels in the rumen fluid were significantly reduced, and propionic acid and acetic acid concentrations both significantly increased, following addition of propionibacteria. Significant 'between strains' differences were observed, with Propionibacterium acidopropionici 341, Propionibacterium freudenreichii CSCC 2207, Propionibacterium jensenii NCFB 572 and P. jensenii 702 each producing more rapid reduction of lactic acid concentration than P. freudenreichii CSCC 2206, P. acidopropionici ATCC 25562 and Propionibacterium thoenii ATCC 4874. Furthermore, the efficacy of this application was dosage related, with the rates of reduction in lactic acid levels and production of propionic acid, both significantly greater for the higher (10 10 cfu mL-1) compared with lower (10 5 cfu mL-1) dosage inoculation. The results confirmed that the introduction of propionibacteria could promote more rapid reduction of lactic acid levels than would occur without their addition, demonstrating their potential in controlling ruminal acidosis.

The effects of the probiotic, Propionibacterium jensenii 702 (PJ 702), supplementation on egg productivity, egg shell thickness, fatty acid profile of eggs, and body weight in early layer hens were investigated. Twenty eight twenty-week-old starter pullets were evenly divided into a treatment and a control group for an eight week experiment. Each bird in the treatment group received 107 cfu PJ 702 daily in a total volume of 1 ml by oral administration. No adverse effect was observed due to administration of PJ 702, and successful gastrointestinal transit in the bird was demonstrated by recovery of PJ 702 from faeces of the treatment group. Layer production was significantly improved by the supplementation of PJ 702. Total egg weight in the treatment group was significantly higher than the control (P<0.001). Average egg weight for the treatment group was 55.26 g, 4.2% higher than the control which averaged 53.02 g. Moreover, the fatty acid profile was significantly altered by the supplementation of PJ 702. Myristic acid (P<0.001), palmitoleic acid (P=0.001) and all-cis-11,14-eicosadienoic acid (P=0.02) were significantly lower in the treatment group compared to the control group. No difference in egg shell thickness was observed between the treatment and control group (P=0.23). In conclusion, the application of novel probiotic PJ 702 in the early layer hen is safe and effective to promote production and the quality of products in layer husbandry.

Ruminal acidosis is a prevalent disorder among dairy cows and feedlot cattle, which can significantly impair their health and productivity. This study, involving seven different strains of dairy propionibacteria, represents an in vitro investigation of the feasibility of using these organisms as direct-fed microbials to control lactic acid acumulation in the rumen. Interactions between the propionibacteria, Streptococcus bovis and Megasphaera elsdenii were evaluated in terms of effects on lactic, acetic and propionic acid metabolism, following co-incubation. Spot resistance tests showed slight but varying degrees of growth inhibition by S. bovis among the propionibacteria, while no inhibition was observed between M. elsdenii and the different strains of dairy propionibacteria. In the co-culture experiments comprising S. bovis in nutrient broth, significant differences in pH and the levels of production of lactic, acetic and propionic acid, were observed between treatments following inoculation with various propionibacteria and/or M. elsdenii. In general, lactic acid concentrations at the end of the incubation were significantly lower in the cultures containing propionibacteria compared with cultures comprising either S. bovis only or S. bovis + M. elsdenii, although efficacy of lactate metabolism varied between species and strains. Moreover,the accumulation of acetic and propionic acid in the combined cultures, but not in the solo S. bovis culture, indicated that these compounds were produced as a result of the metabolism of lactic acid by the propionibacteria and M. elsdenii.