No abstract

Single image-NDVI method for early detection of mosaic symptoms in Capsicum annuum Mosaics are a symptom of a disease often found in red chilies (Capsicum annuum) and is generally caused by viral infections such as the Tobacco mosaic virus. Severe infection can cause stunting and significant yield loss. Serological and molecular detection is a common detection method for plant viruses although they are time-consuming, relatively inefficient for large samples, and are destructive to plants. On the other hand, direct symptoms observation is hampered by human visual abilities and latent symptoms in virus infection. Therefore, detection method based on the plant’s ability to absorb and reflect various spectrums of sunlight, such as the normalized difference vegetation index (NDVI), has the potential to be developed. This study aims to evaluate the potential of a single image-NDVI as an NDVI variant for the early detection of mosaic symptoms in red chilies. The main activity involved image recording of chili plants that were not inoculated (V0) and inoculated (V1) by the virus, and given minimal nutrients (M) using an unmodified RGB camera and lens filter to capture blue and Near-Infrared light reflection. Furthermore, image processing is carried out using the Photo Monitoring plugin on the Fiji-ImageJ application. The recording was done one day after inoculation (dai) until the symptoms were visible. The results showed that there was an increasing trend in the integrated NDVI value in all treatments. Howewer, the increasing trend in V1 was not significant compared to V0 and M. The difference in the mean value of integrated NDVI between V1 was very significant compared to V0 (at 5 dai) and M (at 1 dai). This method’s level of sensitivity, specificity, and accuracy ranges from 80–90% at 5 dai.

Quantitative assessment of plant diseases can be done relatively quickly and practically, especially when applying digital image processing. This paper discusses digital image potential for assessing mosaic symptoms caused by the Tobacco mosaic virus (TMV). Chili plants (Capsicum annuum L.) were grown in pots and subjected to two treatments, i.e., non-inoculated (V0) and TMV inoculated (V1). Plant image recording using a Canon 750D camera with a kit lens was done once a week, starting when the mosaic symptoms are first visible, i.e., in the second-week post-inoculation. Recorded images in RAW format were first converted to TIFF, then subjected to further analysis using image processing applications, namely GIMP 2.8 and Fiji-ImageJ. Differences in the RGB profile of leaves given V0 and V1 treatment was observed. Non-inoculated leaves (V0) have a dark green color pattern, while TMV inoculated leaves (V1) tend to have a mixed color pattern of dark green and bright green. In general, this indicates a decrease in chloroplast’s ability to absorb light in diseased leaves, reducing the photosynthesis level. This preliminary experiment shows digital image processing’s potential for estimating the severity of mosaic disease with a high degree of accuracy and precision.

This experiment was conducted in animal felid/ University of Baghdad/ College of Agriculture/ Animal production from 9/11/2016 until 9/1/2017. Twelve growing Awassi ewes lambs weighted 29.13 ±1.50 kg and 8-10 month old were used in this study, the lambs were divided into three individual groups (4 animals/ group) receive the dietary treatments contain 0.2 and 4% tallow, animals were fed concentrate at 2.5% of body weight, Alfalfa hay was given ad libitum basis as the roughage, The results found that: No significant difference between groups in total and daily concentrate, roughage and total feed intake, However, final body weight not affected by the experimental diets, total and daily weight gain had higher values (p<0.05) in diets containing 2 and 4% tallow, feed conversion efficiency improved significantly (P<0.05) in 4% tallow diet compared to other groups. It can be concluded that added tallow to sheep diets improved some productive performance such as total and daily weight gain, feed conversion efficiency. Excess animal fats from human consumption can be used as an energy source in ruminants feeds. Thus benefiting from excess animal fats from human consumption as a source of energy in ruminants' rations.