No abstract

Impact of weed control methods on the persistence of Parthenium hysterophorus L., and tomato (Solanum lycopersicum L.) yield was studied in two farmer fields i.e. a site heavily infested with P. hysterophorus (Parthenium-site) and Partheniumfree site, in the Jaffna peninsula of the Northern Province of Sri Lanka. The split-plot design consisted of two main plots i.e. manual weeding and ploughing (both followed by harrowing), and three sub-plots i.e. use of a pre-emergent herbicide (Oxyfluorfen; 240 g/L EC at 2 days before planting), mulching [Gliricidia sepium (Jacq.) Kunth ex Walp. leaves at 12 kg per plot on fresh weight basis], and un-weeded plot after crop establishment (control), in three replicates. The soil seed bank of the Parthenium-site was dominated by P. hysterophorus as expected, and the Parthenium-free site was dominated by the perennial sedge Cyperus rotundus L. At tomato harvest, the un-weeded sub-plots recorded the highest weed densities (p<0.05) when compared to the rest, The Parthenium-site showed a higher weed dry weight (p<0.05) when compared to that of the Parthenium-free site, due to higher emergence of the Parthenium weed in the former. Mulching was the best sub-plot treatment for Parthenium control in combination with the main plot treatments. The average fruit weight of tomato at the Parthenium-free site was 7.8 % higher than that of the Partheniumsite (47.8 g per fruit). In the Parthenium-site, mulching resulted in a 6.4% higher fruit weight and 58% higher total yield (p<0.05) when compared to the rest of the sub-plot treatments. The weed competition negatively affected the tomato yield (Y=-0.7551X+7.88; R 2 =0.58; p<0.05), with Parthenium weed playing a dominant role. Mulching with G. sepium coupled with manual weeding during land preparation or ploughing would suppress growth and development of weeds including P. hysterophorus and enhance yield of tomato.

Abstract-An experiment was conducted during March to July in 2017 (off season)

Chilli (Capsicum frutescens L.) is one of the most important cash crop cultivated in the Sri Lanka. Though, chilli cultivation has been tremendously influenced by the adverse climatic conditions and weed infestations. To solve these issues, a field experiment was conducted at Integrated Farm and Training Center, Faculty of Agriculture, University of Jaffna, Kanagarayankulam, during February 2017 to July 2017, to evaluate the impact of partial shade and effect of different weeding intervals on growth and yield performance of chilli. The treatments consisted of two shade levels (partial shade and full sun) and four weeding intervals (weeding at one week, two week, three week intervals and no weeding) in split plot arrangement with three replicates. Light intensity was statistically significant (p < 0.05) between shade levels. The lowest light intensity and the highest relative humidity were recorded in partially shaded treatment as 22.50 klux and 85.42 %, respectively at 8.00 a.m. Weed density was significantly (p < 0.05) differed by shade and weeding interval treatments. The lowest weed density was recorded in full sun (control) and weeding at one week interval treatment. Shade treatments and weeding interval treatments have shown a significant (p < 0.05) effect on plant height, leaf numbers, leaf length, fruit length, fruit fresh weight and total yields. Partial shade and weeding at one week interval have shown significantly higher growth and yield performance compared to the other levels of treatment. Therefore, these results can be recommended for adoption by the farmers to improve the performance of chilli.

Technology seeks a new dimension as collaboration of various methods and technologies in transmission of data. Crowdsourcing enables the availability of huge data over a variety of networks. It is important to understand the needs of the management and monitoring of such data over a long distance and among a huge population especially among a big crowd like that of temples and other public places. Hence integration of network technologies has to be considered for effective attainment of data transfer with high speed and better performance that includes latency. The paper conducts analytics of various collaborated network technologies that was utilised to handle huge data from a crowdsourced network. The network technologies considered for the reviews are Edge computing, Fog computing, IoT based sensors, mobile technologies and cloud-based platforms. After significant analysis of all the research works, it was identified that edge computing has been the chief network technology used to transmit crowdsourced data with speed and efficiency. Cloud platforms assist the transferred data to be stored with privacy and security. The IoT sensors and Fog computing helped in detecting the data and also to increase the bandwidth and improve latency problems. The research gap identified was to enhance the speed and efficiency of transmission in public related problems like surveillance and handling public or social media database which seemed to be more challenging and encouraging future research works.