International audienceProliferations of green, brown and red algae appear in shallow sandy bays in North Brittany (France), and they represent a real economic constraint for the affected communities. In addition to the nuisance for residents and tourist activity, the communities must carry out systematic collection. The collected algae are spread on agricultural land spreading or composted, but these solutions reach their limits rapidly, bringing little added value to the collected algae. Seaweeds are potentially excellent sources of bioactive metabolites that could represent useful leads in the development of new functional ingredients in pharmaceutical and cosmetic industries. The aim of this study was to propose the use of an enzyme-assisted extraction as a tool to improve the extraction efficiency of antiviral compounds from three invasive French seaweeds. We selected the red Solieria chordalis, the green Ulva sp. and the brown Sargassum muticum as models for these experiments. In comparison with water extraction at 50 °C for the same time of treatment, enzymatic hydrolysis increased the yields. The data suggest the potential of enzymatic hydrolysis for producing active fractions in the function of the algal biomass, the behaviour of the cell wall, the selectivity and the action of the enzyme. Enzymatic hydrolysis appeared less effective for polyphenol recovery, but was a promising softer technique for recovering proteins, neutral sugars, uronic acids and sulphate groups. The solvent-free process, higher extraction rate and higher yields, coupled to time-saving and lower cost, make this method economical and sustainable. By using a cell viability assay, all hydrolysate fractions tested were shown to be non-toxic to Vero cells. After 3 days of treatment, no microscopically visible alteration of normal cell morphology was observed even at 500 μg mL−1. S. chordalis extracts have an effective antiviral activity with EC50 between 23.0 and 101.1 μg mL−1 at a multiplicity of infection of 0.001 ID50/cells; 100 % and 98 % cellular protection were obtained for 500 μg mL−1 of hydrolysate extracts carbohydrase C3 and blank, respectively. Other extracts from S. chordalis inhibited viral production less effectively

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Soybean is one of the leading commodities that is being developed in Indonesia. Today, the increase of soybean needs is not followed by its production capacity. Meanwhile, the area of productive land for soybean farming is decreasing due to land conversion for non-agricultural needs. One effort that can be an alternative is using marginal land by applying appropriate technology such as manure and biofertilizer. So that, it was necessary to know the composition of manure and biofertilizer, which was appropriate to increase the growth and yield of soybean plants on marginal soils. Complete Randomized Design was used in the experiment with two factors. The first factor was the ratio of manure: soil (v:v) there are 0:1, 1:1, 1:2, and 2:1. The second factor was rhizobacteria inoculum, which included without rhizobacteria, exogenous rhizobacteria, and indigenous rhizobacteria. Results showed that the composition of the best planting medium for growth and yield of soybean is manure: soil 1: 1 and 1: 2. The source of the rhizobacteria inoculum is not a significant difference to the soybean’s growth and yield. Manure and soil 1: 2 with indigenous inoculum tended to produce the best total number of nodules and effective root nodules. Manure and soil 1:1 with indigenous inoculum produce the best of seeds number. Manure and soil 1:2 or 2:1 with exogenous inoculum tended to produce the best seed index weight (g per 100 seeds).

Oil palm (Elaeis guineensis Jacq.) has become the main plantation commodity in Indonesia. Climate change phenomena and competitiveness fluctuation of palm oil commodities have led to increased need for optimized land productivity while maintaining sustainability. This research aimed to study the potential of oil palm intercropping with liberica coffee (Coffea liberica L.) in several smallholder oil palm plantations in Riau Province, Sumatera Island, Indonesia. Measurements in the middle of the non-harvesting path of oil palm showed the age of oil palm is directly proportional to the difference between air and soil temperature and relative humidity under canopy.  Oil palm roots were dominantly distributed vertically in solum 0 - 30 cm and always dominant compared to coffee at all horizontal distances observed. While the dominant root coffee distribution was in solum 31 - 60 cm. Analysis results show the tap roots extend no further than 30-45 cm below the soil surface. It was known that oil palm roots are dominantly distributed at a distance of 2-3 m from the trunk while the coffee roots are dominantly distributed at a distance of 1-2 m from the trunk. Analysis of oil palm yields in the intercropping system showed no significant decrease compared to monocropping systems with relatively the same age and production input. Coffee production per tree has decreased by 25-30% compared to the average production in monocropping systems.

The effectiveness and efficiency of operations are essential in increasing the production and profitability of oil palm plantations. It can be performed through the application of precision farming principles. One of the main obstacles for oil palm to produce optimally according to their potential is disease attacks on leaves. However, the weakness of the manual observation method is the limited ability of the observer in assessing a disease that attacks leaves. Therefore, it is necessary to have a companion system for smallholders to detect and control diseases with minimal environmental impact properly. Most of the visual-based identification efforts in precision agriculture use the concepts of computer vision and machine learning. This study's problem was the need for machine learning and computer vision-based software to identify diseases to realize sustainable oil palm plantation practices. Disease detection includes a description of the name of the disease in oil palm plantations. In this study, designing a disease recognition based on computer vision and machine learning had used the convolutional neural network (CNN). The application used the Android operating system in real-time. The test results on the model showed that the model had been able to predict with an accuracy rate of 85.5%

Learning about integrated farming could be done by visiting site locations directly. This is a problem for universities that are located in urban areas. The distance of the integrated agricultural location from the campus often raises a significant cost burden. Therefore, providing a learning model around the university would be more efficient, and students could interact and practice directly. The design concept was compiled based on a literature review. The design was produced by direct observation at Condongcatur experimental garden, then continued SWOT analysis. The design was created using software based on the information gathered. The design development included a general description of the experimental garden, landscape biophysical aspect, concept planning, and design. The resulting design was then validated by experts descriptively using a questionnaire. Meanwhile, user acceptance was measured qualitatively through an interview. Based on the results obtained, theoretically, a small-scale integrated farming design has been successfully compiled and met the requirements to be developed as an agricultural learning model. The design also received a good response from the management, which would then be followed up in the long-term development plan of the experimental garden.

Soybean is a very important crop commodity in Indonesia. Increasing soybean production on dryland as cultivation land need to be carried out. Dryland have issues with either of nutrient and water availability which is not supportable for plant growth. Therefore, the application of nano-silica and plant growth promoting rhizobacteria (PGPR) are expected to increase nutrient absorption, synthesis of plant growth hormone and increase in plant resistance to drought stress. The growth of drought-resistant plants is able to be showed through the status of stomata and trichomes on leaves. So that, this study aimed to determine the stomata and trichome performance of soybean plants of Anjasmoro cultivar using nano-silica and PGPR as fertilizers. The study design used a completely randomized design with 2 factors with three replication. The first factor was nano silica concentration i.e. 0, 100 and 200 ppm. The second factor was PGPR concentration i.e. 0, 5, 10, and 15%. Results showed that the nanosilica and PGPR applications had no significant effect on stomata and trichome status of Anjasmoro cultivar except for stomatal aperture and the ratio of the size of the stomata openings. A positive correlation has been found in the study between stomata openings and soybean yields.

Drought is a major abiotic stress that threatens the production of agricultural oil palms. Drought interferes with plant uptake of phosphorus. The goal of this study was to investigate how plant growth-promoting rhizobacteria (PGPR), bio-phosphate microorganisms, and phosphate affected oil palm growth under drought stress. The study was conducted at the Tri Dharma Research Station INSTIPER in Yogyakarta from January to May 2020, and it used a factorial and completely randomized design with two factors and three replicates per treatment. The first factor was a fertilization treatment that included P1 (PGPR), P2 (bio-phosphate microorganisms), P3 (phosphate). The second factor was a drinking interval of L1 (once per day) and L2 (once per seven days). At 120 days after planting, data were collected. The results showed that the PGPR, bio-phosphate microorganisms and phosphate had no significant effect on plant height, number of leaves, leaf area, chlorophyll content, dry weight of plants, volume of root, dry weight of root and shoot, stem diameter, number of stomata, and root-shoot ratio. Root volume, root dry weight, and root-shoot ratio were significantly affected by one-day and seven-day watering intervals. Phosphate fertilization with watering once every seven days considerably increased the width of the stomata openingsI Keywords: PGPR, Bio-Phosphate, Phosphate, Oil Palm, Drought