Seaweeds have been utilized by mankind for several hundreds of years, for the cosmetic applications, for the food industry, as a feed for livestock, or as food directly, and for medicinal purposes by extraction of compounds with antiviral, antibacterial, or antitumor activity. In addition, as a possible renewable raw material for biorefining applications, seaweeds have attracted attention for the production of a variety of biofuels, such as bioethanol and biogas, especially because they contain a lot of carbohydrates. With the rapid development of this seaweed industry, a mass of waste release into the environment leads to very serious pollution problems. Nowadays, this waste is used to produce agriculture biofertilizers in commercial scale. The production of biofertilizers from seaweeds sources has been reported using several experimental conditions in laboratory scale by using enzymes such as cellulases and xylanases. These enzymes degrade seaweed processing waste to low molecular fragments, which can be easily absorbed by plants as biofertilizer.

This work is based on the patents analysis which is a family of techniques and tools for studying the information present within and attached to patents, a major form of intellectual property. It will be divided into three parts: (i) The first part reviews the state of the art by introducing what has been patented in relation to seaweed-based biofertilizers. (ii) The second part provides a detailed analysis of the patentability of formulations and process. (iii) The third part explores the alternatives to patents as a means for incentivising innovation as well as benefit sharing of the results and applications of scientific research. Finally, in the form of conclusions, a portfolio approach is proposed for effective innovation and fair dissemination of information concerning the formulation of biofertilizers based on algae for the benefit of agriculture.

Soil enzymes secure our food security; however, they are sensitive to abiotic stresses. Solving the globe issues of food waste by Bokashi may be secure for our food security. Food waste Bokashi substrate (as soil treatment) and leachate (as seed priming agent and liquid fertilizer) were used to grow bok choy 4 cycles. Soil pH, cation exchangeable capacity, moisture content, aggregate stability and enzyme activity were determined. All variables were positive corelated except catalase activity. Bokashi treatment significantly increased soil pH closed to neutral and CEC. Anaerobic Bokashi treated soil significantly reduced soil catalase activity, however it was gradually increased along the growing cycle. Bokashi treatment significantly maintains the aggregate stability along growing cycles. Hence, Bokashi substrate was recommended to improve soil quality such pH, CEC and urease activity.

Soil enzyme activity is good indicator of soil quality. Urban soil has poor quality for plant growth. In the meanwhile, food waste is a huge issue in most of the area. Burger dirt with the use of food waste has potential to improve soil quality. The objective of this study was to determine the effect of soil enzyme change with Burger dirt. It was cooperated at 1:1 and 1:2 soil to Burger dirt ratio for 2, 4, 6 and 8 weeks and thus determine the soil enzyme activity, pH and moisture content. Soil pH was stabilized to 7 significantly at 6 and 8 weeks of restoration period or 1:2 ratio. The 1:2 soil to Burger dirt ratio showed significantly increased soil moisture content from 12.00±0.286 to 14.3±2.11%. Soil urease activity is enhanced from 1.330±0.0407 to 10.5±0.315 mg NH₃-H at 8 weeks of restoration period and vice versa in catalase activity (0.525±0.0104 to 0.0839±0.00535 mL 0.02 mol/L KMnO₄/g dry soil). An 8-week soil restoration period with 1:2 ratio of soil to Burger dirt was recommended to improve the soil enzyme activity and pH.

Fig fruits are an important horticultural crop, which are traditionally grown in Albania, and has recently attracted the worldwide attention of many researchers, fruit cultivators, processors, and consumers. This study determined the content of polyphenolic compounds, antioxidant activity and some physico-chemical parameters of black and white varieties of Shëngjinas and Kraps autochthonous fig (Ficus carica L.) fruits, which were collected in Tirana, Albania. The influence of maturity stage on physico-chemical parameters such as dry matter, total soluble solids, titratable acidity, ash, vitamin C, total polyphenols content, flavonoids, anthocyanins, and antioxidant activity, were investigated at three maturity stages during the May-June harvesting period. For determination of physico-chemical parameters, the official methods were used, whereas for determination of total phenolic content, the Folin-Ciocalteu method was used. For total flavonoid content, the aluminum chloride colorimetric method was used. For total anthocyanin content, the pH difference method for used, and for antioxidant activity, the ABTS (2,2’-azinobis (3-ethylbenzthiazoline-6-acid) assay was used. In this study black varieties resulted in 86.92% higher content of polyphenols, and a decrease was noted during fruit development (till 59.16% in third maturity stage), total flavonoid content varied around 12.02-65.08 mg catechin equivalent/100 g, and antioxidant activity ranged 119.09-181.65 mg ascorbic acid/100 g, whereas anthocyanins were found in black varieties ranging 4.23-48.98 mg cyaniding-3-glucozide/ 100 g. Black varieties had higher polyphenol compounds and antioxidant activity, whereas Shëngjinas variety resulted in the highest values. During fruit development a decrease of 1.91-fold and 2.45-fold was seen, respectively in the second and third stage of maturation compared to the first one. The selected fig varieties may provide a good source of phytochemicals and nutrients, and the generated data may serve as a guide for its consumption in fresh state, or to be further processed.

Accurate crop classification using remote sensing based satellite imageries approach remains challenging due to mix in spectral signatures. Employing Unmanned Aerial Vehicle (UAV) together with satellite imageries is believed in improving crop classification at field. Accordingly, this study aims to evaluate the potential of UAV images by blending with Sentinel 2A satellite images for crop field classification in Ethiopian agricultural context. The main purpose of the blending is to upgrade and or improve the lower resolution of the data source that is the sentinel 2A data which was 10m resolution. In the study, UAV data was used and preprocessed. The preprocessing includes camera calibration, photo alignment, dense point cloud generation based on the estimated camera positioning of scouting crop types. Then, orthomosaic UAV image was generated from single dense point cloud. Then, the processed UAV data was fused with Sentinel 2A (medium resolution) satellite data using Gram Schmidt pan sharpening method.this method is the most approach that it can run large data sets of spatial resultions. For crop classification, the Random forest (RF) machine-learning algorithm and Maximum likelihood methods were applied. Apart from the UAV and S2A data, field data was collected for training the crop classification. The point field data was collected from Teff, Wheat, Faba bean, Barley and Sorghum crop fields The results show that RF classifier algorithm classifies the crop types with 94% overall accuracy whereas the Maximum likelihood classifier with 90% overall accuracy. This implies that fused image has a potential to be used for crop type classification together with relatively better classification technique with high accuracy level

Water scarcity is the main cause of severe yield reduction in arid areas by creating harmful effects on the morphological, physiological, and biochemical characteristics of the plant. The application of soil amendments is a strategy to mitigate the adverse impact of drought stress. Superabsorbent polymers (SAPs) are eco-friendly materials, which have incredible water absorption ability and water holding capacity in the soil, because of their unique biochemical and structural properties. This study aimed to investigate the effects of superabsorbent polymers on characteristics of sesame under different irrigation intervals. This experiment was performed in a split plot factorial with three replicates, arranged in RCBD with three drought factors as the main plot (Irrigation interval using cumulative evaporation from class A pan: 80 mm (I₁), 160 mm (I₂), and 240 mm (I₃), and superabsorbent (SAPs) STOCKOSORB in three levels (0, 100, 200 kg ha^-1) (Z₀, Z₁, Z₂) as the subplots. The application of superabsorbent polymers (200 kg ha^-1) increased the number of capsules per plant, the number of seeds per capsule, and grain yield by 15.8%, 27%, and 39%, respectively, compared with the control. Moreover, the application of superabsorbent polymers mitigated the adverse effects of increasing the irrigation intervals in biological yield, whereby biological yields in severe stress conditions (I₃) were similar to those obtained in mild stress (I₂). Our data demonstrated that the application of superabsorbent polymers could be a promising approach to improve plant yield, especially under water deficit conditions.

This article investigates the empirical distributional impact of the adoption of Climate-Smart Agricultural Technologies (CSAT) on-farm households’ welfare using a data set that covers four regions, 32 communes, 320 villages, and 2240 households in Mali. Using the Instrumental Variable Quantile Regression model, the paper addresses the potential endogeneity arising from the selection bias and the heterogeneity of the effect across the quantiles of the outcome variables’ distribution. Results show that the adoption of CSAT is positively associated with improved households’ welfare and the farmers' decision to adopt any CSAT is positively and statistically influenced by access to credit, contact with extension agents, participation in training, access to information through the television and being a member of any organization such as cooperative society. Moreover, results further show that the effect of adoption of CSAT on household welfare varied across the different households. In particular, the results show that the impact of the adoption of CSAT on households’ welfare is generally higher for the poorest (people located at the bottom tail of the distribution) end of the welfare distribution. The findings, therefore, highlight the pro-poor impact of the adoption of CSAT in the rural Malian context, as well as the need to tailor the CSAT interventions toward specific socio-economic segments of the rural population in Mali.

The increase in the use of chemical fertilizers soil quality deteriorates, increases greenhouse gas emissions into the air, and water pollution. Also, livestock manure increases GHG, mainly due to the emission of dinitrogen monoxide. And the agricultural sector accounts for the largest share of NH₃ emissions in the European Union. Therefore, granular organic fertilizers are used to supplement the soil with the necessary substances for plants and reduce the negative effects of chemical fertilizers and livestock manure. The aim of this study is to determine the costs of manure and manure pellet fertilization, as well as the impact on the environment. The research was conducted in Lithuania. Costs are calculated for mechanized technological operations (fertilizer loading, transportation, and spreading). Different rates of organic fertilizer were used for costs calculation: manure 16.0 t ha⁻¹, manure pellet 2.0 t ha⁻¹. Experimental research of NH₃ emissions is performed on a laboratory stand using the mass flow method of laser spectroscopy. Samples were placed in a wind tunnel section and sealed with a cover. A gas analyzer GME700 was used to measure the ammonia gas concentration. At the start of the study, the gas analyzer was programmed to record the average NH₃ gas concentration values every minute. Experimental tests are performed until a crust forms on the surface manure. Costs have been obtained significantly higher (approximately 87.39 %) for mechanized technological operations when manure is fertilized compared to manure pellets. However, the price of manure is significantly lower (approximately 96 %). The average ammonia emission from manure pellets is significantly lower compared to manure.

The impact of ongoing Covid-19 pandemic caused disastrous food shortages and increased food prices due to disruption of agricultural systems and activities. In the aftershock of the pandemic, the global economy and infrastructure are more fragile than we realize since the food supply chain has been disrupted. Less consumption of nutrient-rich foods made the people more susceptible to Covid-19 infection during the pandemic. The situation resulted in a pivot to develop technology for economic and year-round production of nutrient-rich vegetables to alleviate malnutrition and to improve immunity of human body. This presentation will focus on the profitability of hydroponic vegetable production, the probable market availability of product in local markets and consumer’s choice of the hydroponic vegetables. Financial management for establishment of polyhouse and hydroponic systems, and the ways of having a standard profit to the grower and/or shareholders were explained. The paper also covered the advantages and benefits of hydroponic farming over conventional soil-based farming, the amount of profit that can be earned from a unit area of hydroponic farming technique, the risks of the technique and how the risks can be overcome. The procedure of establishing the polyhouses for running a profitable hydroponic vegetable farm by the low-income rural community were outlined.

One of the problematic sectors according to GHG and ammonia emissions quantities is agriculture. Without endangering food production (and in order to intensify), greenhouse gas emissions from all sources in animal husbandry will be comprehensively reduced by applying a holistic process management model to one of the most popular cowsheds in Lithuania (260-seat boxing cowshed, cows are milked on site, computerized management of technological processes, productivity 8600 kg of milk, barn system, liquid manure). Considering the cow keeping technology applied on the farm, the equipment used and the feed production and ration system, a model for the management of technological parameters of production processes is prepared for the farm. This model is a trade-off between animal welfare, cow productivity, production costs and GHG and ammonia emissions. The aim of adapting the integrated model is to fully control, manage and optimize milk production processes through bio- and engineering innovations, to implement climate-friendly feed production, feeding and feed rationing systems, to improve animal housing and working conditions and to reduce greenhouse gas and ammonia emissions without increasing production costs. The environmental impact assessment was performed with SimaPro 9.1 process modeling software. Data from milk production, biomass cultivation, and feed preparation, transportation, and equipment were used from the Ecoinvent v3 database. Based on the LML-I calculation methodology, the effect of processes was determined. In order to quantify the potential emissions in the dairy farm, the emission factors were estimated using a life cycle assessment method, per functional unit - 1000 kg of standardized milk. Grass silage, bread silage and feed concentrate were found to account for the largest share of gas emissions - 26.09% (107.39 kg CO2 eq. FU-1), 22.70% (93.44 kg CO2 eq. FU-1) and 21.85% (89.92). kg CO2 eq FU-1) - total CO2 emissions during the process. Considering the critical points of the classic SC scenario, the cultivation technology has been adjusted, where 50% of N fertilizers are replaced by BIO products. Both scenarios (Classic SC and Bio SC) were evaluated for comparison. The use of biopreparations in the categories reduced the environmental impact from 0.1% to 45.7% in dairy production technology grass silage, barley grain, hay production and corn silage stocks. The carbon footprint of the average Lithuanian dairy farm was also lower, i. 392.75 / 1000 = 0.393 kg CO2 eq kg-1 milk). Based on this methodology, it is possible to assess many dairy farms and address critical points in an integrated way, which can help to improve the quality of dairy production and the environment.