Agricultural machinery automatic navigation technology

In this paper, we review, compare, and analyze previous studies on agricultural machinery automatic navigation and path planning technologies. First, the paper introduces the fundamental components of agricultural machinery autonomous driving, including automatic navigation, path planning, control systems, and communication modules. Generally, the methods for automatic navigation technology can be divided into three categories: Global Navigation Satellite System (GNSS), Machine Vision, and Laser Radar. The structures, advantages, and disadvantages of different methods and the technical difficulties of current research are summarized and compared. At present, the more successful way is to use GNSS combined with machine vision to provide guarantee for agricultural machinery to avoid obstacles and generate the optimal path. Then the path planning methods are described, including four path planning algorithms based on graph search, sampling, optimization, and learning. This paper proposes 22 available algorithms according to different application scenarios and summarizes the challenges and difficulties that have not been completely solved in the current research. Finally, some suggestions on the difficulties arising in these studies are proposed for further research.

Large-scale and cost-efficient agrivoltaics system by spectral separation

Agrivoltaics (AV) offers a promising solution to address both food and energy crises. However, crop growth under photovoltaic (PV) conditions faces substantial challenges due to insufficient light transmission. We propose a large-scale and cost-effective spectral separated concentrated agricultural photovoltaic (SCAPV) system. The system utilizes concentrator modules, cell components, and dual-axis tracking systems to enhance power conversion efficiency (PCE), achieving a maximum PCE of 11.6%. After three years of successful operation, a 10 kWp power plant achieved an average annual electricity generation exceeding 107 MWh/ha. The results showed higher yields of various crops, including ginger and sweet potatoes, and significant improvements in soil moisture retention compared to open air. The improvements in PCE and microclimate validate the scalability of the SCAPV, which provides better plant conditions and cost-effectiveness, with an estimated cost reduction of 18.8% compared to conventional PV power plant. This study provides valuable insights and directions for improvement in AV.

Oscillation effect dataset on the measurement accuracy of load-cell sensor applied to the weigh basket

The dataset in the form of weight, which will be closely related to the moisture content of agricultural products that have been dried in a mechanical dryer, is important to know precisely. Changes in these properties occur very quickly, so that it is important to prepare a system that is integrated with the mechanical dryer, especially the fluidized dryer type. On the one hand, the fluidizing dryer causes a shock to the weigh basket, connected to the weighing system mechanism. Therefore, this article collects a dataset of the weight of agricultural products (maize and soybeans) that have experienced shocks on two weigh baskets that could potentially be used in fluidization-type mechanical dryers. A load-cell sensor connected to a weigh basket is used to measure the weight of the agricultural product. A new generation of IoT techniques will control the sensor. Its microcontroller will send data to the cloud server via an internet network. There were a total of 120 treatments in the raw dataset. For agriculture engineering researchers, this data will provide benefits in measuring the weight of agricultural material in the form of grain dried in a mechanical dryer, especially the type of fluidized dryer, it can be more accurately explained.

Systematic review of occupational hazards at postharvest grain operations

INTRODUCTION

Agriculture stands out in relation to the high number of occupational incidents and diseases. In this sense, grains postharvest operations, such as receiving, precleaning, drying, storage and shipping the grains, are highlighted in the number of injuries and fatalities.

AIM

To identify and extract qualitative and quantitative data related to the main occupational hazards present in grains postharvest operations at preprocessing and storage facilities.

METHODS

A systematic review was carried out in the databases of Science Direct, Scopus and Web of Science for papers published between 1980 and 2019. The abstract should have described a study related to any occupational hazard (physical, chemical, biological, ergonomic and mechanical) and at least one of the occupational hazards should be related to any postharvest operations.

RESULTS AND DISCUSSIONS

In total, 42% of 38 analysed papers were published between 2015 and 2019. Three journals were responsible for 45% of publications related to occupational hazards present in grains postharvest operations. The most part of analysed publications related to confined spaces, grain entrapment, machine entanglement and falls hazards are related to Purdue University's Agricultural Safety and Health Program which applied research in occupational safety at grains postharvest.

CONCLUSIONS

The creation of standardised internationals can collaborate to reduce occupational risks in grain storage units. It is suggested the development of monitoring technologies to obtain real-time information on noise, dust, gases and heat in postharvest operations and equipment. The use of intelligent algorithms can create prevention mechanisms for possible occupational risks and avoid injuries to employees.

Reduction of the acidity and peroxide numbers of tengkawang butter (Shorea stenoptera) using thermal and acid activated bentonites

Tengkawang fat (Shorea stenoptera), from an indigenous plant of the Kalimantan forest, has excellent potential as an alternative source of vegetable fat because it has a high level of fatty acids composition. Activated natural bentonite can be used as a bleaching agent to improve the quality of tengkawang fat. This research aims to reduce the acidity, peroxide number values and identify the physicochemical properties (fatty acid composition, nutrients, and thermal) of tengkawang butter. Initially, tengkawang samples from Nanga Yen and Sintang were pre-treated using the degumming process with 1% phosphoric acid and the neutralization process with a 1 M NaOH 10% w/w solution. The results show that the acidity (mg NaOH/g) of the tengkawang fat samples was reduced from 11.00 to 3.36 when using bentonite activated at 200 °C. The bentonite activated with 0.5 M HCl reduced the acidity to 3.61. The peroxide number (meq O₂/kg) of the tengkawang fat samples was reduced from 9.45 to 4.84 and 3.47 by bleaching with thermal-activated and acid-activated bentonites, respectively. Peroxide value correlates with β-carotene content. The smaller of the β-carotene content, the smaller the peroxide value. The acidity, peroxide number, and iodine number values from tengkawang fat after treatment adhere to the SNI 2903: 2016 standard. The main content of fatty acids in tengkawang fat is palmitic acid, stearic acid, and oleic acid. These results show that both products are suitable for the food industry in terms of the acid and peroxide numbers. The application of this research results will assist local people in increasing the economic value of the product from tengkawang plant, which is an indigenous plant from Kalimantan.

Modeling vegetative vigour in grapevine: unraveling underlying mechanisms

Mechanistic modeling constitutes a powerful tool to unravel complex biological phenomena. This study describes the construction of a mechanistic, dynamic model for grapevine plant growth and canopy biomass (vigor). To parametrize and validate the model, the progeny from a cross of Ramsey (Vitis champinii) × Riparia Gloire (V. riparia) was evaluated. Plants with different vigor were grown in a greenhouse during the summer of 2014 and 2015. One set of plants was grafted with Cabernet Sauvignon. Shoot growth rate (b), leaf area (LA), dry biomass, whole plant and root specific hydraulic conductance (k_H and L_pr), stomatal conductance (g_s), and water potential (Ψ) were measured. Partitioning indices and specific leaf area (SLA) were calculated. The model includes an empirical fit of a purported seasonal pattern of bioactive GAs based on published seasonal evolutionary levels and reference values. The model provided a good fit of the experimental data, with R = 0.85. Simulation of single trait variations defined the individual effect of each variable on vigor determination. The model predicts, with acceptable accuracy, the vigor of a young plant through the measurement of L_pr and SLA. The model also permits further understanding of the functional traits that govern vigor, and, ultimately, could be considered useful for growers, breeders and those studying climate change.

Torrefaction of non - oil Jatropha curcas L. (Jatropha) biomass for solid fuel

The use of non-oil Jatropha biomass in the energy mix as a solid fuel offers the most effective ways of utilising such resource. However, available information indicates that biomass has negative inherent properties which lower its fuel value. This negative effect can be improved by slow pyrolysis process called torrefaction where the biomass is heated in the range of 200 °C to 300 °C. In the present investigation the effects of torrefaction temperature on the solid fuel value of different Jatropha biomass materials were determined. Consequently, three types of Jatropha biomass namely; seed cake, stem and fruit cover were considered under five temperature levels (200 °C, 225 °C, 250 °C, 275 °C, 300 °C). Analysis of Variance (ANOVA) revealed that there were significant differences (P > 0.05) in bulk density, hygroscopicity, energy content and ultimate etc. The statistical analysis results indicated that there was biomass type and torrefaction temperature interaction effects on the ultimate analysis, bulk density, hygroscopicity, energy content and energy yield. The interaction effects of the factors under investigation were not observed in mass yield. Increase in torrefaction temperature generally reduced the equilibrium moisture content and volatile matters across the biomass types. However fixed carbon, carbon content, ash content and energy density were increased across the biomass types as the temperature was increased from 200 °C to 300 °C. The torrefied Jatropha seed cake biomass showed relatively enhanced fuel characteristics than the torrefied stem and the torrefied fruit husk when considering the properties under investigation.

Performance evaluation of maize hybrids in inner-plains of Nepal

Hybridization plays a vital role in increasing the production and productivity of maize. Evaluating maize hybrids in a specific environment is a key task for the hybrid maize program. The objective of this study was to identify a promising maize hybrid for winter planting in inner terai regions. Ten maize hybrids were evaluated in a randomized complete block design (RCBD) with three replications during the winter season of 2018 and 2019 at the research field of Purwanchal Agriculture Campus, Jhapa, Nepal. The results suggested that among tested hybrids, P3396 (11.18 tons ha⁻¹), Shresta (10.67 tons ha⁻¹), and Rampur Hybrid 6 (10.37 tons ha⁻¹) produced significantly higher yield in 2018 whereas P3396 (11.10 tons ha⁻¹), Shresta (10.20 tons ha⁻¹), and Ganga Kaveri (10.03 tons ha⁻¹) were the ones with the highest grain yield in 2019. Comparing both years, P3396 and Shresta consistently outperform the other hybrids in terms of grain yield, which is an important traits for the farmers. Correlation studies suggested that ear weight and thousand-grain weight showed a positive significant correlation with grain yield. Therefore, we suggest P3396 and Shresta as promising hybrids for the maize growers in the inner terai regions of Nepal.

Comparison between conventional human energy measurement and physical human energy measurement methods in wetland rice production

Measurement of human energy expenditure during crop production helps in the optimization of production operations and costs by identifying steps which that can benefit from the use of appropriate mechanization technologies. This study measures human energy expenditure associated with all 6 major rice (Oryza sativa L.) cultivation operations using two measurement methods-i.e. conventional human energy expenditure method and direct measurement with a Garmin forerunner 35 body media. The aim of this study was to provide a detailed comparison of these two methods and document the human energy costs in a manner that will identify steps to be taken to help optimize agricultural practices. Results (mean + 95%CL) revealed that the total human energy expenditure obtained through the conventional method was 25.5% higher (33.3 ± 1 versus 26.6 ± 1.3) in transplanting and 26.1% higher (30.3 ± 1.9 versus 24.0 ± 2.1) than the human energy expenditure recorded using the Garmin method in broadcast seeding method.

Similarly, during the harvesting operation, the conventional measurement and Garmin measurement methods differed significantly, with the conventional method the human energy expenditure was 89.9% higher (3.2 ± 0.4 versus 1.68 ± 0.2) in the fields using the transplanting and 88.7% higher (3.3 ± 0.5 versus 1.8 ± 0.3) in the fields using the broadcast seeding than the human energy expenditure recorded using the Garmin method. When using Garmin method, the human energy expenditure in the case of using the midsize combine harvester was 13.49% lesser (592.4 ± 67.2 versus 522.0 ± 75.1) than the case of using conventional one.

Results based on heart rate also indicated that operations such as tillage were less intensive (72 ± 3.3 bpm) compared with operations such as chemicals spraying (135 ± 4 bpm). Although we did not have a criterion measure available to determine which method was the most accurate, the Garmin measurement gives an estimate of actual physical human energy expended in performing a specific task with consider all conditions and thus more information to aid in identifying critical operations that could be optimized and mechanized.

Decision-level fusion of Sentinel-1 SAR and Landsat 8 OLI texture features for crop discrimination and classification: case of Masvingo, Zimbabwe

Radar imagery have few polarization bands which can limit the ability to do traditional digital classification. Harmonization of Sentinel-1 and Landsat 8 data despite having complementary texture information can be a challenge. The objectives of this paper are to explore texture features derived from Landsat 8 OLI and dual-polarized Sentinel-1 SAR speckle filtered and unfiltered backscatter, to aggregate classification results using Decision-Level Fusion (DLF), and to evaluate the performance of decision-level fused maps. Gray Level Co-occurrence Matrix (GLCM) is employed to derive sets of seven texture features for Landsat 8 bands and VV + VH backscatter using 5 × 5, 7 × 7, 9 × 9, and 11 × 11 window sizes. Each texture feature is stacked with a respective source image and classified using Support Vector Machine (SVM). Classified maps from the best three performers from both speckle filtered and unfiltered are aggregated with classified maps from Landsat 8 using plurality voting algorithm and compared using Z-test. Results indicate an overall classification accuracy of 96.02% from DLF images of Landsat and non-speckle filtered maps, whereas Landsat and speckle filtered achieved 94.69%. The best texture information are derived from the blue band followed by the red band, whereas speckle unfiltered textures performed better than speckle filtered textures. We conclude that integration of Landsat 8 and Sentinel-1, either speckle filtered or unfiltered, improves crop classification and speckles do not have statistically significant effects (p = 0.1208).

Non-destructive characterization of physical and chemical clogging in cylindrical drip emitters

Characteristics and deposition pattern of clogging material on cylindrical drip emitters was studied using non-destructive methods of evaluation. Two sets of four cylindrical emitter samples were collected from farm lands. One set of sample emitters was analyzed using Computed Tomography (CT). Other set was dissected and the clogging material extracted was analyzed using Energy Dispersive X-Ray Fluorescence (EDXRF) and X-Ray Diffraction (XRD). CT scans revealed the geometric properties of emitters and the spread of clogging material on the emitter surface. EDXRF analysis found statistically significant inverse relationship between the proportion of physical clogging and chemical clogging materials. XRD analysis indicated presence of physical and chemical clogging materials in their crystalline forms. Emitters having transverse flow path and the boundary optimized with curvature found with the least deposition of physical clogging materials. Corresponding proportion of chemical clogging (as Ca) was found to be much higher. All the samples were found with more clogging material closer to the outlets. Efforts to optimize emitter geometry shall also take into account the outlet area optimization and chemical clogging for obtaining best results.

Nexus between light and culture media on morphogenesis in Bacopa monnieri and saponin yield thereof

Bacopa monnieri, a well-documented nootropic plant of high commercial global demand had been explored for its effect in alleviating other diseases and symptoms. This is primarily attributed to different phytocompounds present in the plant. One of the major constituents among them are saponins. However, variation in agro-climatic conditions and choice of germplasm often affect the growth rate and yield of phytocompounds that significantly impact the efficacy of the plant and its extract. Tissue culture has been attempted to improve the yield of phytocompounds but is often restricted by higher cost and scalability. Current study explores the role of commercial hydroponic media ‘Leafy 200’ vis-à-vis Murashige and Skoog (MS) media, under different color and intensity of lights, on plant morphogenesis, biomass and saponin yield. Blue light induced more shoot differentiation than normal white light. Statistical studies performed using fractional factorial design showed no significant variations in the yield of saponins among the extracts. The study suggests that hydroponic culture to be a sustainable solution and possible substitute to tissue culture that may be exploited for scalable cultivation of the plant.

A computer system supporting agricultural machinery and farm tractor purchase decisions

Operational research, i.e. searching for optimal solutions in a situation of uncertainty and risk, can also be used to support decisions to purchase expensive agricultural machinery. Although Polish farmers receive subsidies from the EU, it does not mean they do not need to make well-thought-out purchases, because wrong purchase decisions will have long-term consequences while using machinery. The article presents the results of the IFOP - the system which has been available on the Internet for several years. It collects data on farming machinery and vehicles based on users' voluntary but subjective opinions. The authors of this article developed an original multi-criteria method of evaluating the quality of these specific products, which enabled them to make relevant rankings of brands. It is an algorithmic-heuristic method, which uses pairwise comparison tools to determine the significance ratios of the criteria. This article presents the results of the 1^st and 2^nd IFOP edition (Race Ranking), which included several dozen brands of tractors registered in Poland. More than fifty qualitative (Q) and non-qualitative (C) traits of farm tractors were taken into account. According to Polish farmers, Valtra - a Finnish brand of farm tractors, part of the AGCO concern, was the most versatile (Q = 4.39 and Q&C = 4.23). These tractors received the best opinions for their functionality, durability, ergonomics and safety.

smAvo and smaTo: A fruity odyssey of smart sensor platforms in Southern Africa

Avocado and tomato production are key agricultural sectors for many economies including South Africa. The quality of avocadoes and tomatoes that reach consumers is directly dependent on the handling at the postharvest stage. The fruit undergoes an extensive journey, and subsequently stress, comprised of several steps, including harvesting, application of postharvest treatments, packaging and transportation by road and sea to reach the export markets. To date, the quantification of these external stresses on a discrete fruit has not been measured in detail, primarily due to a lack of compatible instrumentation. This paper demonstrates a low cost, stand-alone, open source data acquisition system, termed smAvo and smaTo, that can be introduced effortlessly to monitor agricultural processing facilities and transportation networks. The miniaturised Arduino sensor platform is enclosed within a waterproof enclosure and surrounded by a 3D printed shell manufactured from morphologically compatible materials. The software is customisable to the needs of the research project or individual transportation phases under study, providing both extensive environmental data and high-frequency tri-axis acceleration measurements that are crucial to understanding the dynamic processes that directly affect the final quality of the fruit. Four successful field trials demonstrate the fidelity of both the smAvo and smaTo platforms.

Towards an optimal hybrid solar method for lime-drying behavior

Lime is one of the most commonly consumed medicinal plants in Indonesia, which must be dried to preserve its quality, but mostly by using traditional, ineffective drying method. Therefore, this study aims to investigate lime drying process a hybrid solar drying method. The hybrid solar dryer consisted of a solar dryer and Liquefied Petroleum Gas as the supplementary heater. The drying process was conducted until there was no significant weight decrease, with the drying temperature of 40, 50, 60, 70, and 80 °C. Thin-layer modeling and quality analysis were also conducted. The experimental results indicated that 5 h was required to sufficiently dry the lime at 80 °C, while drying at 40 °C took 24 h to finish. The drying rate curve of lime suggested that lime drying mostly happened during the falling-rate period. Moreover, the average efficiency of the hybrid solar dryer ranged from 5.36% to 38.61%, which increased with temperature. From the 10 thin-layer drying models used, the Wang and Singh model was the most suitable to describe the drying behavior of lime. The effective diffusivity values of the limes and the activation energy value during hybrid solar drying were within their respective acceptable range for agricultural products. However, as the drying temperature was increased from 40 to 80 °C, the total phenolic content and vitamin C content decreased, from 87.3 to 27.8 mg GAE/100 g dry limes and 0.118 to 0.015 ppm, respectively. It can be concluded that hybrid solar dryer is able to sufficiently dry the lime, with acceptable drying time and dryer efficiency, although using high drying temperature will decrease the quality of dried lime. Further modifications and improvements to the hybrid solar dryer are required to maximize the quality of dried lime while still maintaining fast and effective drying process.

Characterization of the acyl-ACP thioesterases from Koelreuteria paniculata reveals a new type of FatB thioesterase

Koelreuteria paniculata is a deciduous tree, popular in temperate regions for its ornamental value, which accumulates unusual cyanolipids in its seeds. The seed oil of this plant is rich in the unusual cis-11-eicosenoic fatty acid (20:1, or gondoic acid), a monounsaturated oil of interest to the oleochemical industry. In higher plants, de novo fatty acid biosynthesis takes place in the plastids, a process that is terminated by hydrolysis of the thioester bond between the acyl moiety and the ACP by acyl-ACP thioesterases. The specificity of acyl-ACP thioesterases is fundamental in controlling the fatty acid composition of seed oil. To determine the mechanisms involved in fatty acid biosynthesis in K. paniculata seeds, we isolated, cloned and sequenced two cDNAs encoding acyl-ACP thioesterases in this plant, KpFatA and KpFatB. Both of them were expressed heterologously in Escherichia coli and characterized with different acyl-ACP substrates. The K. paniculata FatB2 displayed unusual substrate specificity, so that unlike most FatB2 type enzymes, it displayed preference for oleoyl-ACP instead of palmitoyl-ACP. This specificity was consistent with the changes in E. coli and N. benthamiana fatty acid composition following heterologous expression of this enzyme. KpFatB also showed certain genetic divergence relative to other FatB-type thioesterases and when modelled, its structure revealed differences at the active site. Together, these results suggest that this thioesterase could be a new class of FatB not described previously.

Performance evaluation of digestate spreading machines in vineyards and citrus orchards: preliminary trials

This research was carried out to evaluate a local biogas plant's solid fraction digestate spreading in a citrus orchard and vineyard. Three spreaders were tested: a broadcast manure spreader in the citrus orchard, and two cylindrical-shaped spreaders in the vineyard; the first one working in broadcast configuration, the second one in localised configuration. Experimental tests assessed effective work time, mean work speed, digestate flow rate and longitudinal and transverse spreading uniformity. In the citrus orchard, the digestate was mainly spread in the centre of the inter-row (around 66%), with low variability between inter-rows (coefficient of variation (CV) equal to 2.7%) and much higher variability within inter-rows (CV = 31.4%). The effective work time was about 28% of total field time and real work capacity was about 0.96 ha h⁻¹. In the vineyard, broadcast spreading released more on the right compared to the left (ratio 1.74) due to distributor disc rotation, whereas localised spreading was more uniform. Overall, variability between inter-rows had CV = 15.1% and within inter-rows CV = 33.3%. Real work capacity was about 0.16 ha h⁻¹ for broadcast spreading and 0.26 ha h⁻¹ for localised spreading. A preliminary economic evaluation, based on sub-contractor tariffs, produced the mean tariff for transaction and spreading costs of digestate in farms near the biogas plant.

An automatic visible-range video weed detection, segmentation and classification prototype in potato field

Weeds might be defined as destructive plants that grow and compete with agricultural crops in order to achieve water and nutrients. Uniform spray of herbicides is nowadays a common cause in crops poisoning, environment pollution and high cost of herbicide consumption. Site-specific spraying is a possible solution for the problems that occur with uniform spray in fields. For this reason, a machine vision prototype is proposed in this study based on video processing and meta-heuristic classifiers for online identification and classification of Marfona potato plant (Solanum tuberosum) and 4299 samples from five weed plant varieties: Malva neglecta (mallow), Portulaca oleracea (purslane), Chenopodium album L (lamb's quarters), Secale cereale L (rye) and Xanthium strumarium (coklebur). In order to properly train the machine vision system, various videos taken from two Marfona potato fields within a surface of six hectares are used. After extraction of texture features based on the gray level co-occurrence matrix (GLCM), color features, spectral descriptors of texture, moment invariants and shape features, six effective discriminant features were selected: the standard deviation of saturation (S) component in HSV color space, difference of first and seventh moment invariants, mean value of hue component (H) in HSI color space, area to length ratio, average blue-difference chrominance (Cb) component in YCbCr color space and standard deviation of in-phase (I) component in YIQ color space. Classification results show a high accuracy of 98% correct classification rate (CCR) over the test set, being able to properly identify potato plant from previously mentioned five different weed varieties. Finally, the machine vision prototype was tested in field under real conditions and was able to properly detect, segment and classify weed from potato plant at a speed of up to 0.15 m/s.

Institutional strengthening model of oil palm independent smallholder in Riau and Jambi Provinces, Indonesia

The oil palm independent smallholder (farmer) is one of the important actors in maintaining the continuity of the production cycle in the oil palm agro-industry supply chain in Indonesia. Various fundamental problems faced by the independent smallholder are related to land legality as well as their limited ability to manage good agricultural practices, access funds and information on current prices, and use of quality and agricultural production facilities. The institutional strengthening of the independent smallholder requires attention and support from government and other business actors in the supply chain of the oil palm agro-industry. This study aims to obtain a model of institutional strengthening through the application of the enrich seven steps of soft system methodology. The assumptions that must be fulfilled in strengthening this institution were described. The institutional strengthening model was developed in three stages, i.e., the establishment of smallholder corporations, the establishment of independent cooperatives, and the revitalization of the Indonesian oil palm independent smallholder association. Various individual strengthening actors were investigated and then integrated. The suggested institutional strengthening model involved cooperatives, smallholder farmers groups, and the oil palm mill, supported by regulatory, financial, and input provider agencies with a mutual partnership program.

Exergetic sustainability and economic analysis of hybrid solar-biomass dryer integrated with copper tubing as heat exchanger

The aim of this study is to present a new hybrid solar-biomass dryer and carry out thermal analysis based on energy and exergo-sustainability analysis considering all the available exergy stream of solar radiation, air stream through the collector, and exergy of the moisture in the product. The research also presented the environmental impact and economic analysis of using the dryer. Performance evaluations show that at collector efficiency of 20.81%–21.89 %, the developed solar dryers can save between 10 – 21hrs of drying time in drying 5 mm thick plantain slices to 15 % moisture content from initial moisture content of 66 % w.b when compared to drying under the open sun. The improvement potential ranged from 0.036 to 20.6W while the waste exergy ratios and sustainability index ranged from 0.38 - 0.55 and 2.3–6.11 respectively. Application of the solar dryers can save between 44 -3074 of CO₂ entering the atmosphere per year while 2.94 to 205.43$ could also be saved at 10–100% rate of usage when compared to diesel fired dryer. The total energy consumption for drying ranges between 5.52 and 35.47 MJ, while the specific energy consumption ranged from 4.3 to 26.2 kWh/kg. The exergy efficiency ranges from 5.6 – 95.13 % during the sunshine hours.

Variation of Jatropha curcas seed oil content and fatty acid composition with fruit maturity stage

Seed oil production in Jatropha seeds through different maturity stages have been investigated. In order to meet the high demand of oil (feedstock) for large scale biodiesel production, increasing oil content or output in Jatropha seeds is required. Jatropha fruits were harvested at four different maturity stages and the seeds were analysed for oil content. The seed oil was analysed for fatty acid profile. Results from four different geographical locations investigated namely; Mmadinare, Thamaga, Maun and Shashe, have shown a similar trend in lipid accumulation in Jatropha seeds as the fruits mature from green to brown dry. However, maximum oil content in seeds varies with geographical location. Accumulation of oil in Jatropha seeds during maturation follows a parabolic trend and reaches its peak when fruits are yellow. Oil yield in Jatropha seed kernels ranges from 38.7% to 45.8% for the four maturity stages investigated. Overall results have revealed that harvesting Jatropha fruits when they are yellow increases seed oil output by 6-9% when compared to harvesting the fruits when they are brown dry. There is a relationship between the trend in fatty acid composition in Jatropha seed oil and seed oil content trend during fruit maturation. Based on the trend of unsaturated fatty acids in Jatropha seed oil, particularly linoleic and oleic acids, it can be deduced that reduction of seed oil content from yellow brown to brown dry stage is a result of breakdown of some of the unsaturated fatty acids.

Specific energy requirements and soil pulverization of a combined tillage implement

Reducing energy use in soil preparation has become increasingly important since it is a major cost in planting. Experiments were conducted with a combined tillage implement consisting of a subsoiler and a rotary harrow to reduce the cost due to step reduction in soil preparation. Three tillage operations, two forward speeds, and two rotational rotor speeds were determined as input factors in this study. Soil clod size, performance parameters, and the specific energy requirements of a combined tillage implement were investigated. The field experiments were using two different soil conditions. Increasing the rotor speed from 299 to 526 rpm decreased the mean soil clod diameter at a depth of 0–200 mm from 22.98 to 19.83 mm and from 31.77 to 26.57 mm for fields 1 and 2, respectively. The specific energy requirement was affected significantly by rotor speed and tillage operation. The specific energy requirements for the combined tillage implement with an on-frame pivot joint and an on-pivotable-shank joint were less by 10.4 and 21.1% and by 18.4 and 24.7%, for fields 1 and 2, respectively, compared to the total power requirement for the separate use of a subsoiler and a rotary harrow.

The impact of land use and land cover (LULC) dynamics on soil erosion and sediment yield in Ethiopia

The central highlands of Ethiopia are characterized as a region of high rates of land degradation and soil erosion. This study aimed to estimate total amount of soil loss and sediment yield using RUSLE model within GIS environment. LULC maps of 1973–2015 were used to evaluate the impact of land use change on soil loss and sediment yield. Each model parameter and sediment deliver ration was computed by using Williams and Berndt empirical equation. The net soil erosion and sediment yield at the Guder river mouth and soil risk map was estimated for the watershed. LULC dynamic for the study period and watershed have shown that there existed a rapid conversion of vegetated land uses to human modified land uses. The study revealed that the mean soil loss from the watershed ranges between 25 and 30 t/ha−1 yr−1 which accounted 25.8, 28.7 and 30.3 t/ha/yr for 1973, 1995 and 2015 periods respectively. The estimated total soil loss in 1973, 1995 and 2015 periods were 198Mt yr-1, 221Mt yr-1 and 239Mt yr-1 respectively. The mean sediment yield estimated was 6.79, 8.65 and 9.44t ha-1 yr-1 for 1973, 1995 and 2015 periods respectively. The sediment deliver ratio (SDR) of the watershed ranged between 0 and 0.26. The spatial distribution of SDR showed that the highest value was recorded on central and eastern part of the watershed. Prioritizing erosion host spot areas is recommended to rehabilitate degraded lands using suitable soil and water conservation structures.

Impacts of land surface model and land use data on WRF model simulations of rainfall and temperature over Lake Tana Basin, Ethiopia

The Weather Research and Forecasting (WRF) model is one of the regional climate models for dynamically downscaling climate variables at finer spatial and temporal scales. The objective of this study was to evaluate the performance of WRF model for simulating temperature and rainfall over Lake Tana basin in Ethiopia. The WRF model was configured for six experimental setups using three land surface models (LSMs): Noah, RUC and TD; and two land use datasets: USGS and updated New Land Use (NLU). The performances of WRF configurations were assessed by comparing simulated and observed data from March to August 2015. The result showed that temperature and rainfall simulations were sensitive to LSM and land use data choice. The combination of NLU with RUC and TD produced very small cold bias (0.27 °C) and warm bias (0.20 °C) for 2m maximum temperature (Tmax) and 2m minimum temperature (Tmin), respectively. WRF model with RUC and NLU captured well the observed spatial and temporal variability of Tmax, while TD and NLU for Tmin. Moreover, rainfall simulation was better with NLU; especially NLU and Noah configuration produced the smallest mean bias (2.39 mm/day) and root mean square error (6.6 mm/day). All the WRF experiments overestimated light and heavy rainfall events. Overall, findings showed that the application of updated land use data substantially improved the WRF model performance in simulating temperature and rainfall. The study would provide valuable support for identifying suitable LSM and land use data that can accurately predict the climate variables in the Blue Nile basin.

The effects of temperature and duration of thermal pretreatment on the solid-state anaerobic digestion of dairy cow manure

Cellulosic substrates such as dairy cow manure often yield low volumes of biogas and low concentrations of methane when digested anaerobically. Thermal pretreatment of dairy cow manure was investigated to determine if pretreatment temperature and duration can be optimized to maximize biogas yield and methane concentration. A central composite rotatable design was used to select combinations of temperature and duration. Based on measured data, statistical models were generated to estimate the biogas yield and methane concentration during digestion. The highest biogas yields were from the untreated samples and samples treated at the center temperature and duration of the statistical model (125 °C, 37.5 min). The model predicted the optimum pretreatment conditions of 140 °C for 30 minutes. Under the conditions of this experiment, temperature and duration had no significant effect on the biogas yield and methane concentration. This lack of significance may indicate that thermal pretreatment may be an unnecessary step in the anaerobic digestion of dairy cow manure, which could reduce capital and operating costs for the industry.

Measurement of aspartic acid in oilseed rape leaves under herbicide stress using near infrared spectroscopy and chemometrics

Oilseed rape is used as both food and a renewable energy resource. Physiological parameters, such as the amino acid aspartic acid, can indicate the growth status of oilseed rape. Traditional detection methods are laborious, time consuming, costly, and not usable in the field. Here, we investigate near infrared spectroscopy (NIRS) as a fast and non-destructive detection method of aspartic acid in oilseed rape leaves under herbicide stress. Different spectral pre-processing methods were compared for optimal prediction performance. The variable selection methods were applied for relevant variable selection, including successive projections algorithm (SPA), Monte Carlo-uninformative variable elimination (MC-UVE) and random frog (RF). The selected effective wavelengths (EWs) were used as input by multiple linear regression (MLR), partial least squares (PLS) and least-square support vector machine (LS-SVM). The best predictive performance was achieved by SPA-LS-SVM (Raw) model using 22 EWs, and the prediction results were R_p = 0.9962 and RMSEP = 0.0339 for the prediction set. The result indicated that NIR combined with LS-SVM is a powerful new method to detect aspartic acid in oilseed rape leaves under herbicide stress.