Energy balance of sunflower production

ArticleThe aim of the present study was to make an energy analysis of sunflower crop in the Trakya Region of Turkey, to evaluate the potential for using it as bioenergy source. Actual data for the common cropping practices applied in the region were collected with questionnaires given to the farmers. Literature data were used to obtain necessary energy indices. The collected information was used to establish energy budgets. Two alternative scenarios were examined: 1st - Using only the seed for biofuel production and 2nd -using the seed for biofuel and the stalks as biomass for bioenergy. The results showed that sunflower presented positive energy balance for both cases. Net energy was 35,334 MJ ha-1 when only the seed was taken into account and 87,308 MJ ha-1 for both seed and stalks. Energy efficiency was 3.67 and 7.34 respectively. Fertilization was the most energy intensive input (6,594 MJ ha-1 ) accounting for 48–50% of the total inputs. Tillage was the second most energy intensive input (3,595 MJ ha-1 ) accounting for 26–27% of total inputs. There were 6 different tillage operations such as ploughing, 4 machinery passages for seedbed preparation and hoeing in the sunflower production. All these operations increased energy inputs of the tillage. The total energy inputs were relatively low because it was possible to achieve high yields without irrigation

Fossil Fuel Deficit-Conservation Tillage and on Farm Biofuel Production to Cope With the Problem

Abstract The limited resources of fossil fuels along with the highly fluctuating prices, call for investigation to find diesel alternatives. Biofuels from vegetable oils, seems the easiest accessible substitutes as they can be used in conventional diesel engines without lot of modifications. There are though two mainstream attitudes on this approach. The one points that it is immoral to divert environmental resources from food production to energy production when the global population increases and the other claims that without mechanization and fuel to power it, food production will finally be decreased. Conservation tillage adoption may contribute in significant fuel savings by eliminating tillage operations. If they would be combined with on farm biofuel production, they would certainly require less land to be devoted for this purpose. In the present work, based on data of a long term tillage experiment, it was calculated the percentage of land that would be required to cultivate with a biofuel crop (sunflower for instance) in order to cover the fuel requirements of an arable farm, for three alternative tillage methods: conventional (CT), reduced (RT) and no-tillage (NT). The results indicated that in CT, the 11% of the land would be enough to provide the biofuel for all the field operations (except irrigation). In RT, due to lower fuel consumption, the 7.5% of the land would be sufficient. That means that a 3.6% yield reduction is justified. In NT, only the 3.5% of the land is required to produce the biofuels justifying a 7.7% yield reduction. This sets the limits of yield reduction that can be acceptable. However we have to add in this balance the environmental effects of using conservation tillage like erosion reduction, increasing soil organic matter and biodiversity maintenance

Assessing Durum Wheat Yield through Sentinel-2 Imagery: A Machine Learning Approach

Two modeling approaches for the estimation of durum wheat yield based on Sentinel-2 data are presented for 66 fields across three growing periods. In the first approach, a previously developed multiple linear regression model (VI-MLR) based on vegetation indices (EVI, NMDI) was used. In the second approach, the reflectance data of all Sentinel-2 bands for several dates during the growth periods were used as input parameters in three machine learning model algorithms, i.e., random forest (RF), k-nearest neighbors (KNN), and boosting regressions (BR). Modeling results were examined against yield data collected by a combine harvester equipped with a yield mapping system. VI-MLR showed a moderate performance with R2 = 0.532 and RMSE = 847 kg ha−1. All machine learning approaches enhanced model accuracy when all images during the growing periods were used, especially RF and KNN (R2 > 0.91, RMSE < 360 kg ha−1). Additionally, RF and KNN accuracy remained high (R2 > 0.87, RMSE < 455 kg ha−1) when images from the start of the growing period until March, i.e., three months before harvest, were used, indicating the high suitability of machine learning on Sentinel-2 data for early yield prediction of durum wheat, information considered essential for precision agriculture applications. © 2022 by the authors

Energy balance of sunflower production

The aim of the present study was to make an energy analysis of sunflower crop in the Trakya Region of Turkey, to evaluate the potential for using it as bioenergy source. Actual data for the common cropping practices applied in the region were collected with questionnaires given to the farmers. Literature data were used to obtain necessary energy indices. The collected information was used to establish energy budgets. Two alternative scenarios were examined: 1st- using only the seed for biofuel production and 2nd -using the seed for biofuel and the stalks as biomass for bioenergy. The results showed that sunflower presented positive energy balance for both cases. Net energy was 35,334 MJ ha-1 when only the seed was taken into account and 87,308 MJ ha-1 for both seed and stalks. Energy efficiency was 3.67 and 7.34 respectively. Fertilization was the most energy intensive input (6,594 MJ ha-1) accounting for 48–50% of the total inputs. Tillage was the second most energy intensive input (3,595 MJ ha-1) accounting for 26–27% of total inputs. There were 6 different tillage operations such as ploughing, 4 machinery passages for seedbed preparation and hoeing in the sunflower production. All these operations increased energy inputs of the tillage. The total energy inputs were relatively low because it was possible to achieve high yields without irrigation. © 2017, Eesti Pollumajandusulikool. All rights reserved

Level of contamination assessment of potentially toxic elements in the urban soils of Volos city (central Greece)

A three-year study, designed to record the level of potentially toxic elements within the urban complex in the city of Volos, Greece, was carried out between 2018 and 2020. For the needs of the aforementioned study, 62 surface (0-15 cm) soil samples were collected each year (i.e., 186 samples in total) from an urban area of 3.65 km2, and the average value of pseudo-total metal concentration was measured. Soil pollution indices, such as the contamination factor (CF) and the geo-accumulation index (Igeo), were estimated regarding each of the metals of interest. The respective thematic maps were constructed, and the spatial variability of the contamination degree was displayed. Higher values of the CF and Igeo were obtained near the heavy traffic roads and beside the railway station, the bus stations, and the commercial port. The maps based on the pollution indices, along with the database that was constructed using the appropriate mathematical tools of geostatistical analysis, may be a useful tool for monitoring, prediction, and continuous verification of contamination in the urban soils of Volos city. © 2021 by the authors. Licensee MDPI, Basel, Switzerland

Effects of Alternative Fertilization and Irrigation Practices on the Energy Use and Carbon Footprint of Canning Peach Orchards

Throughout peach orchards in Greece, plant protection, fertilization and irrigation are often conducted empirically, negatively affecting energy use efficiency and greenhouse gas emissions (GHG emissions). The aim of this study was to apply alternative fertilization and irrigation practices in canning peach orchards to improve nutrient and irrigation water management and to assess yield, energy input–output and the carbon footprint of the alternative cultivation practices for three important clingstone cultivars of different ripening periods. Energy use analysis revealed that the cultivation practice with the highest energy use was almost always irrigation, followed by fertilization, plant protection, weed control and pruning. Electricity, fuels, fertilizers and machinery presented the highest energy requirements. Alternative fertilization, in combination with deficit irrigation (DI), was more energy efficient compared to farmers’ practices in all cultivars based on energy use efficiency, energy productivity and specific energy. Irrigation was the cultivation practice with the highest impact on GHG emissions due to electricity and, secondly, to fuel consumption. Alternative fertilization and DI decreased the intensity (kg CO2eq kg−1) of the emitted GHG compared to farmers’ practices. In conclusion, alternative fertilization and irrigation practices improved energy use efficiency and decreased the carbon footprint of the canning peach orchards by improving yield and decreasing fertilizer and irrigation water input. © 2022 by the authors

Effectiveness of Three Terminating Products on Reducing the Residual Moisture in Dwarf Castor Plants: A Preliminary Study of Direct Mechanical Harvesting in Central Greece

The contribution of castor oil for reaching the targets set by RED1 and RED2 in Europe can be tangible if the problem related to the mechanical harvesting is overcome. Dwarf hybrids suitable for mechanical harvesting are already available on the market but the residual moisture of plants and capsules has to be lowered in order to allow mechanization. In the present case of study, three common terminating products (Glyphosate GLY, Diquat DIQ and Spotlight DEF) were tested on Kaiima C1012 hybrid in a complete randomized block design to assess the effectiveness of using chemical products to decrease residual moisture in castor plants. Plants were harvested via combine harvester equipped with cereal header to evaluate seed loss (due to dehiscence, impact and cleaning shoe) and the dehulling capacity of the combine harvester’s cleaning shoe. DIQ decreased significantly moisture content of capsules (7.32%) in comparison to the other treatments, while the lowest plant moisture was recorded in DIQ (62.38%) and GLY (59.12%). The use of DIQ triggered the highest impact seed loss (61.75%) in comparison with GLY (46.50%) and DEF (29.02%). Control plants could not be harvested mechanically due to the high residual moisture content and high density of weeds. The present case of study provides highlights regarding the need to further investigate the best practice to terminate castor plants and to develop a specific combine header to reduce seed loss from impact. © 2022 by the authors. Licensee MDPI, Basel, Switzerland

Monitoring Chemical-Induced Ripening of Castor (Ricinus communis L.) by UAS-Based Remote Sensing

Castor is a crop with an evergreen habit so artificially-induced ripening is an essential precondition for mechanical harvesting of new dwarf annual hybrids. Plants’ moisture imposes a determinant effect both on pre-harvest and post-harvest seed loss, so frequent monitoring of crop ripening is crucial for identifying the optimum moisture for harvest. Remote sensing information from Unmanned Aerial Systems (UASs) along with field measurements were utilized in the present study in order to evaluate three harvest aid chemicals, herbicides glyphosate (GLY) and diquat (DIQ) and the defoliant Spotlight® (DEF) for terminating the castor crop and identifying opportunities for using remote sensing as a tool for monitoring crop ripening. The results showed that glyphosate required more than two weeks to dry out the crop while diquat and spotlight® presented a rapid action within two to four days. Nineteen vegetation indexes (VIs) were derived from a multispectral and an RGB camera mounted on two UAS and were plotted against field measurements. NDVI presented a higher accuracy (R2 = 0.67) for predicting the castor stems’ and leaves’ moisture content while OSAVI and SIPI2 were more powerful in predicting moisture of capsules (R2 > 0.76). High efficiency was also obtained with VARIgreen, an index estimated from the common bands of a conventional RGB camera. The best performing VIs were further utilized in multiple linear regression models also incorporating the date of spraying as information. The VI models further improved the predicting power with an R2 of up to 0.73 for stems and leaves and 0.81 for capsules. © 2022 by the authors. Licensee MDPI, Basel, Switzerland

Protective Effects of Systiva® Seed Treatment Fungicide for the Control of Winter Wheat Foliar Diseases Caused at Early Stages Due to Climate Change

Foliar fungal diseases are a serious threat to winter wheat production and climate change appears to favor pathogens associated with leaf blotch and tan spot symptoms in the Mediterranean area. The present work aimed to highlight these risks and propose appropriate disease management strategies by evaluating the seed treatment with the Systiva® (BASF) fungicide as a means to protect the crop against foliar fungal infections during the early growing stages. Towards that aim, plant tissue symptoms affected by the pathogens Pyrenophora tritici-repentis and Septoria spp. were systematically recorded in a study field in the region of Larissa, central Greece for three years (2016–2018), and the findings were associated with the monthly weather anomalies. Consequently, for the growing period of 2021–2022, a field experiment was established in the same disease prone field, comparing different doses of the seed treatment with Systiva® fungicide against leaf blotch and tan spot diseases. The evaluation was made by visual disease assessments, remote sensing with an unmanned aerial vehicle (UAV) and metagenomics analysis. Parallel measurements on straw residues were also made to characterize the plant residues perithecia (pseudothecia). Visual leaf disease assessments and UAV remote sensing data showed that Systiva® treatments at doses of 125 cc and 150 cc per 100 kg of wheat seed can reduce the percentage of infected wheat plants caused by foliar fungal pathogens at wheat growth stages GS23-25 and GS30-31. Moreover, the metagenomics analyses performed on the microbial communities revealed that Systiva® can decrease the degree of infection by P. tritici-repentis and Z. tritici but do not provide sufficient protection against P. nodorum. Foliar diseases were influenced by the soil surface area covered with straw residue with a high proportion of natural inoculum (pseudothecia/ascospores). © 2022 by the authors

Soil parameters assessment by remote sensing

In this paper, remote sensing measurements like apparent electrical conductivity (ECa.) are used to assess soil compaction. In an experiment comparing five tillage treatments and their effect to energy crops soil penetration resistance (SPR) was measured at the same time as ECa. ECa measurements were carried out using EM-38with dipoles at 1m apart and SPR by an electronic penetrometer. The negative correlation between the two parameters for all measurements resulted in R2= 0.73. Taking the measurements for each treatment in conventional tillage plots R2 = 0.53, chisel plough tillage 0.61, rotary tiller 0.69, disk harrow 0.55, strip-till 0.35 and no till 0.81. Copyright © 2015 for the individual papers by the papers' authors