1. Increased planting speed did not affect silage and grain yield of maize, while saving seed and energyFilip Vučajnk, Igor Šantavec, Darja Kocjan Ačko, Jurij Rakun, Jože Verbič, Rajko Bernik, Stanislav Trdan, Matej Vidrih, 2020, original scientific article Abstract: Optimal planting speed of vacuum maize planters is usually suggested by planter’s manufacturers, while increased planting speed may influence plant spacing and finally yield. Our hypothesis was that by increasing planting speed over the suggested level plant spacing variability will also increase which will result in decrease of silage and grain yield and saving of seed and energy. The field trial consisted of three planting speeds of 7, 9 and 11 km/h in the form of random blocks. The following measurements were taken as follows: plant spacing, silage and grain yield, fuel and energy use at planting. Results in this study show that planting speed did not have significant influence on silage and grain yield of maize, while up to 10% less seed was needed per hectare and fuel and energy use was lower for 15%. By the increase of planting speed the distance between the plants in a row, and in most cases also the plant spacing variability increased. It was noticed that by increasing planting speed plant density decreased. This research established that at higher planting speeds significant increase of the silage yield per individual plant and of the grain yield per individual plant was achieved. The ear parameters also show that the kernel mass per individual ear, the ear mass, and the cob mass, as well as the individual kernel mass, are larger at the planting speed of 11 km/h than at the planting speed of 7 km/h. At the latter planting speed, significantly higher fuel consumption per hectare and higher energy use was achieved than at the other two planting speeds. Overall the main benefits of planting speed of 11 km/h is saving seed and energy at planting while maintaning the same level of silage and grain yield compared to lower planting speeds used in the trial.
Keywords: energy use, grain yield, maize, planting speed, plant spacing, seed savings, silage yield, vacuum planter
Published in DKUM: 11.03.2025; Views: 0; Downloads: 4
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2. OSNOVE PRECIZNEGA KMETIJSTVA : SkriptaPeter Vindiš, Miran Lakota, Jurij Rakun, 2025, other educational material Abstract: Skripta je namenjena vsem študentom Fakultete za kmetijstvo in biosistemske vede, ki jih omenjena tematika zanima, predvsem pa študentom študijskih smeri Biosistemsko inženirstvo VS ter drugi stopnji magistrskega študijskega programa Kmetijstvo. Omenjeno gradivo je sestavljeno iz vsebin, ki se navezujejo na predmete Osnove preciznega kmetijstva, Geografski informacijski sistemi v kmetijstvu ter Elektronika in avtomatizacija 1. Študentje naj uporabljajo skripto pri učenju in utrjevanju snovi. Skripta na didaktičen način obravnava tematiko v celoti, tako da lahko študent gradivo tudi sam predela in ga razume.
Skripta vsebuje vsebine iz zbranih poglavij uporabe precizne tehnologije v kmetijstvu, traktorskih komponent, potrebnih za pravilno delovanje GPS-sistema, uporabe satelitov in analize slike za namen preciznega kmetijstva, predstavitev spletno-mobilnih orodij za namen uporabe v preciznem kmetijstvu, variabilnega gnojenja kmetijskih površin in uporabe digitalnih kart ter pomena variabilne setve kmetijskih kultur.
Keywords: Precizno kmetijstvo, digitalizacija v kmetijstvu, mobilne aplikacije, precizno gnojenje, precizna setev kmetijskih kultur.
Published in DKUM: 25.02.2025; Views: 0; Downloads: 18
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3. Optimizacija algoritma za avtonomno navigacijo mobilnega robota : magistrsko deloGregor Popič, 2024, master's thesis Abstract: Magistrsko delo opisuje delovanje algoritma avtonomne navigacije robota FarmBeast, ki je namenjen avtomatizaciji različnih kmetijskih opravil, sekundarno pa tudi za tekmovanje Field Robot Event v sklopu panoge osnovne in napredne navigacije. Za delovanje so uporabljeni napredni senzorji, kot sta LiDAR in IMU, pri čemer se podatki filtrirajo in transformirajo z namenom natančnejše zaznave podatkov o okolici robota. Ob tem je za potrebe obračanja implementirana uporaba kvaternionov, kar pripomore k večji natančnosti in robustnosti delovanja. Testiranja, na podlagi primerjave s predhodno verzijo algoritma, so pokazala znatno izboljšanje hitrosti in večjo natančnost vožnje ter izrazito zmanjšanje poškodovanih rastlin. Meritve potrjujejo, da je novo razviti algoritem bolj učinkovit in bolj zanesljiv v primerjavi s predhodno verzijo.
Keywords: FarmBeast robot, avtonomna navigacija, kmetijska avtomatizacija, optimizacija algoritma
Published in DKUM: 03.10.2024; Views: 0; Downloads: 40
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4. Možnost nadgradnje adaptivnega sistema za nanosa fitofarmacevtskih sredstev v sadovnjakih jablan s pomočjo kamere Intel RealSense D435if : diplomsko deloNuša Urnaut, 2024, undergraduate thesis Abstract: Fitofarmacevtska sredstva (v nadaljevanju FFS) so pripravki, ki se uporabljajo v kmetijstvu z namenom varstva rastlin in pridelkov pred škodljivci, pozročitelji bolezni in plevelom. Uporaba FFS in njihovi potencialni negativni učinki na okolje so dandanes zelo odmevni, vendar si zadostne pridelave kmetijskih rastlin ne moremo predstavljati brez njihove uporabe, zato je potrebno več pozornosti nameniti obvladovanju oziroma nadziranju njihove rabe. V sadovnjaku jablan smo izvedli poskus s pomočjo kamere Intel Realsense, ki je osnova nadgradnje osnovnega adaptivnega sistema za nanos FFS, ki deluje na principu elektromagnetnih ventilov na pršilniku. Sistem je bil zasnovan in preizkušen v projektu TRANSFARM 4.0 na Katedri za biosistemsko inženirstvo na Fakulteti za kmetijstvo in biosistemske vede. Cilj diplomske naloge je proučiti možnost nadgradnje tega sistema z uporabo kamere Intel Realsense D435if, s katero bomo lahko izračunali približek prihranka FFS v sadovnjaku v primerjavi z osnovnim adaptivnim sistemom. Ugotoviti želimo, ali se uporaba te kamere obrestuje, saj je cenovno 5-krat ugodnejša od sistema LiDAR, ki se uporablja pri osnovnem adaptivnem sistemu. Poskus je bil opravljen
na delu sadovnjaka, ki je segal 20 m v dolžino in 3 m v širino. Opravljenih je bilo 19 posnetkov krošenj, kjer je bila razdalja med kamero in krošnjami 2 m. Glavna ugotovitev je nakazala potencialni prihranek fitofarmacevtskih sredstev v obsegu 10 odstotkov. Uporaba kamere se je torej izkazala kot učinkovita in predstavlja pomemben korak v razvoju natančnejšega nanosa FFS, kar prinaša kmetom prihranek tako pri uporabi FFS kot pri nakupu tehnologije.
Keywords: sadovnjak, kamera, fitofarmacevtska sredstva, adaptivni sistem
Published in DKUM: 11.09.2024; Views: 40; Downloads: 19
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5. Uporaba sistemov za upravljanje vsebin (CMS) v raziskavi kmetijskih gospodarstev v Sloveniji : diplomsko deloKaja Žučko, 2024, undergraduate thesis Abstract: Diplomsko delo temelji na uporabi sistema Wordpress, ki je sistem za upravljanje vsebin (CMS). Glavni cilj diplomskega dela je izdelati spletno platformo, kjer bodo predstavljena kmetijska gospodarstva v Sloveniji znotraj interaktivnega zemljevida z namenom promoviranja in podpiranja slovenskih kmetijskih gospodarstev ter s tem omogočiti promoviranje in prodajo njihovih pridelkov in izdelkov širši javnosti. Pridobljene podatke o kmetijskih gospodarstvih, predstavljene s sistemom Wordpress, smo pridobili z opravljeno raziskavo znotraj našega diplomskega dela. Raziskava je strukturirana v dva ključna dela. Prvi del vključuje anketiranje udeležencev glede na njihovo kmetijsko prakso, osredotoča se na primarno kmetijsko dejavnost, način kmetovanja ter vrste pridelkov in izdelkov. V drugem delu raziskave se posvečamo vprašanjem o poznavanju in potencialnih možnostih uporabe informacijsko–komunikacijskih tehnologij (IKT).
Pridobljene rezultate smo predstavili s sistemom CMS (Wordpress), kjer smo ne le analizirali rezultate, temveč tudi ustvarili geografsko predstavitev anketiranih kmetijskih gospodarstev v obliki interaktivnega zemljevida. Ta zemljevid obsega kratek opis vsakega gospodarstva, ki dopolnjuje podatke, predstavljene v analizi rezultatov.
S takšnim pristopom k diplomskemu delu bomo omogočili celovit vpogled v kmetijska gospodarstva, njihove prakse in možnosti za implementacijo informacijsko-komunikacijskih tehnologij. Hkrati bo uporaba sistema CMS pripomogla k jasni in pregledni predstavitvi pridobljenih podatkov ter geografskih informacij, kar bo olajšalo razumevanje in interpretacijo rezultatov raziskave.
Keywords: sistemi za upravljanje vsebin (CMS), Wordpress, informacijsko
komunikacijske tehnologije (IKT), kmetijska gospodarstva
Published in DKUM: 04.09.2024; Views: 45; Downloads: 24
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6. Growth and glucosinolate profiles of Eruca sativa (Mill.) (rocket salad) and Diplotaxis tenuifolia (L.) DC. under different LED lighting regimesDenis Stajnko, Peter Berk, Andrej Orgulan, Marko Gomboc, Damijan Kelc, Jurij Rakun, 2022, original scientific article Abstract: In this study, the growth and glucosinolate (GSL) profiles of rocket salad Eruca sativa (Mill.) and Diplotaxis tenuifolia (L.) DC. were determined during 30 days growing under different lighting regimes; T5_ peak at 545 nm, LED1_ peak at 631 nm and LED2_ peak at 598 nm. The biggest increase of dry weight (DW) was measured in E. sativa under T5 (0.657 g DW/plant) and the lowest in D. tenuifolia under LED1 (0.080 g DW/plant). GSL content was found to vary significantly, regardless of the light treatment, but it is related with genotype (E. sativa, r = 0.802**). On average, the highest amount of 4-methylsulfinylbutyl-GSL (glucosativin) (7.3248 mg/g DW) was quantified in E. sativa and D. tenuifolia (6.7428 mg/g DW) under the T5. The regression analysis between different light wavelengths and glucosinolates showed the strongest correlation between photosynthetic photon flux density (PPFD_B) and 4-methylthiobutyl-GSL (glucoerucin) in E. sativa (r = 0.698*) and D. tenuifolia (r = 0.693*), respectively, which indicates the effect of light on the response of plants to induced stress and changes in GSL biosynthesis.
Keywords: salad vegetables, antioxidant compounds, light, abiotic stress, phytohormone
Published in DKUM: 11.07.2024; Views: 124; Downloads: 20
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7. Possibilities and concerns of implementing precision agriculture technologies on small farms in SloveniaJurij Rakun, Erik Rihter, Damijan Kelc, Denis Stajnko, Peter Vindiš, Peter Berk, Peter Polič, Miran Lakota, 2022, original scientific article Abstract: Precision agriculture (PA) through the use and utilization of innovative technologies is a concept in agricultural management that enables long-term efficiency gains, control of unforeseen changes, and a reduction of negative impacts on the environment. However, there are even more reasons and benefits to using precision agriculture technologies (PATs) on farms, but the actual use on small farms is often questionable. The main objective of this research was to evaluate and analyze the current state of PA and its potential on a set of small farms. In addition, a comparison was made between small farms located in less favored areas (LFAs) and more favored areas (MFAs) to find if specific characteristics of the surrounding environment affect the (non-) implementation of these technologies by farm owners, with respect to the given regional possibilities. The result shows that 57.5% of respondents on these farms have never implemented PATs before and 20% are beginners in their respective fields. It was found that there were no statistically significant differences in the integration between fewer LFAs and MFAs technologies and their use in this study. The majority of respondents believe that the main changes need to occur on the level of politics. The results show that the level of cost or initial investment is the main reason and the main obstacle in the implementation of PATs on the surveyed farms.
Keywords: precision agriculture, small farm, technological innovations, implementation, situation overview, survey, ICT
Published in DKUM: 02.07.2024; Views: 161; Downloads: 21
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8. Sensor fusion-based approach for the field robot localization on Rovitis 4.0 vineyard robotJurij Rakun, Matteo Pantano, Peter Lepej, Miran Lakota, 2022, original scientific article Abstract: This study proposed an approach for robot localization using data from multiple low-cost sensors with two goals in mind, to produce accurate localization data and to keep the computation as simple as possible. The approach used data from wheel odometry, inertial-motion data from the Inertial Motion Unit (IMU), and a location fix from a Real-Time Kinematics Global Positioning System (RTK GPS). Each of the sensors is prone to errors in some situations, resulting in inaccurate localization. The odometry is affected by errors caused by slipping when turning the robot or putting it on slippery ground. The IMU produces drifts due to vibrations, and RTK GPS does not return to an accurate fix in (semi-) occluded areas. None of these sensors is accurate enough to produce a precise reading for a sound localization of the robot in an outdoor environment. To solve this challenge, sensor fusion was implemented on the robot to prevent possible localization errors. It worked by selecting the most accurate readings in a given moment to produce a precise pose estimation. To evaluate the approach, two different tests were performed, one with robot localization from the robot operating system (ROS) repository and the other with the presented Field Robot Localization. The first did not perform well, while the second did and was evaluated by comparing the location and orientation estimate with ground truth, captured by a hovering drone above the testing ground, which revealed an average error of 0.005 m±0.220 m in estimating the position, and 0.6°±3.5° when estimating orientation. The tests proved that the developed field robot localization is accurate and robust enough to be used on a ROVITIS 4.0 vineyard robot.
Keywords: localization, odometry, IMU, RTK GPS, vineyard, robot, sensors fusion, ROS, precision farming
Published in DKUM: 02.07.2024; Views: 123; Downloads: 17
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9. Snovanje modularnega avtonomnega kmetijskega robota : magistrsko deloMiha Kajbič, 2023, master's thesis Abstract: Hiter razvoj tehnologije in avtomatizacija procesov v kmetijstvu vplivata na vse pogostejšo uporabo različnih senzorskih in mehatronskih sistemov. V tako imenovanem preciznem kmetovanju nepogrešljivo vlogo igrajo različne mobilne robotske platforme. Slednje so v večini primerov zasnovane za opravljane točno določenih nalog tekom pridelave pridelkov in jih ne moremo uporabljati za različna opravila. Magistrsko delo prikazuje snovanje in izdelavo modularnega avtonomnega kmetijskega robota. Modularna zasnova omogoča enostavno prilagajanje robota množici različnih aplikacij v kmetijstvu. Predstavljen kmetijski robot sestoji iz šestih glavnih sestavnih modulov. V zaključnem delu bodo predstavljeni preračuni elementov, ki so potrebni za ustrezno delovanje robotskega sistema.
Keywords: precizno kmetovanje, robotska platforma, modularna zasnova
Published in DKUM: 05.10.2023; Views: 393; Downloads: 75
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10. Zaznava in lociranje malin z uporabo YOLO algoritma : magistrsko deloUrban Kenda, 2023, master's thesis Abstract: V magistrskem delu smo raziskali delovanje LiDAR senzorjev ter uporabo umetne inteligence v strojnem vidu, vključno z nevronskimi mrežami, konvolucijskimi nevronskimi mrežami (CNN) in algoritmi YOLOv3, v4 in v4-tiny. V praktičnem delu smo testirali vse tri algoritme in nato izbrali najuspešnejšega, YOLOv4, ter ga dodatno analizirali. Preverili smo hitrost algoritmov ter razvili algoritem, ki je na podlagi oblakov točk in kamere sposoben določiti lokacijo malin. Ugotovili smo, da je uporaba LiDAR senzorjev v kombinaciji z umetno inteligenco učinkovita pri zaznavanju in lociranju malin v 3D-prostoru. Najuspešnejši algoritem YOLOv4 je bil sposoben razvrstiti zrele in nezrele maline z natančnostjo 84,13 %. Naš razviti algoritem je omogočil določanje lokacije malin s kombinirano uporabo oblakov točk in kamere ter tako skoraj v polovici izmerjenih primerov določil lokacijo z napako, manjšo od 2 cm.
Keywords: malina, strojni vid, YOLO, nevronska mreža, CNN, oblak točk
Published in DKUM: 15.06.2023; Views: 512; Downloads: 114
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