TY  - JOUR
AU  - Visković, Jelena
AU  - Zheljazkov, Valtcho D.
AU  - Sikora, Vladimir
AU  - Noller, Jay
AU  - Latković, Dragana
AU  - Ocamb, Cynthia M.
AU  - Koren, Anamarija
PY  - 2023
UR  - http://fiver.ifvcns.rs/handle/123456789/3433
AB  - Currently, there are increased interests in growing grain and fiber hemp (Cannabis sativa L.) as well as in large-scale hemp products. Cannabis has been grown/utilized for thousands of years as a fiber, grain, and drug/medicinal plant. However, the strict control of cannabis cultivation to combat illegal use, the spread of new yarns and oilseeds, and the advent of cheap synthetic fibers caused a decreased/eliminated hemp production. Hemp has been banned in most of the world for more than seven decades; it missed out on the Green Revolution and the adoption of new technologies and varieties, creating a knowledge gap. After the 2014 and 2018 Farm Bill in the USA, hemp became legal and the land grand universities launched research programs. The ability to utilize the entire plant for multiple purposes creates opportunity for the market to value hemp products. Hemp production technology varies depending on the type of hemp cultivated (grain, fiber, or cannabinoids), soil characteristics, and environmental factors. Hemp has the potential to be a very sustainable and ecologically benign crop. Hemp roots have a significant potential for absorbing and storing heavy metals such as lead, nickel, cadmium, and other harmful substances. In addition, hemp has been proven to be an excellent carbon trap and biofuel crop. Hemp has the ability to successfully suppress weeds, and it is generally regarded a pesticide-free crop. The purpose of this paper is to examine historic and recent industrial hemp (grain and fiber) literature, with a focus on hemp agronomy and utilization.
PB  - Basel : MDPI
T2  - Agronomy - Basel
T1  - Industrial Hemp (Cannabis sativa L.) Agronomy and Utilization: A Review
IS  - 3
SP  - 931
VL  - 13
DO  - 10.3390/agronomy13030931
ER  - 

@article{
author = "Visković, Jelena and Zheljazkov, Valtcho D. and Sikora, Vladimir and Noller, Jay and Latković, Dragana and Ocamb, Cynthia M. and Koren, Anamarija",
year = "2023",
abstract = "Currently, there are increased interests in growing grain and fiber hemp (Cannabis sativa L.) as well as in large-scale hemp products. Cannabis has been grown/utilized for thousands of years as a fiber, grain, and drug/medicinal plant. However, the strict control of cannabis cultivation to combat illegal use, the spread of new yarns and oilseeds, and the advent of cheap synthetic fibers caused a decreased/eliminated hemp production. Hemp has been banned in most of the world for more than seven decades; it missed out on the Green Revolution and the adoption of new technologies and varieties, creating a knowledge gap. After the 2014 and 2018 Farm Bill in the USA, hemp became legal and the land grand universities launched research programs. The ability to utilize the entire plant for multiple purposes creates opportunity for the market to value hemp products. Hemp production technology varies depending on the type of hemp cultivated (grain, fiber, or cannabinoids), soil characteristics, and environmental factors. Hemp has the potential to be a very sustainable and ecologically benign crop. Hemp roots have a significant potential for absorbing and storing heavy metals such as lead, nickel, cadmium, and other harmful substances. In addition, hemp has been proven to be an excellent carbon trap and biofuel crop. Hemp has the ability to successfully suppress weeds, and it is generally regarded a pesticide-free crop. The purpose of this paper is to examine historic and recent industrial hemp (grain and fiber) literature, with a focus on hemp agronomy and utilization.",
publisher = "Basel : MDPI",
journal = "Agronomy - Basel",
title = "Industrial Hemp (Cannabis sativa L.) Agronomy and Utilization: A Review",
number = "3",
pages = "931",
volume = "13",
doi = "10.3390/agronomy13030931"
}

Visković, J., Zheljazkov, V. D., Sikora, V., Noller, J., Latković, D., Ocamb, C. M.,& Koren, A.. (2023). Industrial Hemp (Cannabis sativa L.) Agronomy and Utilization: A Review. in Agronomy - Basel
Basel : MDPI., 13(3), 931.
https://doi.org/10.3390/agronomy13030931

Visković J, Zheljazkov VD, Sikora V, Noller J, Latković D, Ocamb CM, Koren A. Industrial Hemp (Cannabis sativa L.) Agronomy and Utilization: A Review. in Agronomy - Basel. 2023;13(3):931.
doi:10.3390/agronomy13030931 .

Visković, Jelena, Zheljazkov, Valtcho D., Sikora, Vladimir, Noller, Jay, Latković, Dragana, Ocamb, Cynthia M., Koren, Anamarija, "Industrial Hemp (Cannabis sativa L.) Agronomy and Utilization: A Review" in Agronomy - Basel, 13, no. 3 (2023):931,
https://doi.org/10.3390/agronomy13030931 . .

TY  - JOUR
AU  - Dunđerski, Dušan
AU  - Jaćimović, Goran
AU  - Crnobarac, Jovan
AU  - Visković, Jelena
AU  - Latković, Dragana
PY  - 2023
UR  - http://fiver.ifvcns.rs/handle/123456789/3572
AB  - In this study, we aimed to evaluate the feasibility of digital image analysis (DIA) as a substitute for standard analysis (SA) in assessing corn ear traits in agrotechnical field trials. Accurate and timely prediction of corn yield through corn ear traits can lead to precise agricultural management recommendations for the improvement of production. Four replications with 10 plots each were subjected to different fertilization regimes and analyzed using DIA and SA to determine the kernel number per ear (KN), ear length (EL), and ear diameter (ED). For both methods, the results showed that only nitrogen doses had a significant effect on the examined corn ear traits, and the correlation matrix revealed a strong and significant relationship between yield and corn ear traits. The post-hoc test showed no discrepancy in cases between the two methods for KN and EL, with a 6.7% discrepancy for ED. For both methods, a linear plateau was the best fit for KN and EL with increasing nitrogen doses, whereas a quadratic plateau was the best fit for ED. The regression equations for both methods provided similar recommendations regarding nitrogen requirements. The findings suggest that DIA can be used as a substitute for SA of corn ear traits obtained from different fertilization variants and can provide nitrogen fertilization recommendations for optimal corn yields.
PB  - Basel : MDPI
T2  - Agriculture
T1  - Using Digital Image Analysis to Estimate Corn Ear Traits in Agrotechnical Field Trials: The Case with Harvest Residues and Fertilization Regimes
IS  - 3
SP  - 732
VL  - 13
DO  - 10.3390/agriculture13030732
ER  - 

@article{
author = "Dunđerski, Dušan and Jaćimović, Goran and Crnobarac, Jovan and Visković, Jelena and Latković, Dragana",
year = "2023",
abstract = "In this study, we aimed to evaluate the feasibility of digital image analysis (DIA) as a substitute for standard analysis (SA) in assessing corn ear traits in agrotechnical field trials. Accurate and timely prediction of corn yield through corn ear traits can lead to precise agricultural management recommendations for the improvement of production. Four replications with 10 plots each were subjected to different fertilization regimes and analyzed using DIA and SA to determine the kernel number per ear (KN), ear length (EL), and ear diameter (ED). For both methods, the results showed that only nitrogen doses had a significant effect on the examined corn ear traits, and the correlation matrix revealed a strong and significant relationship between yield and corn ear traits. The post-hoc test showed no discrepancy in cases between the two methods for KN and EL, with a 6.7% discrepancy for ED. For both methods, a linear plateau was the best fit for KN and EL with increasing nitrogen doses, whereas a quadratic plateau was the best fit for ED. The regression equations for both methods provided similar recommendations regarding nitrogen requirements. The findings suggest that DIA can be used as a substitute for SA of corn ear traits obtained from different fertilization variants and can provide nitrogen fertilization recommendations for optimal corn yields.",
publisher = "Basel : MDPI",
journal = "Agriculture",
title = "Using Digital Image Analysis to Estimate Corn Ear Traits in Agrotechnical Field Trials: The Case with Harvest Residues and Fertilization Regimes",
number = "3",
pages = "732",
volume = "13",
doi = "10.3390/agriculture13030732"
}

Dunđerski, D., Jaćimović, G., Crnobarac, J., Visković, J.,& Latković, D.. (2023). Using Digital Image Analysis to Estimate Corn Ear Traits in Agrotechnical Field Trials: The Case with Harvest Residues and Fertilization Regimes. in Agriculture
Basel : MDPI., 13(3), 732.
https://doi.org/10.3390/agriculture13030732

Dunđerski D, Jaćimović G, Crnobarac J, Visković J, Latković D. Using Digital Image Analysis to Estimate Corn Ear Traits in Agrotechnical Field Trials: The Case with Harvest Residues and Fertilization Regimes. in Agriculture. 2023;13(3):732.
doi:10.3390/agriculture13030732 .

Dunđerski, Dušan, Jaćimović, Goran, Crnobarac, Jovan, Visković, Jelena, Latković, Dragana, "Using Digital Image Analysis to Estimate Corn Ear Traits in Agrotechnical Field Trials: The Case with Harvest Residues and Fertilization Regimes" in Agriculture, 13, no. 3 (2023):732,
https://doi.org/10.3390/agriculture13030732 . .