To see the other types of publications on this topic, follow the link: Precision agriculture 4.0.
Journal articles on the topic 'Precision agriculture 4.0'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 journal articles for your research on the topic 'Precision agriculture 4.0.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
1
Ni'mawati, Sakinah, Bariyyah Khoirul, Hadi Ahmad, et al. "Humic Acid for Soil Quality Improvement with Application of Scan Automation on Seedless Watermelon Cultivation." INTERNATIONAL JOURNAL OF LIFE SCIENCE AND AGRICULTURE RESEARCH 02, no. 10 (2023): 341–49. https://doi.org/10.55677/ijlsar/V02I10Y2023-01.
Full textAbstract:
ABSTRACT <strong>Purpose: </strong>Sustainable agricultural intensification needs to be well developed. Therefore, food and agricultural production activities can be continuously produced without damaging the ecosystems and environment. One that can be used is a plant biostimulant based on humus. This research was conducted to examine the effect of humic acid as a soil biostimulant and the impact of its use on the yield of seedless watermelon cultivated on marginal land. This study involve IoT technology through monitoring soil quality which is carried out based on the concept of precision agriculture using the farm management system (FMS) Agrooscan tool. <strong>Methods:</strong> The study used humic acid factor for five treatments (0, 2, 4, 6, and 8 g/L). Observations included soil conditions monitored with Agrooscan instruments such as soil pH, nutrients (N, P, K), as well as measuring plant height, fruit weight, fruit volume and total sugar content (Brix).
2
Restrepo-Arias, Juan Felipe, María José Montoya-Castaño, María Fernanda Moreno-De La Espriella, and John W. Branch-Bedoya. "An Application of Deep Learning Models for the Detection of Cocoa Pods at Different Ripening Stages: An Approach with Faster R-CNN and Mask R-CNN." Computation 13, no. 7 (2025): 159. https://doi.org/10.3390/computation13070159.
Full textAbstract:
The accurate classification of cocoa pod ripeness is critical for optimizing harvest timing, improving post-harvest processing, and ensuring consistent quality in chocolate production. Traditional ripeness assessment methods are often subjective, labor-intensive, or destructive, highlighting the need for automated, non-invasive solutions. This study evaluates the performance of R-CNN-based deep learning models—Faster R-CNN and Mask R-CNN—for the detection and segmentation of cocoa pods across four ripening stages (0–2 months, 2–4 months, 4–6 months, and >6 months) using the RipSetCocoaCNCH12 dataset, which is publicly accessible, comprising 4116 labeled images collected under real-world field conditions, in the context of precision agriculture. Initial experiments using pretrained weights and standard configurations on a custom COCO-format dataset yielded promising baseline results. Faster R-CNN achieved a mean average precision (mAP) of 64.15%, while Mask R-CNN reached 60.81%, with the highest per-class precision in mature pods (C4) but weaker detection in early stages (C1). To improve model robustness, the dataset was subsequently augmented and balanced, followed by targeted hyperparameter optimization for both architectures. The refined models were then benchmarked against state-of-the-art YOLOv8 networks (YOLOv8x and YOLOv8l-seg). Results showed that YOLOv8x achieved the highest mAP of 86.36%, outperforming YOLOv8l-seg (83.85%), Mask R-CNN (73.20%), and Faster R-CNN (67.75%) in overall detection accuracy. However, the R-CNN models offered valuable instance-level segmentation insights, particularly in complex backgrounds. Furthermore, a qualitative evaluation using confidence heatmaps and error analysis revealed that R-CNN architectures occasionally missed small or partially occluded pods. These findings highlight the complementary strengths of region-based and real-time detectors in precision agriculture and emphasize the need for class-specific enhancements and interpretability tools in real-world deployments.
3
Atchala, N’GBENDEMA, SOGBEDJI Mianikpo Jean, and MAZINAGOU Mihikouwe. "Physico-Chemical Characterization of Soils for the Promotion of Precision Agriculture in Irrigated Rice Cultivation in the Zio Valley in Togo." East African Scholars Journal of Agriculture and Life Sciences 5, no. 8 (2022): 151–56. http://dx.doi.org/10.36349/easjals.2022.v05i08.001.
Full textAbstract:
To sustainably improve rice production in the Zio valley, this study characterized the soils of the developed area. More specifically, the study: (i) determined the Physico-chemical properties of soils and (ii) analyzed the impact of rice cultivation on these chemical parameters. Thirty-six (36) fields of producers were selected and distributed in the 4 villages of the irrigated perimeter: 10 in Kovié, 9 in Mission Tové; 9 in Ziwonou, and 8 in Assomé. The samples were manually collected at a depth of 0-30 cm and analyzed at the soil laboratory of the Togolese Institute of Agronomic Research (ITRA). Physically, the soils are sandy-loamy in Kovié (100%), sandy-loamy in Mission Tové (56%), clayey in Assomé (57%), and Ziovonou (78%). Chemically, the soils are acidic with an average pH of 5.57. They present low (0.89%) and moderate (1.3%) limitation levels respectively for nitrogen and organic matter, very severe for assimilable phosphate (2.3±0.16 ppm), and cation exchange capacity (4.64±0.26 meq/100g of soil) and severe for exchangeable potassium (0.14±0.01 meq/100g of soil). The study also showed a significant decrease in the quantities of Nitrogen, Carbon, Potassium exchangeable, and cation exchange capacity respectively of 57%, 72%, 56%, and 85% compared to 1964. The adoption of cultural practices having a less negative impact on the chemical characteristics of the soil combined with an update of the adapted fertilization formulas become imperatives to ensure sustainable exploitation of the perimeter.
4
Silva, Jucicléia Soares da, Abelardo Antônio de Assunção Montenegro, Ênio Farias de França e. Silva, Carolyne Wanessa Lins de Andrade, and José Roberto Lopes da Silva. "Distribuição Espacial da Condutividade Elétrica e Matéria Orgânica em um Solo Neossolo Flúvico (Spatial Distribution of Electrical Conductivity and Organic Matter in a Soil Fluvic Neosol)." Revista Brasileira de Geografia Física 6, no. 4 (2013): 764. http://dx.doi.org/10.26848/rbgf.v6i4.233067.
Full textAbstract:
A agricultura de precisão permite, pelo uso de delimitação de lavouras por coordenadas georreferenciadas, um planejamento mais racional do manejo de nutrientes, incidência de pragas, umidade do solo, plantas daninhas, além de seleção de cultivares em função de sua adaptabilidade às diferentes condições identificadas nas áreas cultivadas. Com isso, o objetivo do presente trabalho foi avaliar a distribuição espacial da condutividade elétrica do extrato de saturação, carbono orgânico total e matéria orgânica em um solo Neossolo Flúvico. O experimento foi conduzido em uma área com malha regular 4 x 4 m, totalizando com 49 pontos, onde foram coletadas amostras nas camadas de 0- 0,20 m para analisar a condutividade elétrica do extrato de saturação, carbono orgânico total e matéria orgânica. As variáveis foram analisadas por meio da estatística descritiva e de ferramentas de geoestatística. As variáveis apresentaram distribuição normal, os semivariogramas se ajustaram a um modelo esférico, a variabilidade do carbono orgânico total e matéria orgânica apresentaram moderadas, a condutividade elétrica do extrato de saturação apresentou fraca dependência espacial. Os mapas de isolinhas apresentaram homogeneidade e similaridade, os mapas condutividade elétrica do extrato de 0-0,20 m foram inversamente proporcionais aos da matéria orgânica e do carbono orgânico.
 
 
 A B S T R A C T
 Precision agriculture allows, by the use of delimitation of crops for georeferenced coordinates, more rational planning of the management of nutrients, pests, soil moisture, weeds, and cultivar selection due to its adaptability to different conditions in the areas identified cultured. With it, the objective of this study was to evaluate the spatial distribution of the electrical conductivity of the saturation extract, total organic carbon and organic matter in soil Fluvic Neosol. The experiment was conducted in an area with regular mesh 4 x 4 m, with a total of 49 points, samples were collected in layers from 0 to 0.20 m to analyze the electrical conductivity of the saturation extract, total organic carbon and organic matter. The variables were analyzed using descriptive statistics and geostatistical tools. The variables were normally distributed, the semivariogram adjusted to a spherical model, the variability of total organic caborn and organic matter showed a moderate electrical conductivity of the saturation extract showed weak spatial dependence. The contour maps showed homogeneity and similarity maps the electrical conductivity of the extract of 0-0.20 m was inversely proportional to the organic matter and organic carbon.
 
 Key-Words: Geostatistics, salinity, total organic carbon, organic matter
5
Oseghale, Agatha Itohan, Job Nda Nmadu, Ramatu Usman Bako, et al. "Sustainable Food Supply: The Interplay between Population Growth and Land Productivity Changes as a Pathway to 2030 and Beyond for Nigeria." Asian Research Journal of Agriculture 17, no. 2 (2024): 414–23. http://dx.doi.org/10.9734/arja/2024/v17i2463.
Full textAbstract:
Context and Background: Sustainable food supply is a critical global challenge, particularly in developing countries like Nigeria, where rapid population growth and limited land resources create a complex interplay with far-reaching implications. Thus, there will be a need to increase food production to keep pace with the population increase. Goal and Objectives: This study seeks to analyse the interplay between population growth and land productivity changes in Nigeria as a pathway towards achieving sustainable food supply by 2030 and beyond, in line with Goal 2 of the 2030 Sustainable Development Goals (SDGs) which is aimed at “ending hunger, achieving food security, improving nutrition, and promoting sustainable agriculture. Methodology: Data on land productivity and Nigeria's population and Population growth for 1961-2022 was sourced from the Economic Research Service of the United States Department of Agriculture (ERS-USDA, 2023). The data was analysed using descriptive statistics such as mean; standard errors and graphs; the Autoregressive Integrated Moving Average (ARIMA) was used to explain the interplay between population growth and land productivity changes in Nigeria. Results: The results of the population estimates revealed that the model successfully converged and significantly (p<0) explained 98.3% of the variance of the endogenous variable that is, the population at an intercept of -2500.7. Of the hypothesized variables, year (1.212), cropland (9.14E-4), irrigated (0.283), and pasture (0.003). These findings imply that the future population would increase in each period until the series becomes explosive because, the coefficient of the lagged variable of population is positive and greater than 1, which is in contrast with the assumptions of the ARIMA model which should be less than 1. Thus, the study recommends adopting precision agriculture techniques such as GPS mapping, soil analysis, crop health monitoring, and automated irrigation to maximize crop yields, reduce costs, and transform farming practices in Nigeria.
6
Orji, O. A., and T. Iruene. "Soil Moisture Characteristics of Humid Tropical Soils of the Southern Part of Rivers State Nigeria." Soil Moisture Characteristics of Humid Tropical Soils of the Southern Part of Rivers State Nigeria 8, no. 10 (2023): 9. https://doi.org/10.5281/zenodo.10110044.
Full textAbstract:
Soil moisture characteristics data are extremely valuable tools for describing and managing water storage and flow transport in soils, as well as informing climate-smart agricultural courses and practices. Saturated hydraulic conductivity (Ks), aggregate size distribution, mean weight diameter (MWD), soil moisture characteristic curve (SMCC) and other indices of soil structure were estimated for soils of the 8 Local Government Areas (Akuku-Toru, Degema, Gokhana, Khana, Ogu-Bolo, Okrika, Oyigbo and Tai) in the South of Rivers State Nigeria. Core samples were taken from across the 8 LGAs in triplicates at 0-5, 5-10, 10-15 and 15-20cm depths along with bulk samples at 0- 10cm and 10-20cm depths. The high spatial variability of these soils of the same terrain, were evidenced in the high coefficient of variation (CV) values in all parameters measured; with the exception of % of sand across all areas sampled. The soils were generally sandy loam to sand. Bulk density values ranged between 1.17 to 1.74gcm-3 at the 0-10cm depth, with a CV of 12.8% across locations. Ks values were generally moderate (2.5x10-3 to 9.9 x 10-4 cmsec-1 ) with a CV of 91.8 to 109.7% across locations and depth. Degema, Okrika and Tai soils had significantly higher aggregate stability as indicated by the MWD, with 43.5 to 46.1% of their aggregates being >3.5mm in diameter size; when compared with the other locations. SMCC showed that moisture content at the field capacity (50cm suction) varied significantly across both locations and depths, with CV values between 49.0 to 71.0%. At the 0.1bar suction, the volumetric moisture contents were in the order 0.030, 0.020, 0.020, 0.020, 0.012, 0.010, 0.010 and 0.002cm3 cm-3 for Gokhana, Degema, Oyigbo, Khana, Ogu-Bolo, Akuku-Toru, Tai and Okrika soils, respectively. Results obtained form a baseline data of the parameters measured, for management of water storage, climate smart and precision agriculture; in these parts of Rivers State.Keywords:- Soil Moisture Characteristics, Aggregate Stability, Saturated Hydraulic Conductivity, CV.
7
Babichev, Alexander N., and Dmitry P. Sidarenko. "Effects of precision irrigation on water regime and productivity of winter wheat." RUDN Journal of Agronomy and Animal Industries 18, no. 4 (2023): 554–65. http://dx.doi.org/10.22363/2312-797x-2023-18-4-554-565.
Full textAbstract:
The aim of the research was to establish the effect of precision irrigation with varying mineral fertilizer availability on winter wheat productivity. Studies were carried out on irrigated arable land in the Rostov region. The test scheme included 3 replications. The climate of the research area is arid but not hot enough. The sum of temperatures for growing period is in the range of 30003200 C, the average annual precipitation is 470 mm, for the growing period - 285 mm. The soil cover of the experimental site is chernozem. According to the granulometric composition of the soil, the entire profile is represented mainly by heavy loam, turning into medium loam at a depth of 130-160 cm. The structural state in dry sieving and the water resistance of the aggregates are characterized as excellent. The lowest water-holding capacity for 0-60-centimeter layer is 28.3 %, which is good according to the existing classification. Soil density in 0.6 m layer is 1.27 t/m3, and in 1.0 m layer - 1.33 t/m3. Differentiated doses of fertilizers against the background of irrigation technologies studied in variants had a significant impact on productivity of winter wheat. Thus, in the variants with no irrigation, water consumption coefficient of winter wheat was 890.8 to 1343.6 m3/t; using the recommended irrigation system reduced its value to 725.91327.3 m3/t, and the precision irrigation technology provided a reduction in the value of water consumption coefficient to 681.61147.6 m3/t. The conducted studies revealed advantage of precision irrigation technology and mineral fertilizers, the use of which in different years provided higher winter crop yield by an average of 0.55 t/ha in comparison with the recommended technology, and, in comparison with variants without irrigation - by 3.49 t/ha. The introduction of modern high-precision irrigation technologies will make agricultural products produced on irrigated land more competitive.
8
Dorner, Joe W., Paul D. Blankenship, and Richard J. Cole. "Performance of Two Immunochemical Assays in the Analysis of Peanuts for Aflatoxin at 37 Field Laboratories." Journal of AOAC INTERNATIONAL 76, no. 3 (1993): 637–43. http://dx.doi.org/10.1093/jaoac/76.3.637.
Full textAbstract:
Abstract A study was conducted to measure the precision of 2 rapid aflatoxin assay systems in use at 37 peanut buying points during the 1991 harvest season. Aflatoxin laboratories were established at the 37 buying points to analyze peanut samples from all incoming farmers’ stock loads as part of a joint project sponsored by various segments of the U.S. peanut industry and the U.S. Department of Agriculture. Eighteen laboratories were equipped with Neogen’s veratox FSP rapid assay system, whereas 19 laboratories used Vicam’s Aflatest rapid assay system. To monitor the performance of the field laboratories during the project, 3 portions of each of six 27 kg samples of ground peanuts were sent to each laboratory for analysis over a period of 6 weeks. Aflatoxin concentrations ranged from 0 to 300 ng/g when eight 200 g subsamples of each sample were analyzed by liquid chromatography (LC). For the 5 samples contaminated with aflatoxin, relative standard deviations for repeatability (RSDr) for laboratories using veratox FSP ranged from 18.66 to 53.29%, and the relative standard deviations for reproducibility (RSDR) ranged from 22.79 to 59.29%. For laboratories using the Aflatest system, RSDr values ranged from 18.70 to 41.48%, and RSDR values ranged from 23.84 to 47.56%. Horwitz ratios &lt; 2.0 were found for 4 of the 5 contaminated samples for both methods, indicating that the overall precision of the 2 methods used in the project was good. Mean aflatoxin concentrations, as determined with the rapid assay systems, were generally lower than those determined by LC, particularly for more highly contaminated samples. This could not be attributed to instability of aflatoxin in peanut paste, because additional information gathered in the study indicated that the stability of aflatoxin in peanut paste stored for 58 days was good.
9
Machado, Marcos V. M., Marcio F. Maggi, Eduardo G. de Souza, Rafaela G. da M. Camicia, and Regiane R. do Amarante. "Application of Plant Densities in Management Units in the Soybean Cultivation." Journal of Agricultural Science 10, no. 6 (2018): 319. http://dx.doi.org/10.5539/jas.v10n6p319.
Full textAbstract:
The application of management units (MU’s) aims to make economically viable to precision agriculture, making the technique accessible to a greater number of producers. Using MU’s, the experimental area is divided into plots with different productive potentials. In this context, the objective of the experiment was to verify the effectiveness of the area division in MU’s and to define the soybean plant density that provides higher productive efficiency in each MU. For the formation of MU’s it was used the altitude variation and the soil penetration resistance 0-0.1 m in the experimental area, being that the area was divided into 2 MU’s, called MU1 and MU2, and each MU was composed of 8 plots. At planting, 2 plant densities were applied, 214 000 and 257 000 plants ha-1, and each density was applied in 4 plots per MU, using row spacing of 0.70 m. In relation to productivity, there was a significant difference, applying the t-Student test, between MU’s, and the MU2, unit with higher productive potential, located in the highest part in the area, achieved higher productivity; and there was an effect, using the Tukey test, on the application of the 2 different plant densities in the MU’s, being that the densities of 214 000 and 257 000 plants ha-1 reached, respectively, higher productivity in MU2 and MU1.
10
Krebs, CJ, GR Singleton, and AJ Kenney. "Six reasons why feral house mouse populations might have low recapture rates." Wildlife Research 21, no. 5 (1994): 559. http://dx.doi.org/10.1071/wr9940559.
Full textAbstract:
Many feral house mouse populations have low recapture rates (0-20%) in live-trapping studies carried out at 2-4-week intervals. We consider six hypotheses to explain low recapture rates. We radio-collared 155 house mice between September 1992 and May 1993 in agricultural fields on the Darling Downs of south-eastern Queensland during a phase of population increase. Low recapture rates during the breeding season were due to low trappability and during the non-breeding period to nomadic movements. During the breeding season radio-collared mice of both sexes survived well and moved mostly small distances (<ll m). Low trappability has consequences for the precision of population indices that rely on catch per unit effort. Capture-recapture models robust to heterogeneity of trap responses should be used to census feral Mus populations.
11
Simm, G., P. Persaud, D. R. Neilson, H. Parkinson, and B. J. McGuirk. "Predicting food intake in dairy heifers from early lactation records." Animal Science 52, no. 3 (1991): 421–34. http://dx.doi.org/10.1017/s000335610001299x.
Full textAbstract:
ABSTRACTNucleus breeding schemes for dairy cattle give opportunities for selection on characteristics other than milk production, such as food intake or efficiency, and for the application of reproductive technologies such as embryo transfer. The emphasis in such schemes involving embryo transfer will be on early lactation measurements of production and food intake, to minimize generation intervals. The aim of this study was to examine the value of early lactation measurements of food intake and other characteristics in predicting longer-term food intake. Intakes of a complete diet, offered ad libitum, were available for 101 heifers up to week 38 of lactation, from the Edinburgh School of Agriculture's Langhill herd. Partial correlations between weekly dry-matter (DM) or metabolizable energy (ME) intakes in early lactation and cumulated intakes to week 38 of lactation, after fitting year and month of calving as fixed effects, and proportion of Holstein blood as a covariate, ranged from 0·27 for week 1, to 0·70 for week 12. Cumulated ME intakes, up to week 38, were regressed on shorter measures of ME intake, together with fat plus protein yield in weeks 1 to 10 of lactation. Other independent variables, such as point estimates of, or changes in, live weight, condition score and backfat depth did not further increase the precision of prediction. The means and standard deviations for milk yield, DM intake and ME intake up to week 38 of lactation were 5877 (s.d. 1087) kg, 4070 (s.d. 400) kg and 51579 (s.d. 4614) MJ respectively. For a fixed duration of intake recording, measurements taken later in lactation gave the most precise prediction of 38-week ME intake (e.g. residual s.d.s from models including 4-week cumulated ME intakes in weeks 1 to 4, 3 to 6 and 5 to 8 of lactation were 2865, 2636 and 2501 MJ respectively, with R2 values of 0·62, 0·67 and 0·71). Shorter periods of intake recording started in week 5 of lactation gave slightly more precise prediction than longer periods of recording started in weeks 1 to 4 (e.g. residual s.d.s from models including cumulative ME intakes in weeks 1 to 10, 3 to 10 and 5 to 10 were 2391, 2298 and 2277 respectively, with R2 values of 0·69, 0·75 and 0·76). These results have implications for the cost: benefit of food intake recording in breeding schemes.
12
Simhachalam, Joga, and Gandham Hima Bindu. "Studies on the Persistence of Pyraclostrobin 10% CS in Acidic, Neutral and Basic Waters by Validated HPLC-DAD Method." Advances in Research 25, no. 4 (2024): 30–39. http://dx.doi.org/10.9734/air/2024/v25i41078.
Full textAbstract:
This paper presents a method for the determination of pyraclostrobin 10% CS, a fungicide used in agriculture, in water samples with different pH values. The method is based on high-performance liquid chromatography with diode array detection (HPLC-DAD) and uses a reversed-phase column and a gradient elution. The method was validated according to the SANCO guidelines and showed good linearity, accuracy, precision, sensitivity and selectivity. The method was applied to study the persistence of pyraclostrobin 10% CS in acidic, neutral and basic water under laboratory conditions. The results showed that pyraclostrobin 10% CS was degraded rapidly in basic water with a half-life of less than ten days. The degradation products were identified by HPLC. The study involved exposing water samples to direct sunlight until the end of the experiment. The water samples had different pH levels: acidic (4.0), neutral (7.0) and basic (9.0). The water samples also contained Pyraclostrobin, a fungicide. The researchers collected aliquots of the water samples at various time intervals: 0, 1, 5, 10, 15, 20 and 30 days. The analysis continued until the Pyraclostrobin residues were below the detection limit. The DT50 can vary significantly depending on environmental conditions, such as pH levels. At pH 4, pH 7, and pH 9, the reported DT50 ranges between 6 to 8.1 days, indicating a moderate rate of degradation or dissipation in these conditions. These values suggest that the substance is relatively stable across a range of acidic to basic conditions, with only slight variations in the degradation rate.
13
Gava, Ricardo, Paulo S. L. de Freitas, Rogério T. de Faria, Roberto Rezende, and José A. Frizzone. "Soil water evaporation under densities of coverage with vegetable residue." Engenharia Agrícola 33, no. 1 (2013): 89–98. http://dx.doi.org/10.1590/s0100-69162013000100010.
Full textAbstract:
This study was conducted at the Agronomic Institute of Paraná (IAPAR) in Londrina, State of Paraná (PR), Brazil (latitude 23º18'S, longitude 51º09'W and average altitude of 585 m). The local climate, according to the classification of Köeppen, is Cfa type, i.e., humid subtropical climate, with rain in all seasons and can occur dry seasons during the winter. It was determined soil evaporation (E) under different coverage densities with residue from the wheat crop. The treatments were installed in weighting lysimeters of 2.66 m² and 1.3 m deep, which allows to determine E by the mass difference with measuring precision of 0.1mm at one hour intervals. Treatments consisted of 0; 2.5; 5 and 10 t ha-1 of wheat crop residues, placed evenly over each lysimeter. In the first cycle (September 22nd to October 20th, 2008), the reduction of E, as compared to a bare soil, was 4; 15 and 24%, while in the second cycle (December 1st to 30th, 2008), the reduction was of 15; 22 and 25%, respectively, for the treatments of 2.5; 5 and 10 t ha-1.
14
Ge, Xiangyu, Jianli Ding, Xiuliang Jin, et al. "Estimating Agricultural Soil Moisture Content through UAV-Based Hyperspectral Images in the Arid Region." Remote Sensing 13, no. 8 (2021): 1562. http://dx.doi.org/10.3390/rs13081562.
Full textAbstract:
Unmanned aerial vehicle (UAV)-based hyperspectral remote sensing is an important monitoring technology for the soil moisture content (SMC) of agroecological systems in arid regions. This technology develops precision farming and agricultural informatization. However, hyperspectral data are generally used in data mining. In this study, UAV-based hyperspectral imaging data with a resolution o 4 cm and totaling 70 soil samples (0–10 cm) were collected from farmland (2.5 × 104 m2) near Fukang City, Xinjiang Uygur Autonomous Region, China. Four estimation strategies were tested: the original image (strategy I), first- and second-order derivative methods (strategy II), the fractional-order derivative (FOD) technique (strategy III), and the optimal fractional order combined with the optimal multiband indices (strategy IV). These strategies were based on the eXtreme Gradient Boost (XGBoost) algorithm, with the aim of building the best estimation model for agricultural SMC in arid regions. The results demonstrated that FOD technology could effectively mine information (with an absolute maximum correlation coefficient of 0.768). By comparison, strategy IV yielded the best estimates out of the methods tested (R2val = 0.921, RMSEP = 1.943, and RPD = 2.736) for the SMC. The model derived from the order of 0.4 within strategy IV worked relatively well among the different derivative methods (strategy I, II, and III). In conclusion, the combination of FOD technology and the optimal multiband indices generated a highly accurate model within the XGBoost algorithm for SMC estimation. This research provided a promising data mining approach for UAV-based hyperspectral imaging data.
15
McClure, Julie. "Deconstructing Precision Agriculture." CSA News 60, no. 4 (2015): 26. http://dx.doi.org/10.2134/csa2015-60-4-15.
Full text
16
Oliveira, Cleomar Ferreira de, Marconi Batista Teixeira, Adriana Ramos, Renato Moreira da Silva, Pedro Henrique Pinto Ribeiro, and José Antônio Frizzone. "PORTABLE SAND FILTER FOR SMALL DRIP IRRIGATION SYSTEMS." IRRIGA 21, no. 1 (2018): 90. http://dx.doi.org/10.15809/irriga.2016v21n1p90-103.
Full textAbstract:
PORTABLE SAND FILTER FOR SMALL DRIP IRRIGATION SYSTEMS CLEOMAR FERREIRA DE OLIVEIRA1; MARCONI BATISTA TEIXEIRA2*; ADRIANA RAMOS3; RENATO MOREIRA DA SILVA4; PEDRO HENRIQUE PINTO RIBEIRO5 E JOSÉ ANTÔNIO FRIZZONE6 1 Engenheiro Agrônomo, Prof. Dr. IFMinas Gerais - Campus Muzambinho, MG.2 Engenheiro Agrônomo, Prof. Dr. IFGoiano - Campus Rio Verde, GO. *E-mail: marconibt@gmail.com3 Engenheira Agrônoma, Profa. Dra. Universidade Estadual de Santa Cruz – Ilhéus, BA.4 Engenheiro Agrônomo, Doutor, Departamento de Engenharia de Biossistemas, LEB - ESALQ/USP, Piracicaba - SP.5 Tecnólogo em Irrigação e Drenagem, Doutorando, Departamento de Engenharia Rural, UNESP/FCA, Botucatu, SP.6 Engenheiro Agrônomo, Prof. Titular, Departamento de Engenharia de Biossistemas, LEB - ESALQ/USP, Piracicaba - SP. 1 ABSTRACT Filters in drip irrigation systems are fundamental to ensure effective control of water quality and to reduce clogging of emitters. Current study aims at constructing a low cost portable sand filter for small localized irrigation systems (up to 1.0 ha) and at determining its head loss due to flow. Tests were carried out in the Hydraulic Laboratory of Biosystems Engineering Department of Agriculture School “Luiz de Queiroz”, University of São Paulo. Magnetic-induction Conaut Krohne model IFS 4000 w/6 with IFC 090 D signal convert of discharge, reading range between 0 and 90 m3.h-1 and 99% precision, was used for flow rate measurements. Pressure loss at each observation point was determined indirectly by two differential pressure gauges with a mercury column. A set of 20 flow readings was performed in three replications. Results showed that maximum filter discharge complied with ASAE guidelines and the cost of materials for manufacture of the filter was U$ 382.15. Linear mathematical model adequately describes the loss of pressure of the sand filter due to flow variation. Rates of minimum and maximum flow recommended range between 0.0257 m3.h-1 and 0.556 m3.h-1, and thus may satisfy small trickle irrigation projects. Keywords: Filtration, water quality, head loss, flow rate.
17
Sharaby, Noureldin N., Artyom A. Doroshenko, and Andrey V. Butovchenko. "Simulation of Sesame Seeds Outflow in Oscillating Seed Metering Device Using DEM." Engineering Technologies and Systems 30, no. 2 (2020): 219–31. http://dx.doi.org/10.15507/2658-4123.030.202002.219-231.
Full textAbstract:
Introduction. Sesame crop is one of the most important export crops in many countries around the world, especially in Africa. To meet the agricultural requirement of precision planting, various types of precision seed planters have been developed. Numerous studies were carried out to study the optimisation of the parameters of the precision planting. One of these parameters, affecting the quality of the precision seeder, is the grain outflow from the seed metering device. Materials and Methods. In order to maintain good continuous performance of an oscillating seeder, it is important to monitor seed flow in real-time and adjust oscillation parameters automatically. Existing research methods, such as prototyping and monitoring the process using a high-speed camera, by reason of the random movement of particles, do not allow obtaining sufficient data to understand trajectories and velocities of particles and existing equations for particle motion when simulating the sowing process do not allow taking into account the interaction of particles that having various shapes, rolling and sliding friction coefficients, and the elastic modulus of particle materials and a working body. In this study, the outflow rate of sesame seeds in an oscillating seed metering device was modeled using the simulation method based on the discrete element method. The aim of this study is to create a simulation model of an oscillating-type sowing planter using the sowing sesame seeds as an example for evaluating the effectiveness of this model, and the possibility of further optimization and prediction of sowing seeds with this device. Results. The analysis of the results showed that during the simulation, the sowing rate of sesame seeds when leaving the oscillating seed metering holes has significant differences in number and direction. The results of the modeling process in this study showed that when opening a hole in the oscillating seeder, a number of sesame seeds from 0 to 4 were coming out of it. The resulting model allows monitoring the behavior of each particle of a sesame seed, analyzing its trajectory, speed, and forces acting on it at any one time, and varying the parameters to obtain the dependence of uneven seeding on the kinematic and geometric parameters of the device. Discussion and Conclusion. The obtained simulation results provide an effective method for predicting the consumption of sesame seeds from the oscillating seed meter, which serves as the basis for optimizing the kinematic and geometric parameters of the oscillating sowing device in order to increase its efficiency. This model is universal and can be adapted to sow other crops.
18
Cambouris, A. N., B. J. Zebarth, N. Ziadi, and I. Perron. "Precision Agriculture in Potato Production." Potato Research 57, no. 3-4 (2014): 249–62. http://dx.doi.org/10.1007/s11540-014-9266-0.
Full text
19
Simm, G., and S. V. Murphy. "The effects of selection for lean growth in Suffolk sires on the saleable meat yield of their crossbred progeny." Animal Science 62, no. 2 (1996): 255–63. http://dx.doi.org/10.1017/s1357729800014557.
Full textAbstract:
AbstractThis experiment involved a commercial evaluation of carcasses of extensively reared crossbred lambs. These were sired by Suffolk rams from either a selection line or a control line of a Scottish Agricultural College (SAC) selection experiment, in which selection wasfor lean growth, or by Suffolk ‘reference sires’ from an industry co-operative breeding scheme (SSRS). The lambs were slaughtered at a target live weight of 42 kg between June and October 1992. In total, 421 lamb carcasses were included in the evaluation, 173 from six selection-line rams, 193 from six control-line rams and 55from three SSRS rams. Each of the carcasses was visually appraised for estimated subcutaneous fat proportion and for conformation of the shoulder, loin and leg, as well as being classified using conventional Meat and Livestock Commission (MLC) scales for fat and conformation. Animals were slaughtered at an average age of 139·5 (s.d. 25·6) days and achieved an average cold carcass weight of 20·04 (s.d. 0·96) kg. Carcasses had an average estimated subcutaneous fat proportion of 122·3 (s.d. 22·4) g/kg — equivalent to MLC fat class 3L to 3H. Overall conformation scores, on a 15-point scale, averaged 8·63 (s.d. 1·80) points. Carcasses were cut into joints according to a leading supermarket specification. The weights of pairs of shoulder, flank, loin and leg joints were obtained for each carcass, as well as weights of bone and fat removed during jointing. Saleable meat weights and proportions averaged 15·31 (s.d. 0·76) kg and 765·9 (s.d. 10·0) g/kg respectively. At a constant carcass weight, the SAC selection-line progeny were significantly younger (-11 days), had a significantly higher carcass value (+£1·50), a significantly lower estimated subcutaneous fat proportion (-13 g/kg), and a significantly higher weight of saleable meat (+0·1 kg) and higher proportion ofsaleable meat (+4 glkg) than control-line progeny, but had lower conformation scores. SSRS progeny had similar growth and fatness to selection-line lambs, but had poorer conformation, and significantly more bone in the carcass than either of the SAC lines. When comparisons were made at a constant estimated subcutaneous fat proportion, all differences in conformation between SAC lines disappeared. However, SSRS progeny remained poorer in conformation. The SSRS rams werefrom afoundation generation of the scheme, and were not expected to be markedly superior for carcass characteristics. Carcass weight was byfar the most important predictor of weight of saleable meat, or leg and loin joint weights. Conformation and estimated fat proportion made only marginal improvements, if any, to the precision of prediction, with fat proportion being the more important of the two predictors.
20
Zhang, Naiqian, Maohua Wang, and Ning Wang. "Precision agriculture—a worldwide overview." Computers and Electronics in Agriculture 36, no. 2-3 (2002): 113–32. http://dx.doi.org/10.1016/s0168-1699(02)00096-0.
Full text
21
Schmoldt, D. L. "Precision agriculture and information technology." Computers and Electronics in Agriculture 30, no. 1-3 (2001): 5–7. http://dx.doi.org/10.1016/s0168-1699(00)00151-4.
Full text
22
Duff, Hannah, Paul B. Hegedus, Sasha Loewen, Thomas Bass, and Bruce D. Maxwell. "Precision Agroecology." Sustainability 14, no. 1 (2021): 106. http://dx.doi.org/10.3390/su14010106.
Full textAbstract:
In response to global calls for sustainable food production, we identify two diverging paradigms to address the future of agriculture. We explore the possibility of uniting these two seemingly diverging paradigms of production-oriented and ecologically oriented agriculture in the form of precision agroecology. Merging precision agriculture technology and agroecological principles offers a unique array of solutions driven by data collection, experimentation, and decision support tools. We show how the synthesis of precision technology and agroecological principles results in a new agriculture that can be transformative by (1) reducing inputs with optimized prescriptions, (2) substituting sustainable inputs by using site-specific variable rate technology, (3) incorporating beneficial biodiversity into agroecosystems with precision conservation technology, (4) reconnecting producers and consumers through value-based food chains, and (5) building a just and equitable global food system informed by data-driven food policy. As a result, precision agroecology provides a unique opportunity to synthesize traditional knowledge and novel technology to transform food systems. In doing so, precision agroecology can offer solutions to agriculture’s biggest challenges in achieving sustainability in a major state of global change.
23
Lichman, G. I., S. A. Belykh, and A. N. Marchenko. "METHODS OF APPLYING FERTILIZERS IN PRECISION AGRICULTURE." Agricultural Machinery and Technologies 12, no. 4 (2018): 4–9. http://dx.doi.org/10.22314/2073-7599-2018-12-4-4-9.
Full textAbstract:
It is impossible to achieve the planned yields, product quality, and economic efficiency in agricultural production using only organic fertilizers. joint application of organic and solid mineral fertilizers solves the problem of replenishing the soil content of nitrogen, phosphorus and other elements used by plants. The authors have carried out the research of new methods of variable-rate application of mineral fertilizers in plant growing, allowing to increase the profitability of agricultural production. (Research purpose) is to develop new methods of variable-rate application of mineral fertilizers in crop production, which will allow increasing the profitability of crop production as compared with the conventional methods of applying fertilizers basing on average field indicators. (Materials and methods) The authors have developed a calculation technique implemented in the VBA Excel computer program for determining the main indicators: gross output, fertilizer saving, profit, etc. The main variable to change in the calculations is the planned yield based on average field parameters. At the end of the calculation process, the values of the best result for gross harvest output and profit are displayed on the screen. The research objects for the calculation were represented by elementary areas of crop areas of three farms – “Prodresurs”, Agropoligon VIUA, and “Murminskoye” with different soil types: chernozem, loamy, and sandy-loam. (Results and discussion) The method of proportional variable-rate application of fertilizers on three types of soils gives a stable increase in profit as compared with the application of fertilizers basing on the average field indicators. (Conclusions) Calculations have shown that under the specified conditions and at the equal yield of 30 c/ha the application of organomineral fertilizers is the most effective, profitability has accounted for 40 percents – on mesopodzol sandy-loam soils; 8.7 percents – on sod-podzolic soils; and 1.3 percents – on black soils. The method of proportional variable-rate application of mineral fertilizers accompanied with variable-rate application of organic fertilizers makes it possible to reduce the amount of mineral fertilizers applied by half.
24
Tulayev, Yu V., A. B. Abuova, S. V. Somova, A. I. Sidorik, and O. S. Safronova. "The nutritional regime of the soil and the nitrogen status of plants in the grain-fallow and fruitshifting crop rotations." Agrarian science, no. 3 (May 8, 2022): 51–56. http://dx.doi.org/10.32634/0869-8155-2022-357-3-51-56.
Full textAbstract:
The main agrotechnical significance of crop rotation is that each crop is placed in the best conditions for its growth and development and at the same time prepares good conditions for the next crop in the crop rotation. Under optimal cultivation conditions and a high level of mineral nutrition, the grain yield of modern wheat varieties reaches 18.4 c/ha. In real economic conditions, when high prices for mineral fertilizers limit their use, the yield of spring wheat grain in the Kostanay region is 11.2 c/ha. In the experiment, 2 types of crop rotations were studied — 4-course grain-fallow (fallow— wheat — wheat — wheat) and 4-course fruit-shifting (peas — wheat — oilseed flax — wheat). On each crop rotation variants with different levels of mineral nutrition were laid — without fertilizers (control) and P15. Seeding rate of agricultural crops (million/ha of germinating seeds): spring wheat — 3.0; peas — 1.0; oilseed flax — 6.0. The experiment adopted the technology of tillage — No-till with elements of precision farming. All records and observations were carried out according to standard methods. The analysis of the dynamics of the food regime of the soil indicates that the best conditions for mineral nutrition of plants are created when placing crops in a grain-fallow crop rotation, which includes herbicidal steam with long-term annual application of mineral fertilizers. Thus, in the soil layer of 0–40 cm on the first wheat after fallow, the content of nitrate nitrogen was characterized as average and amounted to 11.9–12.8 mg/kg, the content of mobile phosphorus had increased and amounted to 121 mg/kg of soil. In terms of the effectiveness of the use of options for the purpose of regulating the food regime, it is necessary to distinguish all three wheat fields in the grain-fallow crop rotation. Here, the highest indicator in the earing phase — above the control by 6.1–14.7% — was in variants with the use of fertilizer in rows.
25
De Baerdemaeker, Josse. "Process Monitoring and Control for Precision Agriculture." IFAC Proceedings Volumes 33, no. 29 (2000): 23–30. http://dx.doi.org/10.1016/s1474-6670(17)36746-0.
Full text
26
Stafford, John V., and Paul G. Carter. "10th European Conference on Precision Agriculture (Part III)." Precision Agriculture 18, no. 6 (2017): 899. http://dx.doi.org/10.1007/s11119-017-9547-0.
Full text
27
Davoodi, Mohammadreza, Javad Mohammadpour Velni, and Changying Li. "Coverage Control with Multiple Ground Robots for Precision Agriculture." Mechanical Engineering 140, no. 06 (2018): S4—S8. http://dx.doi.org/10.1115/1.2018-jun-4.
Full textAbstract:
In this work, coverage of agricultural fields using a team of autonomous unmanned ground robots with no human intervention is investigated. To this end, field is first represented by a topological mapandthenadistributedenergy-awaredeployment strategy is proposed to optimally distribute robots with the aim of persistent monitoring of specified regions of interest. When a robot participating in the coverage task approaches a low energy reserve, the team of robots collectively and cooperatively adjust the coverage formation to allow the agent to return to a designated base station, where it can recharge before rejoining the effort. Preliminary (simulation) results are provided to show the effectiveness and capabilities of the proposed coverage algorithm.
28
García-Munguía, Argelia, Paloma Lucía Guerra-Ávila, Efraín Islas-Ojeda, et al. "A Review of Drone Technology and Operation Processes in Agricultural Crop Spraying." Drones 8, no. 11 (2024): 674. http://dx.doi.org/10.3390/drones8110674.
Full textAbstract:
Precision agriculture is revolutionizing the management and production of agricultural crops. The development of new technologies in agriculture, such as unmanned aerial vehicles (UAVs), has proven to be an efficient option for spraying various compounds on crops. UAVs significantly contribute to enhancing precision agriculture. This review aims to determine whether integrating advanced precision technologies into drones for crop spraying enhances spraying accuracy compared to drones utilizing standard spraying technologies. To achieve this, 100 articles published between 2019 and 2024 were selected and analyzed. The information was summarized into five main areas: (1) improved spraying with agricultural drone technologies, (2) operational parameters, (3) spraying applications of chemical and natural compounds with agricultural drones, (4) evaluations of control pest efficacy, and (5) considerable limitations. Finally, considerations are presented on the advantages of drone technology with artificial intelligence (AI); the practical effects of reducing pesticides, which, in some cases, have reached a reduction of 30% compared to the recommended dose; and future directions for improving precision agriculture. The use of drones in precision agriculture presents technical and scientific challenges for the maximization of spraying efficiency and the minimization of agrochemical use.
29
Cook, S. E., and R. G. V. Bramley. "Precision agriculture — opportunities, benefits and pitfalls of site-specific crop management in Australia." Australian Journal of Experimental Agriculture 38, no. 7 (1998): 753. http://dx.doi.org/10.1071/ea97156.
Full textAbstract:
Summary. Precision agriculture is the term given to crop management methods which recognise and manage within-paddock spatial and temporal variations in the soil–plant–atmosphere system. This paper reviews the principles, practice and perceived benefits of precision agriculture. The objective of precision agriculture is to improve the control of input variables such as fertiliser, seed, chemicals or water with respect to the desired outcomes of increased profitability, reduced environmental risk or better product quality. The practice can be viewed as comprising 4 stages: information acquisition; interpretation; evaluation; and control. Much of the technology to acquire information and control machinery is available or at a late stage of development. However, methods of interpretation are less well developed.
30
Hundal, Gaganpreet Singh, Chad Matthew Laux, Dennis Buckmaster, Mathias J. Sutton, and Michael Langemeier. "Exploring Barriers to the Adoption of Internet of Things-Based Precision Agriculture Practices." Agriculture 13, no. 1 (2023): 163. http://dx.doi.org/10.3390/agriculture13010163.
Full textAbstract:
The production of row crops in the Midwestern (Indiana) region of the US has been facing environmental and economic sustainability issues. There has been an increase in trend for the application of fertilizers (nitrogen & phosphorus), farm machinery fuel costs and decreasing labor productivity leading to non-optimized usage of farm inputs. Literature describes how sustainable practices such as profitability (return on investments), operational cost reduction, hazardous waste reduction, delivery performance and overall productivity might be adopted in the context of precision agriculture technologies (variable rate irrigation, variable rate fertilization, cloud-based analytics, and telematics for farm machinery navigation). The literature review describes low adoption of Internet of Things (IoT)-based precision agriculture technologies, such as variable rate fertilizer (39%), variable rate pesticide (8%), variable rate irrigation (4%), cloud-based data analytics (21%) and telematics (10%) amongst Midwestern row crop producers. Barriers to the adoption of IoT-based precision agriculture technologies cited in the literature include cost effectiveness, power requirements, wireless communication range, data latency, data scalability, data storage, data processing and data interoperability. Therefore, this study focused on exploring and understanding decision-making variables related to barriers through three focus group interview sessions conducted with eighteen (n = 18) subject matter experts (SME) in IoT- based precision agriculture practices. Dependency relationships described between cost, data latency, data scalability, power consumption, communication range, type of wireless communication and precision agriculture application is one of the main findings. The results might inform precision agriculture practitioners, producers and other stakeholders about variables related to technical and operational barriers for the adoption of IoT-based precision agriculture practices.
31
Vorokh, Viktor, and Vitalii Zatserkovnyi. "Use of unmanned aerial vehicles in precision agriculture." Technical sciences and technologies, no. 4 (38) (December 30, 2024): 336–49. https://doi.org/10.25140/2411-5363-2024-4(38)-336-349.
Full textAbstract:
The use of unmanned aerial vehicles (UAVs) in agriculture in general, and precision agriculture in particular, is expanding significantly every year. UAVs are employed in various tasks, including sowing, monitoring crop growth and yields, field mapping, and spraying crops with plant protection products (PPP) or applying fertilizers. Precision agriculture enables the integration of geospatial data, GIS and remote sensing technologies, artificial intelligence, Big Data, the Internet of Things, and other innovative solutions. UAVs provide opportunities for rapid monitoring, analyzing field conditions and dynamics, identifying problem areas requiring managerial intervention, evaluating the effectiveness of agronomic practices, and storing photogrammetric data and high-resolution images efficiently. Modern UAVs, accessible to farmers, not only deliver current information on plant condition and growth dynamics but also allow for protective treatment of fields and perennial plantations using pesticides. UAVs can provide georeferenced data on the state of cultivated crops, significantly assisting farmers in maintaining high yields. Moreover, UAVs equipped with multispectral and RGB cameras enable the prompt storage of agricultural images in the near-infrared spectrum, facilitating monitoring of vegetation health and condition. UAV imaging offers much greater detail compared to satellite imagery, achieving resolutions down to centimeters per pixel, thanks to flight altitudes ranging from 100 to 600 meters above ground. The paper outlines the use of UAVs in precision agriculture and explores field monitoring methods using UAVs. The implementation of UAV imaging technology allows for the creation of electronic field maps and the rapid adoption of managerial decisions based on the collected data. The NDVI index obtained with UAVs provides a more comprehensive and detailed representation of current conditions on individual field sections, a level of detail that is difficult to achieve with satellite imagery. It is noted that our country has strong potential for adopting UAVs in agriculture, considering their technical, economic, and human resources.
32
Mohammed, Maged, Muhammad Munir, and Aljazi Aljabr. "Prediction of Date Fruit Quality Attributes during Cold Storage Based on Their Electrical Properties Using Artificial Neural Networks Models." Foods 11, no. 11 (2022): 1666. http://dx.doi.org/10.3390/foods11111666.
Full textAbstract:
Evaluating and predicting date fruit quality during cold storage is critical for ensuring a steady supply of high-quality fruits to meet market demands. The traditional destructive methods take time in the laboratory, and the results are based on one specific parameter being tested. Modern modeling techniques, such as Machine Learning (ML) algorithms, offer unique benefits in nondestructive methods for food safety detection and predicting quality attributes. In addition, the electrical properties of agricultural products provide crucial information about the interior structures of biological tissues and their physicochemical status. Therefore, this study aimed to use an alternative approach to predict physicochemical properties, i.e., the pH, total soluble solids (TSS), water activity (aw), and moisture content (MC) of date fruits (Tamar), during cold storage based on their electrical properties using Artificial Neural Networks (ANNs), which is the most popular ML technique. Ten date fruit cultivars were studied to collect data for the targeted parameters at different cold storage times (0, 2, 4, and 6 months) to train and test the ANNs models. The electrical properties of the date fruits were measured using a high-precision LCR (inductance, capacitance, and resistance) meter from 10 Hz to 100 kHz. The ANNs models were compared with a Multiple Linear Regression (MLR) at all testing frequencies of the electrical properties. The MLR models were less accurate than ANNs models in predicting fruit pH and had low performance and weak predictive ability for the TSS, aw, and MC at all testing frequencies. The optimal ANNs prediction model consisted of the input layer with 14 neurons, one hidden layer with 15 neurons, and the output layer with 4 neurons, which was determined depending on the measurements of the electrical properties at a 10 kHz testing frequency. This optimal ANNs model was able to predict the pH with R2 = 0.938 and RMSE = 0.121, TSS with R2 = 0.954 and RMSE = 2.946, aw with R2 = 0.876 and RMSE = 0.020, and MC with R2 = 0.855 and RMSE = 0.803 b by using the measured electrical properties. The developed ANNs model is a powerful tool for predicting fruit quality attributes after learning from the experimental measurement parameters. It can be suggested to efficiently predict the pH, total soluble solids, water activity, and moisture content of date fruits based on their electrical properties at 10 kHz.
33
Matthew, N. O. Sadiku, A. Omotoso Adedamola, and M. Musa Sarhan. "Green Agriculture." International Journal of Trend in Scientific Research and Development 4, no. 2 (2020): 69–70. https://doi.org/10.5281/zenodo.3842922.
Full textAbstract:
Agriculture has made an enormous environmental footprint and is making agricultural development risky. Green agriculture uses well developed modern farming and sustainability concepts to improve natural agricultural techniques. It also draws on green technology to enhance farming. This paper provides a brief introduction on green agriculture. Matthew N. O. Sadiku | Adedamola A. Omotoso | Sarhan M. Musa "Green Agriculture" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-2 , February 2020, URL: https://www.ijtsrd.com/papers/ijtsrd29792.pdf
34
Pashkov, Sergey V., and Gulnur Z. Mazhitova. "DIGITIZATION OF AGRICULTURE IN KAZAKHSTAN: REGIONAL EXPERIENCE." Географический вестник = Geographical bulletin, no. 4(59) (2021): 27–41. http://dx.doi.org/10.17072/2079-7877-2021-4-27-41.
Full textAbstract:
The article deals with digitization of agriculture as the determinative direction of crop production intensification in Kazakhstan. The main condition for the digitization to be implemented is the development of precision agriculture. The aim of our work is to study the process of agricultural digitization in Kazakhstan and particularly the North Kazakhstan region, which is the oldest territory of rainfed agriculture and the leading area in terms of crop production by value and in terms of economic fertility of rainfed land. We analyze the main provisions of state programs (‘Kazakhstan–2050’, ‘Digital Kazakhstan’) aimed at integrating geospatial technologies into farming and crop production, which is supposed to increase labor productivity in the industry. In the course of research, the peculiarities of using satellite imagery and shooting from unmanned aerial vehicles in precision agriculture were noted; factors that hinder the introduction of digital technologies in the development of agriculture were identified; SWOT analysis of environmental and economic conditions of the precision agriculture development in the region was carried out. The article proposes measures to be taken for further development of agricultural digitization in the region: both innovative (development of agrarian voltaics) and paternalistic ones (state stimulation of agrarian formations, etc.). The digitization of the agricultural sector will create econologically sustainable programmable system of farming based on high natural agricultural potential and advanced geospatial technologies resting on predictive analytics.
35
Gusev, Aleksey, Egor Skvorcov, and Ekaterina Morozova. "Studying the international practice of introducing precision farming technologies based on national programs for the development of the agrarian sector of foreign countries." Russian Journal of Management 8, no. 3 (2020): 121–25. http://dx.doi.org/10.29039/2409-6024-2020-8-3-121-125.
Full textAbstract:
The relevance of the research lies in the insufficiently studied theoretical aspects of the application of precision farming technologies. The development programs of the industry in countries with developed agriculture contain separate elements for the development of precision farming technologies. The aim is to study the international practice of introducing precision farming technologies on the basis of national programs for the development of the agrarian sector of countries with developed agriculture. The United States occupies a leading position in the development of precision farming technologies. This became possible thanks to the implementation of the Food and Agriculture Cyber Informatics and Tools (FACT) program, as well as the development of these technologies by private companies (Ag Leader Technology; AgJunction, Inc; CropMetrics LLC, etc.). In the People's Republic of China, in the Thirteenth Five-Year Plan for the Economic and Social Development of the Republic, Article 4 proclaims a course for the modernization of agriculture, which is designed for 2015-2020. It is planned to introduce a regional pilot project in the field of precision farming technologies based on IoT, increasing the level of intelligence and precision of agriculture. Japan has implemented the Strategic Innovation Promotion Program (SIP) for the next generation of agriculture, forestry and fisheries. Its main tasks include an automatic travel system for agricultural machinery under human supervision (by 2018), as well as an unmanned system for agricultural machinery with remote monitoring (by 2020). In total, 15.6 billion yen (11.5 billion rubles) was allocated for the implementation of these tasks in the period from 2014 to 2018. In Germany, 14 digital innovation parks have been created, aimed at developing both precision farming technologies and technologies of the Internet of things, big data and others.
36
Abidin, Zainul, Raisul Falah, Raden Arief Setyawan, and Fitri Candra Wardana. "Wireless sensor network using nRF24L01+ for precision agriculture." Bulletin of Electrical Engineering and Informatics 14, no. 2 (2025): 1003–13. https://doi.org/10.11591/eei.v14i2.8481.
Full textAbstract:
Precision agriculture is a strategy for varying inputs and cultivation methods to suit varying soil conditions and agricultural crops. In order to optimize precision agriculture, wireless sensor network (WSN) is suitable to be integrated. In this research, network devices that communicate using nRF24L01+ based WSN was proposed. As a prototype, four sensor nodes were employed to measure the parameters of air temperature and humidity, soil moisture, and power supply voltage. While, a sink node serves to store measurement data locally. The data are sent to the sink node with a mesh network topology and saved in a comma-separated values (CSV) file and local database. Experimental results show that each sensor node can measure all parameters and successfully send data to the sink node every 1 minute without losing the data. The mesh topology can route data transfer automatically. Round trip time (RTT) of each sensor node depends on the distance from each node. Average power consumption of all sensor nodes in send mode is between 84 mW and 90 mW. Meanwhile, in sleep mode, the sensor nodes 1 and 2 consumed around 21-22 mW and the sensor nodes 3 and 4 consumed around 30 mW which are lower than the send mode.
37
Krug, Evelin T. S., Glaucio J. Gomes, Eduardo G. de Souza, Luciano Gebler, Ricardo Sobjak, and Claudio L. Bazzi. "Estimating soil loss by laminar erosion using precision agriculture computational tools." Revista Brasileira de Engenharia Agrícola e Ambiental 26, no. 12 (2022): 907–14. http://dx.doi.org/10.1590/1807-1929/agriambi.v26n12p907-914.
Full textAbstract:
ABSTRACT The study aimed to identify and evaluate the spatial variability in laminar erosion in areas using precision agriculture tools. Soil data from three properties in the western region of Paraná state, Brazil, were used: one in the municipality of Céu Azul (area A) and two in Serranópolis do Iguaçu (areas B and C). To identify discrepant data (outliers), analysis of the dispersion of quartiles was performed using a box-plot graph. Data normality was verified using the Kolmogorov-Smirnov test. A spatial analysis was performed using AgDataBox-Map software. The parameters of the universal soil loss equation were estimated and used with map algebra to produce a model to identify areas susceptible to erosion. Area A (soil loss estimate = 0-200 t ha-1 per year) presented greater susceptibility to erosion than areas B and C (soil loss estimate = 0-150 t ha-1 per year); however, all areas had a low susceptibility to erosion.
38
Nash, Edward, Peter Korduan, and Ralf Bill. "Applications of open geospatial web services in precision agriculture: a review." Precision Agriculture 10, no. 6 (2009): 546–60. http://dx.doi.org/10.1007/s11119-009-9134-0.
Full text
39
Borgest, N. М., D. V. Budaev, and V. V. Travin. "ONTOLOGY OF PRECISION AGRICULTURE DESIGN: PROBLEM STATE, SOLUTION APPROACHES." Ontology of Designing 26, no. 7 (2017): 423–42. http://dx.doi.org/10.18287/2223-9537-2017-7-4-423-442.
Full text
40
Кyrychenko, Roman, and Serhii Burlaka. "WAYS OF IMPROVING WORKING BODIES OF PLANTERS FOR PRECISION AGRICULTURE." Vibrations in engineering and technology, no. 4(111) (December 2, 2023): 37–46. http://dx.doi.org/10.37128/2306-8744-2023-4-6.
Full textAbstract:
The article is devoted to the study of the Кey role played by planters in modern practices of sustainable agriculture. Modern structural and technological solutions used in planters, such as automation, built-in sensors and artificial intelligence, and their impact on increasing productivity and optimizing crop cultivation are considered. The authors draw attention to environmental aspects, including spot seeding and the use of renewable energy sources in planters, which contribute to the conservation of resources. In addition, the prospect of introducing artificial intelligence and autonomous systems in planters to improve the efficiency and rationalization of crop cultivation processes is discussed. The Кey aspects and advantages of using seed drills in the practice of sustainable agriculture are noted. A special emphasis is placed on technological innovations, including automation, built-in sensors and the use of artificial intelligence. The potential of increasing productivity and optimizing agronomic processes to achieve a higher level of productivity with efficient use of resources is considered. The article pays special attention to the ecological aspects that can be achieved with spot seeding. The advantages of these approaches are noted, such as improving the quality of the soil, which ensures stable and sustainable cultivation of agricultural crops. Further development of the topic includes a discussion of the prospects for the use of artificial intelligence and autonomous systems in planters, which can lead to further improvements in efficiency and cost reduction. The authors of the paper highlight the Кey aspects of using seed drills as a tool to conserve biodiversity while ensuring sustainable and sustainable agriculture for future generations..
41
Chesnokov, Yu V. "QTL analysis and management of plant productivity in the precision agriculture." Vegetable crops of Russia, no. 4 (August 27, 2020): 12–19. http://dx.doi.org/10.18619/2072-9146-2020-4-12-19.
Full textAbstract:
Modern crop cultivation technologies have reached the limits of “saturation” both in the ecological (environmental pollution, suppression of the mechanisms of its self-regulation), energy (exponential growth of irreplaceable energy costs for each additional unit of production), and in production. In this regard, environmental factors (air drought, frosts, active temperatures, etc.), which cannot be optimized, are becoming increasingly important in ensuring a steady increase in the yield of cultivated plant forms. In recent decades, more and more attention has been paid to technogenic and biological systems of agriculture, based on the ecologization and biologization of the intensification processes of adaptive crop production. Such approaches are the precision agriculture system (PA) and QTL analysis. Using these approaches allows not only to ensure a steady increase in productivity due to the combined use of the advantages of precision farming and molecular genetic assessment, including the creation of new forms and varieties that are responsive to РА agricultural practices, but also to level the negative impact of abiotic and biotic environmental factors that limit the size and quality of the crop as well as plant productivity. It is shown that the strategy of adaptive intensification of crop production through the use of the TK system and QTL analysis approaches is not alternative to existing farming systems, however, it focuses modern agriculture on the growth of knowledge-intensive agricultural production as a whole. An analysis of the causes under consideration, the current unfavorable trends in modern crop production and agriculture, clearly shows their scale and long-term nature, and therefore the inevitability of the search for new priorities for intensification of crop production and agriculture, providing a qualitatively new stage of their development in the interests of man.
42
Stafford, John V., and Jim Schepers. "Introduction: Special Issue on 8th European Conference on Precision Agriculture (ECPA)." Precision Agriculture 14, no. 1 (2013): 1. http://dx.doi.org/10.1007/s11119-012-9303-4.
Full text
43
Epinat, Virginie, Alfred Stein, Steven M. de Jong, and Johan Bouma. "A wavelet characterization of high-resolution NDVI patterns for precision agriculture." International Journal of Applied Earth Observation and Geoinformation 3, no. 2 (2001): 121–32. http://dx.doi.org/10.1016/s0303-2434(01)85003-0.
Full text
44
Filippini-Alba, J. M., G. R. Crizel, C. L. Girardi, and C. A. Flores. "Precision Viticulture Focusing Southern Brazil." International Journal of Advanced Engineering Research and Science 9, no. 12 (2022): 542–53. http://dx.doi.org/10.22161/ijaers.912.60.
Full textAbstract:
There are four main wine regions in Rio Grande do Sul state, Brazil: (1) "Serra Gaúcha"; (2) São Francisco Valley; (3) “Serra do Sudeste” and (4) “Campos de Cima da Serra”. The region (1) is the oldest wine region of Brazil, related to Italian immigration in nineteen century. Regions (2), (3) and (4) are newer, showing similarities but soft changes in climate and soil conditions. Precision viticulture (PV) has advanced in these poles in the last 20 years. Different techniques related to precision viticulture in the context of the precision agriculture (PA) network of Embrapa, including soil mapping, physical properties sensors, remote sensing, spectrorradiometry and miscellaneous methods. Results suggest a medium technological development of PA in Brazil, with the most approaches related to grain production and few enterprises of growing fruit or viticulture, including PV. Most techniques considered an academic context or, in a few specific cases, the productive sector.
45
Schultze, Steven R., Murdoch N. Campbell, Samantha Walley, Katie Pfeiffer, and Bryan Wilkins. "Exploration of sub-field microclimates and winter temperatures: Implications for precision agriculture." International Journal of Biometeorology 65, no. 7 (2021): 1043–52. http://dx.doi.org/10.1007/s00484-021-02086-0.
Full text
46
Yost, M. A., K. A. Sudduth, C. L. Walthall, and N. R. Kitchen. "Public–private collaboration toward research, education and innovation opportunities in precision agriculture." Precision Agriculture 20, no. 1 (2018): 4–18. http://dx.doi.org/10.1007/s11119-018-9583-4.
Full text
47
Miller, N. J., T. W. Griffin, I. A. Ciampitti, and A. Sharda. "Farm adoption of embodied knowledge and information intensive precision agriculture technology bundles." Precision Agriculture 20, no. 2 (2018): 348–61. http://dx.doi.org/10.1007/s11119-018-9611-4.
Full text
48
Vrindts, E., M. Reyniers, P. Darius, et al. "Analysis of Soil and Crop Properties for Precision Agriculture for Winter Wheat." Biosystems Engineering 85, no. 2 (2003): 141–52. http://dx.doi.org/10.1016/s1537-5110(03)00040-0.
Full text
49
Borisenko, N. A. "Precision agriculture in Kyrgyzstan: a vague future or a philosophical formality." Abyss (Studies in Philosophy, Political science and Social anthropology), no. 4(30) (2024): 88–96. https://doi.org/10.33979/2587-7534-2024-4-88-96.
Full textAbstract:
This study attempts to answer the urgent question of the development of agriculture in Kyrgyzstan, considering the existing realities of the economic opportunities of farmers and the level of technologies used to a greater extent in the agricultural sector. The author examines the problems of strategic planning from the perspective of futures studies, pointing out the role that the methodological approaches of Futures Consciousness, foresight and Anticipatory Governance can play in this.
50
Sanders, Catherine E., Kennedy A. Mayfield-Smith, and Alexa J. Lamm. "Exploring Twitter Discourse around the Use of Artificial Intelligence to Advance Agricultural Sustainability." Sustainability 13, no. 21 (2021): 12033. http://dx.doi.org/10.3390/su132112033.
Full textAbstract:
This paper presents an exploration of public discourse surrounding the use of artificial intelligence (AI) in agriculture, specifically related to precision agriculture techniques. (1) Advancements in the use of AI have increased its implementation in the agricultural sector, often framed as a sustainable solution for feeding a growing global population. However, lessons learned from previous agricultural innovations indicate that new technologies may face public scrutiny and suspicion, limiting the dissemination of the innovation. Using systems thinking approaches can help to improve the development and dissemination of agricultural innovations and limit the unintended consequences of innovations within society. (2) To analyze the current discourse surrounding AI in agriculture, a content analysis was conducted on Twitter using Meltwater to select tweets with specific reach and engagement. (3) Seven themes resulted from the analysis: precision agriculture and digital technology innovation; transformation and the future of agriculture; accelerate solutions, solve challenges; data management and accessibility; transforming crop management, prioritizing adoption; and AI and sustainability. (4) The discourse on AI in agriculture on Twitter was overwhelmingly positive, failing to account for the potential drawbacks or limits of the innovation. This paper examines the limits of the current communication and outreach across environmental, economic, social, cultural, political, and behavioral contexts.