Agriculture

13 pages, 2759 KiB

Open AccessArticle

Classification of Fresh and Frozen-Thawed Beef Using a Hyperspectral Imaging Sensor and Machine Learning

by Seongmin Park, Suk-Ju Hong, Sungjay Kim, Jiwon Ryu, Seungwoo Roh and Ghiseok Kim

Agriculture 2023, 13(4), 918; https://doi.org/10.3390/agriculture13040918 - 21 Apr 2023

Cited by 1 | Viewed by 1764

The demand for safe and edible meat has led to the advancement of freeze-storage techniques, but falsely labeled thawed meat remains an issue. Many methods have been proposed for this purpose, but they all destroy the sample and can only be performed in [...] Read more.

The demand for safe and edible meat has led to the advancement of freeze-storage techniques, but falsely labeled thawed meat remains an issue. Many methods have been proposed for this purpose, but they all destroy the sample and can only be performed in the laboratory by skilled personnel. In this study, hyperspectral image data were used to construct a machine learning (ML) model to discriminate between freshly refrigerated, long-term refrigerated, and thawed beef meat samples. With four pre-processing methods, a total of five datasets were prepared to construct an ML model. The PLS-DA and SVM techniques were used to construct the models, and the performance was highest for the SVM model applying scatter correction and the RBF kernel function. These results suggest that it is possible to construct a prediction model to distinguish between fresh and non-fresh meat using the spectra obtained by purifying hyperspectral image data cubes, which can be a rapid and non-invasive method for routine analyses of the meat storage state. Full article

(This article belongs to the Topic Applications of Big Data and Machine Learning in Smart Agriculture)

► Show Figures

Figure 1

21 pages, 9929 KiB

Open AccessArticle

Design and Testing of a Self-Propelled Dandelion Seed Harvester

by Zhe Qu, Qi Lu, Haihao Shao, Long Liu, Xiuping Wang and Zhijun Lv

Agriculture 2023, 13(4), 917; https://doi.org/10.3390/agriculture13040917 - 21 Apr 2023

Cited by 2 | Viewed by 1683

Abstract

At present, there are few harvesters for dandelion (Taraxacum mongolicum) seeds, which limits the large-area planting of dandelion. Furthermore, manual harvesting is characterized by huge labor intensity, low efficiency, and high costs. Combining the material characteristics of dandelion plants and seeds [...] Read more.

At present, there are few harvesters for dandelion (Taraxacum mongolicum) seeds, which limits the large-area planting of dandelion. Furthermore, manual harvesting is characterized by huge labor intensity, low efficiency, and high costs. Combining the material characteristics of dandelion plants and seeds with agronomic requirements for harvesting dandelion seeds, a self-propelled dandelion seed harvester was designed. The harvester is mainly composed of collection devices, separation devices, transmission devices, and a rack. It can facilitate seed collection from plants, seed transportation, and seed–pappus separation in one operation. The collection and separation processes of dandelion seeds were studied to ascertain the main factors that affect the collection rate. Then, the collection and separation devices were designed, and their parameters were analyzed. Taking the forward speed, wind velocity of blowers, and rate of rotation of the drum as test factors and the collection rate as the evaluation index, quadratic regression orthogonal rotating field tests were performed. In this way, the optimal combination of operation parameters was determined: the collection rate is optimal when the forward speed is 0.8 m·s⁻¹, the air velocity from the blowers is 1.63 m·s⁻¹, and the rate of rotation of the drum is 419 rpm. Field test results showed that a favorable harvesting effect was achieved after operation of the harvester, and only small amounts of dandelion seeds remained unharvested. Under the optimal parameter combination, the collection rate reached 89.1%, which could meet requirements for practical field harvesting of dandelion seeds. The test results satisfy the design requirement. Full article

(This article belongs to the Special Issue 'Eyes', 'Brain', 'Feet' and 'Hands' of Efficient Harvesting Machinery)

► Show Figures

Figure 1

12 pages, 2851 KiB

Open AccessArticle

Non-Destructive Appraisal of Macro- and Micronutrients in Persimmon Leaves Using Vis/NIR Hyperspectral Imaging

by Maylin Acosta, Isabel Rodríguez-Carretero, José Blasco, José Miguel de Paz and Ana Quiñones

Agriculture 2023, 13(4), 916; https://doi.org/10.3390/agriculture13040916 - 21 Apr 2023

Cited by 3 | Viewed by 3273

Abstract

Visible and near-infrared (Vis/NIR) hyperspectral imaging (HSI) was used for rapid and non-destructive determination of macro- and micronutrient contents in persimmon leaves. Hyperspectral images of 687 leaves were acquired in the 500–980 nm range over 6 months, covering a complete vegetative cycle. The [...] Read more.

Visible and near-infrared (Vis/NIR) hyperspectral imaging (HSI) was used for rapid and non-destructive determination of macro- and micronutrient contents in persimmon leaves. Hyperspectral images of 687 leaves were acquired in the 500–980 nm range over 6 months, covering a complete vegetative cycle. The average reflectance spectrum of each leaf was extracted, and foliar ionomic analysis was used as a reference method to determine the actual concentration of the nutrients in the leaves. Analyses were performed via emission spectrometry (ICP-OES) for macro- and micronutrients after microwave digestion and using the Kjeldahl method to quantify nitrogen. Partial least square regression (PLS-R) was used to predict the nutrient concentration based on spectral data from the leaf using actual values of each element as predictor variables. Several methods were used to pre-process the spectra, including Savitzky–Golay (SG) smoothing, standard normal variate (SNV) and first (1D) and second derivatives (2D). Seventy-five percent of the samples were used to calibrate and validate the model by cross-validation, whereas the remaining twenty-five % were used as an independent test set. The best performance of the models for the test set achieved an R² = 0.80 for nitrogen. Results were also satisfactory for phosphorous, calcium, magnesium and boron, with determination coefficient R² values of 0.63, 0.66, 0.58 and 0.69, respectively. For the other nutrients, lower prediction rates were attained (R² = 0.48 for potassium, R² = 0.38 for iron, R² = 0.24 for copper, R² = 0.23 for zinc and R² = 0.22 for manganese). The variable importance in projection (VIP) was used to extract the most influential bands for the best-predicted nutrients, which were N, K and B. Full article

(This article belongs to the Special Issue Applications of Data Analysis in Agriculture)

► Show Figures

Figure 1

18 pages, 10064 KiB

Open AccessArticle

Fate of Copper in Saline–Alkali Soil with Long-Term Application of Biogas Residue

by Binhao Liu, Shengxiao Wang, Pengcheng Dong, Xinzhe Zhang, Long Zhang, Chen Chen, Xihui Xu, Yan Xia, Zhenguo Shen, Liang Shi and Yahua Chen

Agriculture 2023, 13(4), 915; https://doi.org/10.3390/agriculture13040915 - 21 Apr 2023

Viewed by 1395

Abstract

The retention of copper (Cu) in saline–alkali soil (SAS) during long-term application of biogas residue (BR) with a high concentration of Cu raises concerns. In this work, the fate of Cu was detected using adsorption isotherms, scanning electron microscope—energy dispersive spectrometer, Fourier transform [...] Read more.

The retention of copper (Cu) in saline–alkali soil (SAS) during long-term application of biogas residue (BR) with a high concentration of Cu raises concerns. In this work, the fate of Cu was detected using adsorption isotherms, scanning electron microscope—energy dispersive spectrometer, Fourier transform infrared spectrometer, X-ray diffraction, isothermal titration calorimetry, X-ray photoelectron spectroscopy, and microzone X-ray fluorescence spectrometer. The results showed that the main groups for Cu adsorption by SAS and BR were carboxyl, hydroxyl, amide and amine. The adsorption of Cu by the carboxyl group was entropy–enthalpy co-driven (|ΔH| < |TΔS|, ΔH < 0). The adsorption of Cu by the amine group was entropy-driven (|ΔH| > |TΔS|, ΔH > 0). The adsorption of Cu on the SAS and BR was achieved by organic matter rather than minerals. The degradation of BR in the SAS increases the content of Cu adsorption groups such as carboxyl and amine groups, and Cu was adsorbed on the surface or inside SAS through organic groups. This study provides further theoretical support for the application of BR in SAS. Full article

(This article belongs to the Special Issue Effects of Plant-Microbe Interactions on Phyto- and Bio-Remediation Capacity)

► Show Figures

Figure 1

18 pages, 7788 KiB

Open AccessArticle

An Improved Mask RCNN Model for Segmentation of ‘Kyoho’ (Vitis labruscana) Grape Bunch and Detection of Its Maturity Level

by Yane Li, Ying Wang, Dayu Xu, Jiaojiao Zhang and Jun Wen

Agriculture 2023, 13(4), 914; https://doi.org/10.3390/agriculture13040914 - 21 Apr 2023

Cited by 3 | Viewed by 1593

Abstract

The ‘Kyoho’ (Vitis labruscana) grape is one of the mainly fresh fruits; it is important to accurately segment the grape bunch and to detect its maturity level for the construction of an intelligent grape orchard. Grapes in the natural environment have [...] Read more.

The ‘Kyoho’ (Vitis labruscana) grape is one of the mainly fresh fruits; it is important to accurately segment the grape bunch and to detect its maturity level for the construction of an intelligent grape orchard. Grapes in the natural environment have different shapes, occlusion, complex backgrounds, and varying illumination; this leads to poor accuracy in grape maturity detection. In this paper, an improved Mask RCNN-based algorithm was proposed by adding attention mechanism modules to establish a grape bunch segmentation and maturity level detection model. The dataset had 656 grape bunches of different backgrounds, acquired from a grape growing environment of natural conditions. This dataset was divided into four groups according to maturity level. In this study, we first compared different grape bunch segmentation and maturity level detection models established with YoloV3, Solov2, Yolact, and Mask RCNN to select the backbone network. By comparing the performances of the different models established with these methods, Mask RCNN was selected as the backbone network. Then, three different attention mechanism modules, including squeeze-and-excitation attention (SE), the convolutional block attention module (CBAM), and coordinate attention (CA), were introduced to the backbone network of the ResNet50/101 in Mask RCNN, respectively. The results showed that the mean average precision (mAP) and mAP_0.75 and the average accuracy of the model established with ResNet101 + CA reached 0.934, 0.891, and 0.944, which were 6.1%, 4.4%, and 9.4% higher than the ResNet101-based model, respectively. The error rate of this model was 5.6%, which was less than the ResNet101-based model. In addition, we compared the performances of the models established with MASK RCNN, adding different attention mechanism modules. The results showed that the mAP and mAP_0.75 and the accuracy for the Mask RCNN50/101 + CA-based model were higher than those of the Mask RCNN50/101 + SE- and Mask RCNN50/101 + CBAM-based models. Furthermore, the performances of the models constructed with different network layers of ResNet50- and ResNet101-based attention mechanism modules in a combination method were compared. The results showed that the performance of the ResNet101-based combination with CA model was better than the ResNet50-based combination with CA model. The results showed that the proposed model of Mask RCNN ResNet101 + CA was good for capturing the features of a grape bunch. The proposed model has practical significance for the segmentation of grape bunches and the evaluation of the grape maturity level, which contributes to the construction of intelligent vineyards. Full article

(This article belongs to the Section Digital Agriculture)

► Show Figures

Figure 1

12 pages, 871 KiB

Open AccessArticle

From Waste to Resources: Sewage Sludges from the Citrus Processing Industry to Improve Soil Fertility and Performance of Lettuce (Lactuca sativa L.)

by Caterina Lucia, Daniela Pampinella, Eristanna Palazzolo, Luigi Badalucco and Vito Armando Laudicina

Agriculture 2023, 13(4), 913; https://doi.org/10.3390/agriculture13040913 - 21 Apr 2023

Cited by 2 | Viewed by 1426

Abstract

The citrus industry produces a large number of sludges as a consequence of citrus wastewater treatment. The correct disposal of citrus sewage sludges (CSSs) has been attempted using anaerobic digestion, aerobic digestion, and lime stabilization. However, since CSSs hold nitrogen, phosphorus, and other [...] Read more.

The citrus industry produces a large number of sludges as a consequence of citrus wastewater treatment. The correct disposal of citrus sewage sludges (CSSs) has been attempted using anaerobic digestion, aerobic digestion, and lime stabilization. However, since CSSs hold nitrogen, phosphorus, and other macronutrients required by crops, in line with the circular economy principles, they could be utilized for agricultural purposes, such as organic fertilizer. The aim of this study was to assess the effect of CSSs supplied at different doses on soil fertility and lettuce performance. To this end, a pot experiment was established. The soil was amended with CSSs at three different concentrations (2.5, 5, 10 t ha⁻¹). After 46 days of lettuce growth, the experiment was stopped, and soils and plants were analyzed. Soil amended with CSSs showed an increase in total organic C ranging from 7% to 11%. Additionally, available P increased but only at the highest CSS dose. The addition of CSSs affected the biochemical properties of soil, but a univocal trend related to the number of CSSs applied was not found. Microbial biomass C increased only with the highest dose of CSS applied, while the metabolic quotient (qCO₂) decreased. Such a positive effect on soil fertility and soil microorganisms, in turn, lead to an increase in lettuce biomass. Moreover, results indicated that following CSS addition, lettuce crops adsorbed more N in leaves than in roots, whereas P, Ca, Mg, K, and Na showed an opposite pattern and increased more consistently in roots. In conclusion, amendment with CSSs enhances soil fertility by increasing, regardless of CSS dose, total organic C, and, at the highest dose, P availability and microbial biomass C. Such improvement in soil fertility, in turn, increases lettuce biomass production without affecting its quality, i.e., alteration of the (K + Na)/(Ca + Mg) ratio. Full article

(This article belongs to the Special Issue Soil Quality and Crop Nutrition)

► Show Figures

Figure 1

19 pages, 4420 KiB

Open AccessArticle

The Effect of Glutamine as Feed Additive on Selected Parameters of the Nonspecific Immune Response in Pigs

by Łukasz S. Jarosz, Ewa Tomaszewska, Agnieszka Marek, Marcin Hejdysz, Artur Burmańczuk, Artur Ciszewski, Sebastian Nowaczewski, Zbigniew Grądzki, Maciej Batorski, Małgorzata Świątkiewicz and Anna Rysiak

Agriculture 2023, 13(4), 912; https://doi.org/10.3390/agriculture13040912 - 21 Apr 2023

Viewed by 1311

Abstract

The use of feed additives containing glutamine can influence the growth and development of piglets during the weaning period. The aim of this study was to determine the effect of feed supplementation with 0.5% L-glutamine on selected parameters of the nonspecific immune response [...] Read more.

The use of feed additives containing glutamine can influence the growth and development of piglets during the weaning period. The aim of this study was to determine the effect of feed supplementation with 0.5% L-glutamine on selected parameters of the nonspecific immune response of pigs. The research was carried out on 60 pigs (Polish Large White × Polish Landrace), from 28 days of age to slaughter. The obtained results showed an increased percentage of phagocytic cells (monocytes and granulocytes) and oxygen blast cells in pigs between 28 and 70 days of age, proving that non-specific immune mechanisms were stimulated, which contributed to the improvement of the processes of antigen elimination from the body. The increase in the percentage of cells expressing SWC3, CD11b/CD18⁺, CD14⁺ and CD14⁺CD16⁺ molecules on granulocytes and monocytes during this period resulted in the enhancement of the host defense mechanisms by stimulating phagocytosis and enhancing the mechanisms of a non-specific immune response. The high concentration of TNF-α and IL-1β as well as Il-10 in the experimental group indicates the cellular phenotype of the Th1-type response, and the maintenance of the immune balance between the pro-inflammatory and anti-inflammatory responses and ensuring the homeostasis of the organism. Full article

(This article belongs to the Special Issue Effects of Nutrition Quality on the Health, Productivity, and Performance of Livestock)

► Show Figures

Figure 1

4 pages, 210 KiB

Open AccessEditorial

Advanced Research of Rhizosphere Microbial Activity

by Tibor Szili-Kovács and Tünde Takács

Agriculture 2023, 13(4), 911; https://doi.org/10.3390/agriculture13040911 - 21 Apr 2023

Cited by 1 | Viewed by 1306

Abstract

Soils are generally considered a complex and largely unexplored vital “black box” with thousands of microorganism taxa in their networks [...] Full article

(This article belongs to the Special Issue Advanced Research of Rhizosphere Microbial Activity)

20 pages, 932 KiB

Open AccessArticle

The YieldWise Approach to Post-Harvest Loss Reduction: Creating Market-Driven Supply Chains to Support Sustained Technology Adoption

by Steven Sonka, Hyeonsuh Lee and Sonali Shah

Agriculture 2023, 13(4), 910; https://doi.org/10.3390/agriculture13040910 - 21 Apr 2023

Cited by 1 | Viewed by 1818

Abstract

Excessively high levels of post-harvest loss often are a feature of agricultural systems dominated by small-holder farmers. However, this situation is something of a paradox, as technologies exist that have been shown in field demonstrations to substantially reduce post-harvest loss. What explains this [...] Read more.

Excessively high levels of post-harvest loss often are a feature of agricultural systems dominated by small-holder farmers. However, this situation is something of a paradox, as technologies exist that have been shown in field demonstrations to substantially reduce post-harvest loss. What explains this paradox? Building on insights derived from the Rockefeller Foundation’s YieldWise Initiative, this article proposes that while reducing post-harvest loss generally does require technology adoption by small-holder farmers, market-driven supply chains are essential to the sustained use of those technologies. We illustrate this approach using in-depth interview data collected from the YieldWise participants belonging to the Iringa Hope Cooperative in Tanzania. Data on the benefits and challenges of such an approach are provided from the perspective of the small-holder farmer. In addition, we model the economic benefits associated with this approach. Full article

(This article belongs to the Special Issue Recent Innovations in Post-harvest Preservation and Protection of Agricultural Products—Series II)

► Show Figures

Figure 1

28 pages, 3572 KiB

Open AccessReview

Recovering, Stabilizing, and Reusing Nitrogen and Carbon from Nutrient-Containing Liquid Waste as Ammonium Carbonate Fertilizer

by Mariana Brondi, Mohamed Eisa, Ricardo Bortoletto-Santos, Donata Drapanauskaite, Tara Reddington, Clinton Williams, Caue Ribeiro and Jonas Baltrusaitis

Agriculture 2023, 13(4), 909; https://doi.org/10.3390/agriculture13040909 - 21 Apr 2023

Cited by 7 | Viewed by 4772

Abstract

Ammonium carbonates are a group of fertilizer materials that include ammonium bicarbonate, ammonium carbonate hydrate, and ammonium carbamate. They can be synthesized from diverse nutrient-bearing liquid waste streams but are unstable in a moist environment. While extensively utilized several decades ago, their use [...] Read more.

Ammonium carbonates are a group of fertilizer materials that include ammonium bicarbonate, ammonium carbonate hydrate, and ammonium carbamate. They can be synthesized from diverse nutrient-bearing liquid waste streams but are unstable in a moist environment. While extensively utilized several decades ago, their use gradually decreased in favor of large-scale, facility-synthesized urea fertilizers. The emergence of sustainable agriculture, however, necessitates the recovery and reuse of nutrients using conventional feedstocks, such as natural gas and air-derived nitrogen, and nutrient-containing biogenic waste streams. To this extent, anaerobic digestion liquid presents a convenient source of solid nitrogen and carbon to produce solid fertilizers, since no significant chemical transformations are needed as nitrogen is already present as an ammonium ion. This review describes detailed examples of such feedstocks and the methods required to concentrate and crystallize solid ammonium carbonates. The technologies currently proposed or utilized to stabilize ammonium carbonate materials in the environment are described in detail. Finally, the agricultural efficiency of these materials as nitrogen and carbon source is also described. Full article

(This article belongs to the Topic Low Carbon Economy and Sustainable Development)

► Show Figures

Figure 1

16 pages, 663 KiB

Open AccessArticle

Influence of Conservation Agriculture on Durum Wheat Grain, Dough Texture Profile and Pasta Quality in a Mediterranean Region

by Imene Kerbouai, Dorra Sfayhi, Khaled Sassi, Hatem Cheikh M’hamed, Houda Jenfaoui, Jouhaina Riahi, Slim Arfaoui, Moncef Chouaibi and Hanen Ben Ismail

Agriculture 2023, 13(4), 908; https://doi.org/10.3390/agriculture13040908 - 21 Apr 2023

Cited by 1 | Viewed by 1935

Abstract

There is a growing interest in the Mediterranean regions to switch to conservation agriculture (CA) to address climate change and soil deterioration issues. The novelty of this study lies in the quality of the supply chain, from the raw material (durum wheat grain) [...] Read more.

There is a growing interest in the Mediterranean regions to switch to conservation agriculture (CA) to address climate change and soil deterioration issues. The novelty of this study lies in the quality of the supply chain, from the raw material (durum wheat grain) to the ready-to-sell product (spaghetti), under long-term CA, and using two varieties over two years of study. This study aims to investigate the impact of two soil management systems (SM) (CA after 10/11 (since 2009–2010) years switching vs. conventional tillage (CT)) on grain quality, dough texture profile, and pasta quality of two Tunisian durum wheat varieties (Karim and Monastir) in a 2-year-long experiment (2019 and 2020). The results showed that the SM had a significant impact on the grain quality in both years in terms of protein content and wet gluten, which were, respectively, lower under CA (11.92% vs. 11.15% for protein content) and (18.75% vs. 17.68% for wet gluten) in the wet year. These parameters increased in the dry year but they were higher under CA (15.70% vs. 14.42 ± 0.94% for protein content) and (26.00% vs. 23.20% for wet gluten). These results have, in turn, affected the dough quality (springiness, chewiness, and cohesiveness) and pasta cooking time and decreased the pasta cooking loss and water absorption index. In terms of the variety (V) factor, “Karim” variety in the dry year had a higher protein content and better dough quality than “Monastir” variety, and it reduced the pasta cooking time. In addition, the pasta yellow index (b*) from grains grown under CA was always higher than those in the CT system (23.99 vs. 19.72% and 25.24 vs. 22.19% in 2019 and 2020, respectively). The interaction between SM and V was significant in both years only for the dough hardness and pasta b* parameters. In conclusion, long-term CA may be a crucial solution in the dry season to promote food quality and achieve sustainable agriculture goals. Full article

(This article belongs to the Section Agricultural Product Quality and Safety)

► Show Figures

Figure 1

23 pages, 3409 KiB

Open AccessArticle

Analysis of the Spatio-Temporal Evolution, Influencing Factors, and Spillover Effects of the Urban–Rural Income Gap in Chongqing Municipality, China

by Shiqin Yang, Zisheng Yang, Renyi Yang and Xueli Cai

Agriculture 2023, 13(4), 907; https://doi.org/10.3390/agriculture13040907 - 20 Apr 2023

Cited by 2 | Viewed by 1481

Abstract

In addition to being necessary for the stability, coordination, and sustainable growth of the national economy, narrowing the urban–rural income gap is also an “Important national matter” for the long-term security of the nation. “Big mountain areas, big cities, big reservoir areas, big [...] Read more.

In addition to being necessary for the stability, coordination, and sustainable growth of the national economy, narrowing the urban–rural income gap is also an “Important national matter” for the long-term security of the nation. “Big mountain areas, big cities, big reservoir areas, big rural areas, and ethnic areas” are all present in the municipality of Chongqing. All of the poverty-stricken counties have been lifted out of poverty, despite the promotion of targeted poverty alleviation and other policies, significant urban–rural income gaps remain. In view of the current research, there has been no in-depth discussion on the correlation between urban and rural income gap and poverty levels in various regions, and there has been no in-depth discussion on the spatial correlation and spillover effects of various influencing factors. This paper employs panel data from 2010 to 2021 for 37 counties in Chongqing; based on an analysis of the characteristics of the urban–rural income gap’s spatial pattern and spatio-temporal evolution, it classifies each county (city and district) as either a non-poverty or poverty-stricken county and uses spatial econometric models to conduct an in-depth study of the influencing factors and spillover effects of the urban–rural income gap in Chongqing. The outcomes of our analysis of the influencing factors reveal that the level of fixed assets investment, the per capita spending of public funds, the proportion of rural employees, the proportion of grain sowing, the amount of agricultural fertilizer applied per unit area, the proportion of real estate development investment, and population density variables are important causes of the URIG in Chongqing. The spillover effects of these factors vary between poverty-stricken and non-poverty-stricken counties. This paper aims to provide reference to policymakers to design measures to narrow the urban–rural income gap and advance the urban–rural coordinated development strategy on the basis of a thorough examination of the spatial and temporal evolution, influencing variables, and spillover effects of the urban–rural income gap in Chongqing. Full article

(This article belongs to the Special Issue Agricultural Development Strategies for Less-Favoured Areas)

► Show Figures

Figure 1

19 pages, 5060 KiB

Open AccessArticle

Deep Learning Application for Crop Classification via Multi-Temporal Remote Sensing Images

by Qianjing Li, Jia Tian and Qingjiu Tian

Agriculture 2023, 13(4), 906; https://doi.org/10.3390/agriculture13040906 - 20 Apr 2023

Cited by 5 | Viewed by 3620

Abstract

The combination of multi-temporal images and deep learning is an efficient way to obtain accurate crop distributions and so has drawn increasing attention. However, few studies have compared deep learning models with different architectures, so it remains unclear how a deep learning model [...] Read more.

The combination of multi-temporal images and deep learning is an efficient way to obtain accurate crop distributions and so has drawn increasing attention. However, few studies have compared deep learning models with different architectures, so it remains unclear how a deep learning model should be selected for multi-temporal crop classification, and the best possible accuracy is. To address this issue, the present work compares and analyzes a crop classification application based on deep learning models and different time-series data to exploit the possibility of improving crop classification accuracy. Using Multi-temporal Sentinel-2 images as source data, time-series classification datasets are constructed based on vegetation indexes (VIs) and spectral stacking, respectively, following which we compare and evaluate the crop classification application based on time-series datasets and five deep learning architectures: (1) one-dimensional convolutional neural networks (1D-CNNs), (2) long short-term memory (LSTM), (3) two-dimensional-CNNs (2D-CNNs), (4) three-dimensional-CNNs (3D-CNNs), and (5) two-dimensional convolutional LSTM (ConvLSTM2D). The results show that the accuracy of both 1D-CNN (92.5%) and LSTM (93.25%) is higher than that of random forest (~ 91%) when using a single temporal feature as input. The 2D-CNN model integrates temporal and spatial information and is slightly more accurate (94.76%), but fails to fully utilize its multi-spectral features. The accuracy of 1D-CNN and LSTM models integrated with temporal and multi-spectral features is 96.94% and 96.84%, respectively. However, neither model can extract spatial information. The accuracy of 3D-CNN and ConvLSTM2D models is 97.43% and 97.25%, respectively. The experimental results show limited accuracy for crop classification based on single temporal features, whereas the combination of temporal features with multi-spectral or spatial information significantly improves classification accuracy. The 3D-CNN and ConvLSTM2D models are thus the best deep learning architectures for multi-temporal crop classification. However, the ConvLSTM architecture combining recurrent neural networks and CNNs should be further developed for multi-temporal image crop classification. Full article

(This article belongs to the Special Issue Novel Applications of Optical Sensors and Machine Learning in Agricultural Monitoring)

► Show Figures

Figure 1

18 pages, 6997 KiB

Open AccessArticle

Design of 4UM-120D Electric Leafy Vegetable Harvester Cutter Height off the Ground Automatic Control System Based on Incremental PID

by Wenming Chen, Lianglong Hu, Gongpu Wang, Jianning Yuan, Guocheng Bao, Haiyang Shen, Wen Wu and Zicheng Yin

Agriculture 2023, 13(4), 905; https://doi.org/10.3390/agriculture13040905 - 20 Apr 2023

Cited by 2 | Viewed by 1511

Abstract

In this study, a 4UM-120D electric leafy vegetable harvester was employed as the research object. An automatic control system was created to maintain the cutter’s height above the ground within ±2% of the desired value. The intention was to reduce the operators’ work [...] Read more.

In this study, a 4UM-120D electric leafy vegetable harvester was employed as the research object. An automatic control system was created to maintain the cutter’s height above the ground within ±2% of the desired value. The intention was to reduce the operators’ work intensity while improving the leafy vegetable harvester’s working quality. The automatic control system for the cutter height from the ground was explained, along with its structure and operating philosophy. MATLAB was used to establish the two-phase hybrid stepper motor’s mathematical electrical equation and mechanical equation models. An analysis was carried out on the fundamentals and differences between position PID and incremental PID control algorithms. Utilizing incremental PID in combination, the control strategy for the harvester cutter height from the ground was built, and an automatic control system was produced under the corresponding control strategy. The stability, accuracy, and rapidity of the automatic control system of the cutter height from the ground under the incremental PID control strategy were analyzed by simulating different actual working conditions with MATLAB/Simulink and taking the steady-state transition time as the evaluation index. The test results show that when the deviation between the current value and the set value was greater than 2%—that is, when the harvester was in the condition of suddenly crossing the ditch or suddenly climbing the slope—the automatic control system based on the incremental PID control strategy had a good dynamic response performance and stability. This resulted in the automatic control function of the harvester cutter height off the ground being achieved. When the rotation angle PID control algorithm’s proportional coefficient is Kp = 4.665, the rotation speed PID control algorithm’s proportional coefficient is Kp = 5.65 and its integral coefficient is Ki = 3.86, and the current PID control algorithm’s proportional coefficient is Kp = 0.5455 and its integral coefficient is Ki = 30.4578. The harvester abruptly crossed a ditch while operating steadily, and the automatic control system’s steady-state transition time for the height of the cutter off the ground was 1.0811 s. The harvester abruptly climbed a slope while operating steadily, and the automatic control system’s steady-state transition time for the height of the cutter off the ground was 1.1185 s. Data from the field tests revealed a degree of reliability in the simulation test results. The study offered a strategy for raising the harvester quality for leafy vegetables while lowering the operator workload. Full article

(This article belongs to the Special Issue Intelligent Systems in Precision Agriculture: Data, Applications and Techniques)

► Show Figures

Figure 1

23 pages, 1044 KiB

Open AccessArticle

Does Digital Technology Application Promote Carbon Emission Efficiency in Dairy Farms? Evidence from China

by Chenyang Liu, Xinyao Wang, Ziming Bai, Hongye Wang and Cuixia Li

Agriculture 2023, 13(4), 904; https://doi.org/10.3390/agriculture13040904 - 20 Apr 2023

Cited by 4 | Viewed by 1621

Abstract

The implementation of digital technology has become paramount to facilitating green and low-carbon development in dairy farms amidst the advent of digital agriculture and low-carbon agriculture. This study examined the impact of digital technology implementation on the carbon emission efficiency of Chinese dairy [...] Read more.

The implementation of digital technology has become paramount to facilitating green and low-carbon development in dairy farms amidst the advent of digital agriculture and low-carbon agriculture. This study examined the impact of digital technology implementation on the carbon emission efficiency of Chinese dairy farms via an assessment of micro-survey data, incorporating an Undesirable Outputs-SBM model, a Tobit model, the propensity score matching technique, a quantile regression model, and an instrumental variable approach. This study examined the potential moderating influence of environmental regulations on digital technology applications and the carbon emission efficiency of dairy farms. The findings of the research indicate that the implementation of digital technology had a considerable beneficial consequence on the carbon emission proficiency of dairy farms. The statistical significance level of the mean treatment effect was 0.1161, with the most profound influence of precision feeding digital technology on the carbon emission efficiency in dairy farms. The application of digital technology has a more pronounced effect on dairy farms with lower levels of carbon emission efficiency compared to those with medium and high levels of carbon emission efficiency. The application of digital technology toward the carbon emission efficiency of dairy farms is positively moderated by environmental regulations. Finally, this paper puts forward some specific policy recommendations to achieve the strategic goal of low carbon and efficient development in dairy farms through the application of digital technology, which enriches the existing research on carbon emission reduction in dairy farms from theoretical and practical aspects. Full article

(This article belongs to the Special Issue Greenhouse Gas Emissions in Agricultural System and Green Infrastructures: Mechanisms and Mitigation Measures)

► Show Figures

Figure 1

16 pages, 3197 KiB

Open AccessArticle

Evaluating the Performance and Opportunity Cost of a Smart-Sensed Automated Irrigation System for Water-Saving Rice Cultivation in Temperate Australia

by Matthew Champness, Leigh Vial, Carlos Ballester and John Hornbuckle

Agriculture 2023, 13(4), 903; https://doi.org/10.3390/agriculture13040903 - 20 Apr 2023

Cited by 2 | Viewed by 2017

Abstract

Irrigated rice is the largest user of precious global water reserves. Adoption of water-saving irrigation practices is limited by the associated increased labor demand compared to flooded rice cultivation. Automated gravity surface irrigation systems have shown the potential to deliver significant labor savings [...] Read more.

Irrigated rice is the largest user of precious global water reserves. Adoption of water-saving irrigation practices is limited by the associated increased labor demand compared to flooded rice cultivation. Automated gravity surface irrigation systems have shown the potential to deliver significant labor savings in traditional flooded rice; however, widespread adoption does not seem apparent. Furthermore, previously designed systems have not been capable of irrigation control during both ponded and non-ponded periods. This study aimed to evaluate the performance of an automated irrigation system for rice with features not previously developed, provide direction for future systems and analyze the opportunity cost (the value of other on- or off-farm activities that could be conducted with that time) of time associated with automated irrigation. The automated irrigation system was found to successfully control 23–31 flush-irrigation events per bay per season in a 9-bay border-check aerobic rice field for 2 seasons. In addition, successful water control was achieved in a traditional drill-sown field with 4 flush irrigations followed by 15 weeks of permanent flooding. Labor savings of 82–88% during the flush-irrigation events and 57% during the ponding period were achieved with automation when compared to manual irrigation. However, the opportunity cost of the saved time was found to comprise the greatest benefit. Changing the analysis from using a flat “cash” cost of time to using opportunity cost of time reduced the payback period from seven to four years at the traditional ponded-rice site. In the more labor-intensive aerobic rice site, the payback period was reduced from three years to one year when accounting for the opportunity cost of time as opposed to only the direct costs. Whilst the payback period is site-dependent and cultivation method-dependent, these case studies demonstrate that automated gravity surface irrigation can enable novel water-saving practices in rice and provide substantial economic benefits. Full article

(This article belongs to the Special Issue The Use and Management of Agricultural Irrigation Systems and Technologies)

► Show Figures

Figure 1

16 pages, 3531 KiB

Open AccessArticle

Characterizing a Year-Round Particulate Matter Concentration and Variation under Different Environmental Controls in a Naturally Ventilated Dairy Barn

by Yujian Lu, Xiao Yang, Lei E, Zhiwei Fang, Yongzhen Li, Chao Liang, Zhengxiang Shi and Chaoyuan Wang

Agriculture 2023, 13(4), 902; https://doi.org/10.3390/agriculture13040902 - 19 Apr 2023

Cited by 3 | Viewed by 1256

Abstract

A mixing fan and spraying system is commonly used to control the indoor environment of naturally ventilated dairy barns worldwide. However, its impact on particulate matter (PM) concentration and variation is still unclear due to the lack of year-round field data. To systematically [...] Read more.

A mixing fan and spraying system is commonly used to control the indoor environment of naturally ventilated dairy barns worldwide. However, its impact on particulate matter (PM) concentration and variation is still unclear due to the lack of year-round field data. To systematically characterize the PM dynamics under different environmental controls (namely, EC1: No Fans and No Spraying; EC2: Fans; EC3: Fans and Spraying), a year-round continuous monitoring of PM less than 2.5 μm in aerodynamic diameter (PM_2.5) and total suspended particle (TSP) concentrations, as well as indoor environmental factors, was carried out inside a naturally ventilated dairy barn using an IoT-based sensor monitoring network. Results showed that the hourly mean TSP and PM_2.5 concentrations were 94.7 μg m⁻³ and 49.8 μg m⁻³, respectively. EC2 had a higher TSP content (116.6 μg m⁻³) than EC1 (98.0 μg m⁻³) and EC3 (81.9 μg m⁻³). EC1 had the greatest PM_2.5 concentration (57.1 μg m⁻³), followed by EC2 (48.3 μg m⁻³) and EC3 (44.7 μg m⁻³). EC1 showed clear TSP and PM_2.5 fluctuations during the daily operations at 07:00 to 08:00 and 18:00 to 19:00, while irregular peaks in EC2 and a relatively steady diurnal variation in EC3 were found. Daily Tsp concentrations in the three ECs did not exceed 300 μg m⁻³. However, 17.8%, 11.5%, and 4.8% of the observed days in EC1, EC2, and EC3 had daily mean PM_2.5 concentrations above the healthy threshold (75 μg m⁻³), mostly from 07:00 to 08:00 and 22:00–07:00. In conclusion, the mixing fan and spraying system had significant effects on PM concentration and variation, and more protection procedures should be taken for farm workers to prevent long-term health risk exposure, to EC1 in particular. Full article

(This article belongs to the Section Farm Animal Production)

► Show Figures

Figure 1

18 pages, 1785 KiB

Open AccessReview

Environmental and Agronomical Factors Limiting Differences in Potato Yielding between Organic and Conventional Production System

by Krystyna Zarzyńska, Cezary Trawczyński and Milena Pietraszko

Agriculture 2023, 13(4), 901; https://doi.org/10.3390/agriculture13040901 - 19 Apr 2023

Cited by 1 | Viewed by 2122

Abstract

This paper presents the results of the authors’ own research and literature research on the impact of selected environmental and agronomical factors on the yield of potato grown under the organic system and the possibility of increasing the yield. The results are based [...] Read more.

This paper presents the results of the authors’ own research and literature research on the impact of selected environmental and agronomical factors on the yield of potato grown under the organic system and the possibility of increasing the yield. The results are based on research conducted for several years at the Institute of Plant Breeding and Acclimatization in Jadwisin, Poland. The influence of factors such as soil quality and climatic conditions, selection of varieties, seed potato preparation, irrigation of plantations, complementary fertilization, and protection against the late blight was described. The aim of this work was to indicate which of these factors affect the yield increase and to what extent. It was stated that it is possible to increase the yield of potato tubers grown under the organic system through all of the proposed treatments. In our studies, using drip irrigation and complementary fertilization had the greatest effect (25.5% and 19%, respectively). Seed potato presprouting had a smaller influence (4.3%) on the final tuber yield. In the years with high pressure of the pathogen Phytophthora infestans, the selection of cultivars with high resistance was very important. Most of the agronomical treatments not only improved the total yield of tubers, but also increased the share of tubers with a larger diameter. A very high variability of potato yielding depending on weather conditions and a selection of cultivars was emphasized. We can say that a proper agronomical practice carried out on an organic potato plantation can largely eliminate the yielding gap between a conventional and an organic system. Full article

(This article belongs to the Special Issue Advances in Organic Agriculture—Decreasing Yield Gap via Optimising Cultivation Methods and Agrarian Policy)

► Show Figures

Figure 1

15 pages, 1408 KiB

Open AccessArticle

The Effect of Applied Biostimulants on the Yielding of Three Non-Genetically Modified Soybean Cultivars

by Katarzyna Rymuza, Elżbieta Radzka and Joanna Cała

Agriculture 2023, 13(4), 900; https://doi.org/10.3390/agriculture13040900 - 19 Apr 2023

Cited by 3 | Viewed by 1612

Abstract

Background: Soybean is one of major crop plants cultivated in numerous parts of the world, which is due to an increasing demand for plant protein. Both in Europe and Poland, much attention is paid to enhancing the production of their own fodder protein, [...] Read more.

Background: Soybean is one of major crop plants cultivated in numerous parts of the world, which is due to an increasing demand for plant protein. Both in Europe and Poland, much attention is paid to enhancing the production of their own fodder protein, as to reduce the import of soybean meal produced from genetically modified plants. Climate warming and breeding progress have made it possible to grow soybeans in central Europe. The yield potential of plants, including soybeans, can be enhanced by an application of biostimulants, which alleviate negative effects of stresses disturbing the life processes of plants. The objective of the present work was to evaluate, under the climatic conditions of central-eastern Poland, the yielding of three non-modified soybean cultivars treated with biostimulants. Methods: A field experiment was conducted in the years 2017–2019 in eastern Poland (central Europe). The soil of the experimental field belonged to the Haplic Luvisol group. The experimental factors included three non-GMO soybean cultivars (Abelina, Merlin, and SG Anser) and two biostimulants (Asahi SL and Improver). Results: Soybean seed yields were affected by the climatic conditions during the growing season, cultivars, and biostimulant applications. Regardless of cultivars and biostimulants, the highest yields were produced by plants grown in 2017 (on average, 3.41 Mg∙ha⁻¹), them being slightly lower in 2019 (on average, 3.0 Mg∙ha⁻¹) and the lowest in the dry 2018 (on average, 2.48 Mg∙ha⁻¹). Significant differences were recorded between cv. SG Anser (the average yield 2.73 Mg∙ha⁻¹) and Merlin (the average yield 3.31 Mg∙ha⁻¹). An application of biostimulants resulted in a significant increase in soybean seed yield compared with the control. Biostimulants contributed to a significant increase in the values of the remaining characteristics, i.e., 1000-seed weight, seed number per pod, and average number of seeds per pod. Full article

(This article belongs to the Special Issue The Role of Plant Hormones and Growth Regulators in Modern Crop Cultivation Technologies)

► Show Figures

Figure 1

17 pages, 6485 KiB

Open AccessArticle

Bioactive Compounds Extraction Using a Hybrid Ultrasound and High-Pressure Technology for Sustainable Farming Systems

by Florin Nenciu, Viorel Fatu, Vlad Arsenoaia, Catalin Persu, Iulian Voicea, Nicolae-Valentin Vladut, Mihai Gabriel Matache, Iuliana Gageanu, Eugen Marin, Sorin-Stefan Biris and Nicoleta Ungureanu

Agriculture 2023, 13(4), 899; https://doi.org/10.3390/agriculture13040899 - 19 Apr 2023

Cited by 2 | Viewed by 1447

Abstract

In the context of agricultural soil degradation caused by the extensive use of chemical amendments, ecological alternatives with minimal detrimental impact on ecosystems are gaining popularity. Recent advancements in processing technologies have improved the quality and extraction efficiency of bioactive compounds, particularly when [...] Read more.

In the context of agricultural soil degradation caused by the extensive use of chemical amendments, ecological alternatives with minimal detrimental impact on ecosystems are gaining popularity. Recent advancements in processing technologies have improved the quality and extraction efficiency of bioactive compounds, particularly when multiple conventional or innovative techniques are being used to potentially overcome the most common limitations. This paper proposes the development and testing of a hybrid technology design that employs two extraction techniques, namely ultrasound and high pressure, that can be used either separately or in tandem. An initial assessment of the prototype potential for isolating the desired compounds was made, by testing three various working regimens for the processing of a mixture of onion, pea, and soybean. By incorporating the bioactive compounds produced during the experimental phase in the seedling transplantation holes, we were able to test the potential of stimulating the development rate of vegetables and reducing the attack of pests. The extracts obtained using the hybrid technology showed positive results when used to reduce pest attacks (decreasing average attack frequency by 7%), however had negative effects when used to promote biostimulation, when acted as an inhibitor. The hybrid extraction approach improved the mass transfer into solvent by 14% when compared to high-pressure processing and by 7% when compared to sonication. Full article

(This article belongs to the Section Agricultural Technology)

► Show Figures

Figure 1

10 pages, 836 KiB

Open AccessArticle

Agent-Based Modelling to Improve Beef Production from Dairy Cattle: Young Beef Production

by Addisu H. Addis, Hugh T. Blair, Paul R. Kenyon, Stephen T. Morris, Nicola M. Schreurs and Dorian J. Garrick

Agriculture 2023, 13(4), 898; https://doi.org/10.3390/agriculture13040898 - 19 Apr 2023

Cited by 1 | Viewed by 1458

Abstract

Approximately 42% of the total calves born in New Zealand’s dairy industry are either euthanized on farms or commercially slaughtered as so-called bobby calves within 2 weeks of age. These practices have perceived ethical issues and are considered a waste of resources because [...] Read more.

Approximately 42% of the total calves born in New Zealand’s dairy industry are either euthanized on farms or commercially slaughtered as so-called bobby calves within 2 weeks of age. These practices have perceived ethical issues and are considered a waste of resources because these calves could be grown on and processed for beef. Young beef cattle harvested between 8 and 12 months of age would represent a new class of beef production for New Zealand and would allow for a greater number of calves to be utilized for beef production, reducing bobby calf numbers in New Zealand. However, the acceptance of such a system in competition with existing sheep and beef cattle production systems is unknown. Therefore, the current study employed an agent-based model (ABM) developed for dairy-origin beef cattle production systems to understand price levers that might influence the acceptance of young beef production systems on sheep and beef cattle farms in New Zealand. The agents of the model were the rearer, finisher, and processor. Rearers bought in 4-days old dairy-origin calves and weaned them at approximately 100 kg live weight before selling them to finishers. Finishers managed the young beef cattle until they were between 8 and 12 months of age in contrast to 20 to 30 months for traditional beef cattle. Processing young beef cattle in existing beef production systems without any price premium only led to an additional 5% of cattle being utilized compared to the traditional beef cattle production system in New Zealand. This increased another 2% when both weaner cattle and young beef were sold at a price premium of 10%. In this scenario, Holstein Friesian young bull contributed more than 65% of total young beef cattle. Further premium prices for young beef cattle production systems increased the proportion of young beef cattle (mainly as young bull beef), however, there was a decrease in the total number of dairy-origin cattle processed, for the given feed supply, compared to the 10% premium price. Further studies are required to identify price levers and other alternative young beef production systems to increase the number of young beef cattle as well the total number of dairy-origin beef cattle for beef on sheep and beef cattle farms. Some potential options for investigation are meat quality, retailer and consumer perspectives, and whether dairy farmers may have to pay calf rearers to utilize calves with lower growth potential. Full article

(This article belongs to the Special Issue Big Data Analytics and Machine Learning for Smart Agriculture)

► Show Figures

Figure 1

13 pages, 1307 KiB

Open AccessArticle

Growth and Quality of Leaf and Romaine Lettuce Grown on a Vertical Farm in an Aquaponics System: Results of Farm Research

by Bożena Matysiak, Stanisław Kaniszewski and Monika Mieszczakowska-Frąc

Agriculture 2023, 13(4), 897; https://doi.org/10.3390/agriculture13040897 - 19 Apr 2023

Cited by 3 | Viewed by 3462

Abstract

The integration of indoor vertical cultivation with a recirculating aquaculture system into an aquaponic system has the potential to become one of the most effective sustainable production systems for fish and leafy vegetables. In this study, lettuce was produced on rafts in a [...] Read more.

The integration of indoor vertical cultivation with a recirculating aquaculture system into an aquaponic system has the potential to become one of the most effective sustainable production systems for fish and leafy vegetables. In this study, lettuce was produced on rafts in a coupled recirculation aquaponic system in the plant factory under controlled environmental conditions. The aims of this study were to evaluate the yield, mineral status, and health-promoting bioactive compounds of leaf and romaine lettuce cultivars grown in a recirculating aquaponic system. The yield and biometric parameters and quality parameters of lettuce leaves (nitrate, mineral, L-ascorbic acid, carotenoid, phenolic compound, and total polyphenolic contents) were examined. Monitoring of the water in the aquaponic system showed a low concentration of nitrates, phosphorus (P), potassium (K), and magnesium (Mg), but the proportion of mineral nutrients as well as pH were stable throughout the lettuce cultivation period. The heads of romaine lettuce ‘Yakina’, ‘Pivotal’, and ‘Waygo’ reached a fresh weight of 86 g, on average, 23% higher than the leaf lettuce ‘Nordice’ over a three-week cultivation period. Despite the low nutrient concentration in the aquaponic solution, the nutrient status of the romaine lettuces ‘Yakina’ and ‘Pivotal’ was within the optimal range. The concentrations of chlorophyll a and carotenoids in ‘Yakina’ and ‘Pivotal’ were higher than those in ‘Nordice’ and ‘Waygo’. The nitrate, phosphorus, and potassium contents in the leaves of ‘Nordice’ and ‘Waygo’ were below the optimal range; however, their polyphenol concentrations were the highest. Our results indicate that the effectiveness of aquaponic cultivation of lettuce in terms of biomass production and the nutritional and health-promoting value of lettuce depends on the plant genotype. Full article

(This article belongs to the Special Issue Sustainable Production of Horticultural Crops)

► Show Figures

Figure 1

16 pages, 347 KiB

Open AccessArticle

Oat Hull as a Source of Lignin-Cellulose Complex in Diets Containing Wheat or Barley and Its Effect on Performance and Morphometric Measurements of Gastrointestinal Tract in Broiler Chickens

by Tomasz Hikawczuk, Anna Szuba-Trznadel, Patrycja Wróblewska and Andrzej Wiliczkiewicz

Agriculture 2023, 13(4), 896; https://doi.org/10.3390/agriculture13040896 - 19 Apr 2023

Viewed by 1133

Abstract

The purpose of the experiment was to determine the effect of oat hull on the performance and morphometric measurements of the gastrointestinal tract, and to correlate the results of these measurements with the type of the determined dietary fiber in feed and the [...] Read more.

The purpose of the experiment was to determine the effect of oat hull on the performance and morphometric measurements of the gastrointestinal tract, and to correlate the results of these measurements with the type of the determined dietary fiber in feed and the number of microorganisms. The Asp method is simpler and quicker than non-starch polysaccharide analysis, and can give quick information in the analysis of fiber fractions (soluble and insoluble) in the component or in a diet, and also related the obtained results with the performance of broiler chickens. The utilization of oat hull in the amount of 1% of the diet of broiler chickens results in the highest body weight on the 28th day of life (p < 0.05) in comparison to the group not receiving oat hull in the diet and with a 3% share of this structural component. Oat hull in the diet of broiler chickens in the amount of 1% also reduces the total length of the intestines (p < 0.05), compared with the share of 0 and 3%. The soluble fiber contained in the grains of barley and wheat has an influence on the higher metabolic weight of the glandular stomach of broiler chickens compared to the birds receiving corn grain in their diet. Barley grain and oat hull in the amount of 3% significantly (p < 0.01) increase the weight of gizzards. The increase in the weight of the proventriculus (r = 0.392), gizzard (r = 0.486) and duodenum (r = 0.657) was positively correlated with the growth of E. coli bacteria in the crop. The opposite effect in the case of negative correlation was determined in the case of the duodenum and E. coli count (r = −0.593). Full article

(This article belongs to the Special Issue Effects of Dietary Interventions on Poultry Production)

22 pages, 8475 KiB

Open AccessArticle

Evaluating the Canopy Chlorophyll Density of Maize at the Whole Growth Stage Based on Multi-Scale UAV Image Feature Fusion and Machine Learning Methods

by Lili Zhou, Chenwei Nie, Tao Su, Xiaobin Xu, Yang Song, Dameng Yin, Shuaibing Liu, Yadong Liu, Yi Bai, Xiao Jia and Xiuliang Jin

Agriculture 2023, 13(4), 895; https://doi.org/10.3390/agriculture13040895 - 19 Apr 2023

Cited by 2 | Viewed by 1776

Abstract

Maize is one of the main grain reserve crops, which directly affects the food security of the country. It is extremely important to evaluate the growth status of maize in a timely and accurate manner. Canopy Chlorophyll Density (CCD) is closely related to [...] Read more.

Maize is one of the main grain reserve crops, which directly affects the food security of the country. It is extremely important to evaluate the growth status of maize in a timely and accurate manner. Canopy Chlorophyll Density (CCD) is closely related to crop health status. A timely and accurate estimation of CCD is helpful for managers to take measures to avoid yield loss. Thus, many methods have been developed to estimate CCD with remote sensing data. However, the relationship between the CCD and the features used in these CCD estimation methods at different growth stages is unclear. In addition, the CCD was directly estimated from remote sensing data in most previous studies. If the CCD can be accurately estimated from the estimation results of Leaf Chlorophyll Density (LCD) and Leaf Area Index (LAI) remains to be explored. In this study, Random Forest (RF), Support Vector Machines (SVM), and Multivariable Linear Regression (MLR) were used to develop CCD, LCD, and LAI estimation models by integrating multiple features derived from unmanned aerial vehicle (UAV) multispectral images. Firstly, the performances of the RF, SVM, and MLR trained over spectral features (including vegetation indices and band reflectance; dataset I), texture features (dataset II), wavelet coefficient features (dataset III), and multiple features (dataset IV, including all the above datasets) were analyzed, respectively. Secondly, the CCD_P was calculated from the estimated LCD and estimated LAI, and then the CCD was estimated based on multiple features and the CCD_P was compared. The results show that the correlation between CCD and different features is significantly different at every growth stage. The RF model trained over dataset IV yielded the best performance for the estimation of LCD, LAI, and CCD (R² values were 0.91, 0.97, and 0.97, and RMSE values were 6.59 μg/cm², 0.35, and 24.85 μg/cm²). The CCD directly estimated from dataset IV is slightly closer to the ground truth CCD than the CCD_P (R² = 0.96, RMSE = 26.85 μg/cm²) calculated from LCD and LAI. The results indicated that the CCD of maize can be accurately estimated from multiple multispectral image features at the whole growth stage, and both CCD estimation strategies can be used to estimate the CCD accurately. This study provides a new reference for accurate CCD evaluation in precision agriculture. Full article

(This article belongs to the Topic Applications of Big Data and Machine Learning in Smart Agriculture)

► Show Figures

Figure 1

15 pages, 5002 KiB

Open AccessArticle

Agricultural Combine Remaining Value Forecasting Methodology and Model (and Derived Tool)

by Ivan Herranz-Matey and Luis Ruiz-Garcia

Agriculture 2023, 13(4), 894; https://doi.org/10.3390/agriculture13040894 - 18 Apr 2023

Cited by 3 | Viewed by 1220

Abstract

Harvesting is an integral component of the agricultural cycle, necessitating the use of high-performance grain harvester combines, which are utilized for a short period each year. Given the seasonality and significant cost involved, list prices ranging from a quarter to almost a million [...] Read more.

Harvesting is an integral component of the agricultural cycle, necessitating the use of high-performance grain harvester combines, which are utilized for a short period each year. Given the seasonality and significant cost involved, list prices ranging from a quarter to almost a million euros, a fact-based investment assessment decision-making process is essential. However, there is a paucity of research studies forecasting the remaining value of grain harvester combines in recent years. This study proposes a straightforward methodology based on public information that employs various parametric and non-parametric models to develop a robust and user-friendly model that can assist decision makers, such as farmers, contractors, sellers, and finance and insurance entities, in optimizing their harvesting operations. The model employs a power regression mode, with RMSE of 1.574 and RSqAdj of 0.8457 results, to provide accurate and reliable insights for informed decision-making. The robust model transparency enables us to easily create a mainstreamed spreadsheet-based dashboard tool. Full article

(This article belongs to the Section Agricultural Economics, Policies and Rural Management)

► Show Figures

Graphical abstract

15 pages, 4772 KiB

Open AccessArticle

Development of SSR Molecular Markers and Genetic Diversity Analysis of TPS Gene Family in Chimonanthus praecox

by Xuemei Fu, Nan Yang, Yongqin Du, Hafiz Muhammad Kamran, Huabo Wang, Shaoyuan Chen and Longqing Chen

Agriculture 2023, 13(4), 893; https://doi.org/10.3390/agriculture13040893 - 18 Apr 2023

Cited by 1 | Viewed by 1334

Abstract

Terpene synthase (TPS) plays a key role in the biosynthesis of terpenoids, which are the most important components of the volatile compounds of wintersweet (Chimonanthus praecox). In this study, 52 CpTPS genes were found in wintersweet which were divided into 5 [...] Read more.

Terpene synthase (TPS) plays a key role in the biosynthesis of terpenoids, which are the most important components of the volatile compounds of wintersweet (Chimonanthus praecox). In this study, 52 CpTPS genes were found in wintersweet which were divided into 5 subfamilies. We identified 146 SSRs in the CpTPS genes, and obtained 33 pairs of SSR primers with good polymorphism through amplification in 6 wintersweet samples. Then, these primers were amplified in 69 samples from China’s main wintersweet production areas. Through structural analysis, 69 samples were divided into 2 clusters, and were divided into 4 groups in a genetic cluster analysis, of which SH-33 and SW were separate groups. Through AMOVA analysis, it was found that the variation mainly occurred in the population, and that the gene flow between populations was Nm > 1, so it might lead to population differentiation. In other words, these findings provided useful information for the biosynthesis of terpenoids, the construction of a genetic linkage map, the detection of quantitative trait loci, marker-assisted selection and other aspects of wintersweet. Full article

(This article belongs to the Special Issue Better Ornamental Plants for Our Green Industry)

► Show Figures

Figure 1

19 pages, 6688 KiB

Open AccessArticle

Flight Parameter—Wind Vortex Characteristic Control Model of a Four-Multirotor Unmanned Aerial Vehicle Operating in Pesticide Spraying of Rice

by Zhijie Liu, Gangao Fan, Siyan Ye, Zhixun Zhang, Han Wu, Bo Long, Huifen Li, Hui Cheng, Longmei Wu and Jiyu Li

Agriculture 2023, 13(4), 892; https://doi.org/10.3390/agriculture13040892 - 18 Apr 2023

Cited by 1 | Viewed by 1326

Abstract

The downwash airflow generated by the rotors can enhance the penetration of pesticide droplets, allowing them to penetrate deeper into the canopy and more comprehensively control pests. Downwash air will produce a “wind vortex” in plant canopy, and the parameters of a “wind [...] Read more.

The downwash airflow generated by the rotors can enhance the penetration of pesticide droplets, allowing them to penetrate deeper into the canopy and more comprehensively control pests. Downwash air will produce a “wind vortex” in plant canopy, and the parameters of a “wind vortex” represent the effect of pesticide deposition to a certain extent. To obtain the corresponding relationship between wind vortices and flight parameters and control the effect of pesticide spraying, this paper carried out unmanned aerial vehicle (UAV) flight experiments in the field. Wind vortices were generated in rice canopy by downwash airflow, and the parameters of wind vortices were obtained by identifying wind-vortex images using the inter-frame difference method. The wind-vortex parameter control model was established, which can calculate the altitude and speed of the UAV when applying pesticide according to the target wind-vortex parameter. The deviations in the altitude were determined to be 0.67 and 0.43 m, and the deviations in the speed were 0.29 and 0.35 m/s during downwind and headwind UAV operations, respectively. The model relation functions were established, and their accuracies were found to be 97.1%, 92.3%, 69%, and 58% (downwind), and 97%, 78.4%, 62%, and 57% (upwind), respectively, indicating that downwind UAV operation leads to a clear relation between the wind-vortex parameters and the UAV-flight parameters. The model establishes the corresponding relationship between the wind-vortex parameters and flight parameters, which provides a theoretical basis for studying the precise application control method of UAV. Full article

(This article belongs to the Special Issue Application of UAVs in Precision Agriculture)

► Show Figures

Figure 1

22 pages, 1350 KiB

Open AccessArticle

Simulated Ecosystem and Farm-Level Economic Impacts of Conservation Tillage in a Northeastern Iowa County

by Edward Osei, Syed H. Jafri, Philip W. Gassman and Ali Saleh

Agriculture 2023, 13(4), 891; https://doi.org/10.3390/agriculture13040891 - 18 Apr 2023

Cited by 3 | Viewed by 1392

Abstract

While the ecological benefits of no-till are largely indisputable, the economic impacts are less certain, and the latter may be partly to blame for lower-than-expected adoption of no-till. In this study, we contribute to a better understanding of the ecosystem and farm-level economic [...] Read more.

While the ecological benefits of no-till are largely indisputable, the economic impacts are less certain, and the latter may be partly to blame for lower-than-expected adoption of no-till. In this study, we contribute to a better understanding of the ecosystem and farm-level economic impacts of no-till, with Buchanan County in the northeastern region of the U.S. State of Iowa as the backdrop due to previously established data and model validation efforts in that region. Using the Agricultural Policy Environmental eXtender (APEX) and Farm Economic Model (FEM), we simulated two tillage scenarios—a conservation tillage baseline and no-till—for continuous corn and corn–soybean rotations in Buchanan County using gridded historical climate data. We find that no-till provides clear ecosystem benefits, except that soluble nutrient losses might actually rise. We also find that under current commodity prices for corn and soybeans, no-till is not as profitable as the conservation tillage baseline. For no-till to be at least as profitable as the baseline under current commodity prices, the yield penalty associated with no-till cannot be higher than 1.5% for corn and 0.8% for soybeans, or similar combinations that entail a revenue penalty of about $24,000 for an 809-hectare continuous corn or corn–soybean operation. Given the simulated yield penalties associated with no-till, corn and soybean prices would have to be substantially lower in order for no-till to break even. Consequently, incentives for conservation practice implementation may need to be tied to commodity prices and yield penalties in order to elicit greater adoption rates. Full article

(This article belongs to the Special Issue Natural Resource and Environmental Economics in Agriculture)

► Show Figures

Figure 1

14 pages, 4232 KiB

Open AccessArticle

Responses of Micropropagated Rhubarb (Rheum rhaponticum) Plantlets to Different Growing Media and Light Conditions in the Greenhouse

by Agnieszka Wojtania, Bożena Matysiak, Monika Mieszczakowska-Frąc, Jacek S. Nowak and Justyna Szwejda-Grzybowska

Agriculture 2023, 13(4), 890; https://doi.org/10.3390/agriculture13040890 - 18 Apr 2023

Viewed by 1353

Abstract

Cultivating red-stalked rhubarb plants is an important source of raw materials for producing health-promoting foods. The quality and quantity of rhubarb crops are significantly dependent on planting material. To obtain high-quality planting material for the value selection of the rhubarb ‘Raspberry’, we evaluated [...] Read more.

Cultivating red-stalked rhubarb plants is an important source of raw materials for producing health-promoting foods. The quality and quantity of rhubarb crops are significantly dependent on planting material. To obtain high-quality planting material for the value selection of the rhubarb ‘Raspberry’, we evaluated the morphological and physiological responses of micropropagated plantlets to different growth substrates and light quality during early growth ex vitro in the greenhouse. The plantlets were grown in high-EC (GM1) and low-EC (GM2) peat substrates under four light-emitting diodes (LED) light treatments as supplementary lighting (SL) in the wintertime: 100% red (R), 100% blue (B), white light [44.4% green (G), 24.4% B, 28.9% R; 2.2% far red (FR)] and R+B+G+FR (49.4/16.3/10.3/23.8%) light. Compared to the control (natural sunlight), applied LED lighting significantly increased all growth parameters, but only in plantlets grown in GM1 substrate. Among LED treatments, R+B+G+FR light had the most stimulative effect on all growth parameters (length of leaf petioles, leaf area, biomass) and soluble sugar production. Still, it decreased the levels of phenolic compounds in the leaf petioles. Phenolic synthesis, mainly anthocyanins, was the highest under white light (622.8 mg·100 g⁻¹ dry mass), followed by red (601.8 mg·100 g⁻¹), blue (464.4 mg·100 g⁻¹), and R+B+G+FR light (416.4 mg·100 g⁻¹). High anthocyanin accumulation under R-LED light was associated with high antioxidant activity and growth cessation. Hence, for optimal effects related to plant growth and anthocyanin biosynthesis, the use of W-LED lighting is recommended for the early growth ex vitro of micropropagated rhubarb plantlets. Full article

(This article belongs to the Section Crop Production)

► Show Figures

Figure 1

20 pages, 27365 KiB

Open AccessArticle

An Intelligent and Precise Agriculture Model in Sustainable Cities Based on Visualized Symptoms

by Bashar Igried, Shadi AlZu’bi, Darah Aqel, Ala Mughaid, Iyad Ghaith and Laith Abualigah

Agriculture 2023, 13(4), 889; https://doi.org/10.3390/agriculture13040889 - 18 Apr 2023

Cited by 1 | Viewed by 1415

Abstract

Plant diseases represent one of the critical issues which lead to a major decrease in the quantity and quality of crops. Therefore, the early detection of plant diseases can avoid any losses or damage to these crops. This paper presents an image processing [...] Read more.

Plant diseases represent one of the critical issues which lead to a major decrease in the quantity and quality of crops. Therefore, the early detection of plant diseases can avoid any losses or damage to these crops. This paper presents an image processing and a deep learning-based automatic approach that classifies the diseases that strike the apple leaves. The proposed system has been tested using over 18,000 images from the Apple Diseases Dataset by PlantVillage, including images of healthy and affected apple leaves. We applied the VGG-16 architecture to a pre-trained unlabeled dataset of plant leave images. Then, we used some other deep learning pre-trained architectures, including Inception-V3, ResNet-50, and VGG-19, to solve the visualization-related problems in computer vision, including object classification. These networks can train the images dataset and compare the achieved results, including accuracy and error rate between those architectures. The preliminary results demonstrate the effectiveness of the proposed Inception V3 and VGG-16 approaches. The obtained results demonstrate that Inception V3 achieves an accuracy of 92.42% with an error rate of 0.3037%, while the VGG-16 network achieves an accuracy of 91.53% with an error rate of 0.4785%. The experiments show that these two deep learning networks can achieve satisfying results under various conditions, including lighting, background scene, camera resolution, size, viewpoint, and scene direction. Full article

(This article belongs to the Special Issue Technological Innovation for Measurements on Crop Physiological and Agronomic Traits)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Agriculture, Volume 13, Issue 4 (April 2023) – 177 articles

Further Information

Guidelines

MDPI Initiatives

Follow MDPI