Editor’s Choice Articles

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

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26 pages, 2151 KiB  
Review
The Path to Smart Farming: Innovations and Opportunities in Precision Agriculture
Agriculture 2023, 13(8), 1593; https://doi.org/10.3390/agriculture13081593 - 11 Aug 2023
Cited by 28 | Viewed by 8608
Abstract
Precision agriculture employs cutting-edge technologies to increase agricultural productivity while reducing adverse impacts on the environment. Precision agriculture is a farming approach that uses advanced technology and data analysis to maximize crop yields, cut waste, and increase productivity. It is a potential strategy [...] Read more.
Precision agriculture employs cutting-edge technologies to increase agricultural productivity while reducing adverse impacts on the environment. Precision agriculture is a farming approach that uses advanced technology and data analysis to maximize crop yields, cut waste, and increase productivity. It is a potential strategy for tackling some of the major issues confronting contemporary agriculture, such as feeding a growing world population while reducing environmental effects. This review article examines some of the latest recent advances in precision agriculture, including the Internet of Things (IoT) and how to make use of big data. This review article aims to provide an overview of the recent innovations, challenges, and future prospects of precision agriculture and smart farming. It presents an analysis of the current state of precision agriculture, including the most recent innovations in technology, such as drones, sensors, and machine learning. The article also discusses some of the main challenges faced by precision agriculture, including data management, technology adoption, and cost-effectiveness. Full article
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22 pages, 6735 KiB  
Article
Tea Tree Pest Detection Algorithm Based on Improved Yolov7-Tiny
Agriculture 2023, 13(5), 1031; https://doi.org/10.3390/agriculture13051031 - 09 May 2023
Cited by 13 | Viewed by 2838
Abstract
Timely and accurate identification of tea tree pests is critical for effective tea tree pest control. We collected image data sets of eight common tea tree pests to accurately represent the true appearance of various aspects of tea tree pests. The dataset contains [...] Read more.
Timely and accurate identification of tea tree pests is critical for effective tea tree pest control. We collected image data sets of eight common tea tree pests to accurately represent the true appearance of various aspects of tea tree pests. The dataset contains 782 images, each containing 1~5 different pest species randomly distributed. Based on this dataset, a tea garden pest detection and recognition model was designed using the Yolov7-tiny network target detection algorithm, which incorporates deformable convolution, the Biformer dynamic attention mechanism, a non-maximal suppression algorithm module, and a new implicit decoupling head. Ablation experiments were conducted to compare the performance of the models, and the new model achieved an average accuracy of 93.23%. To ensure the validity of the model, it was compared to seven common detection models, including Efficientdet, Faster Rcnn, Retinanet, DetNet, Yolov5s, YoloR, and Yolov6. Additionally, feature visualization of the images was performed. The results demonstrated that the Improved Yolov7-tiny model developed was able to better capture the characteristics of tea tree pests. The pest detection model proposed has promising application prospects and has the potential to reduce the time and economic cost of pest control in tea plantations. Full article
(This article belongs to the Section Digital Agriculture)
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18 pages, 1172 KiB  
Review
Recent Developments in Rice Molecular Breeding for Tolerance to Heavy Metal Toxicity
Agriculture 2023, 13(5), 944; https://doi.org/10.3390/agriculture13050944 - 25 Apr 2023
Cited by 9 | Viewed by 2432
Abstract
Heavy metal toxicity generally refers to the negative impact on the environment, humans, and other living organisms caused by exposure to heavy metals (HMs). Heavy metal poisoning is the accumulation of HMs in the soft tissues of organisms in a toxic amount. HMs [...] Read more.
Heavy metal toxicity generally refers to the negative impact on the environment, humans, and other living organisms caused by exposure to heavy metals (HMs). Heavy metal poisoning is the accumulation of HMs in the soft tissues of organisms in a toxic amount. HMs bind to certain cells and prevent organs from functioning. Symptoms of HM poisoning can be life-threatening and not only cause irreversible damage to humans and other organisms; but also significantly reduce agricultural yield. Symptoms and physical examination findings associated with HM poisoning vary depending on the metal accumulated. Many HMs, such as zinc, copper, chromium, iron, and manganese, are present at extremely low levels but are essential for the functioning of plants. However, if these metals accumulate in the plants in sufficient concentrations to cause poisoning, serious damage can occur. Rice is consumed around the world as a staple food and incidents of HM pollution often occur in rice-growing areas. In many rice-producing countries, cadmium (Cd), arsenic (As), and lead (Pb) have been recognized as commonly widespread HMs contaminating rice fields worldwide. In addition to mining and irrigation activities, the use of fertilizers and pesticides has also contributed significantly to HM contamination of rice-growing soils around the world. A number of QTLs associated with HM stress signals from various intermediary molecules have been reported to activate various transcription factors (TFs). Some antioxidant enzymes have been studied which contribute to the scavenging of reactive oxygen species, ultimately leading to stress tolerance in rice. Genome engineering and advanced editing techniques have been successfully applied to rice to improve metal tolerance and reduce HM accumulation in grains. In this review article, recent developments and progress in the molecular science for the induction of HM stress tolerance, including reduced metal uptake, compartmentalized transportation, gene-regulated signaling, and reduced accumulation or diversion of HM particles to plant parts other than grains, are discussed in detail, with particular emphasis on rice. Full article
(This article belongs to the Special Issue Challenges and Side Effects of Heavy Metals in Agriculture)
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14 pages, 2635 KiB  
Article
Effects of Variety and Pulsed Electric Field on the Quality of Fresh-Cut Apples
Agriculture 2023, 13(5), 929; https://doi.org/10.3390/agriculture13050929 - 24 Apr 2023
Cited by 5 | Viewed by 1403
Abstract
The suitability of five apple varieties (Ralls, Qinguan, Fuji, Delicious, and Cattle) for fresh-cut processing was compared based on the evaluation of weight loss, firmness, color, titratable acid (TA), polyphenoloxidase (PPO) activity and peroxidase (POD) activity, and the impact of pulsed electronic field [...] Read more.
The suitability of five apple varieties (Ralls, Qinguan, Fuji, Delicious, and Cattle) for fresh-cut processing was compared based on the evaluation of weight loss, firmness, color, titratable acid (TA), polyphenoloxidase (PPO) activity and peroxidase (POD) activity, and the impact of pulsed electronic field (PEF) on fresh-cut apples’ quality was explored. The results showed that the changes to Delicious apples in terms of the color parameter, firmness, and weight loss were comparable to or lower than the other samples, while the TA content was higher than the other samples during storage. Therefore, Delicious was selected for the study of the effects of PEF on fresh-cut apples. By measuring the physicochemical properties and microbiological characteristics within 10 days of storage, it was found that the PPO and POD activity of apples treated with PEF at 3 kV/cm on the 10th day decreased the most, with 44.61% and 36.48% decreases, respectively. In addition, apples treated with 5 kV/cm showed the greatest decrease in malondialdehyde (MDA) content and the number of microorganisms, 63.98%, and 9.17%, respectively. In general, the PEF-treated apples retained a high level of quality. These results suggested that PEF treatment is a promising technology for extending the storage period of fresh-cut apples. Full article
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14 pages, 1865 KiB  
Article
Organic Nitrogen Fertilizer Selection Influences Water Use Efficiency in Drip-Irrigated Sweet Corn
Agriculture 2023, 13(5), 923; https://doi.org/10.3390/agriculture13050923 - 22 Apr 2023
Cited by 2 | Viewed by 1495
Abstract
Organic farmers often rely on off-farm nitrogen (N) sources for mid-season N. Farmers can also produce cyano-fertilizer on-farm by growing N-fixing cyanobacteria (Anabaena spp.) in raceways and applying the cyanobacteria through irrigation systems. A two-year field study was conducted, and blood meal, [...] Read more.
Organic farmers often rely on off-farm nitrogen (N) sources for mid-season N. Farmers can also produce cyano-fertilizer on-farm by growing N-fixing cyanobacteria (Anabaena spp.) in raceways and applying the cyanobacteria through irrigation systems. A two-year field study was conducted, and blood meal, feather meal, fish emulsion, and cyano-fertilizer were evaluated to determine whether the water use efficiency (WUE) of sweet corn (Zea mays) was affected by fertilizer type. Fish emulsion and cyano-fertilizer were supplied in four split applications through drip irrigation, while the blood meal and feather meal were subsurface banded pre-plant. Leaf gas exchange measurements were taken during tasseling. The amounts of phytohormone and Fe applied in organic N fertilizers were correlated with field water use efficiency (fWUE), instantaneous water use efficiency (iWUE), and leaf gas exchange components of sweet corn. A positive relationship was observed between the amount of salicylic acid (SA) applied with both iWUE (r = 0.71, p < 0.05) and fWUE (r = 0.68, p < 0.01). The amount of Fe applied was positively correlated with the leaf vapor pressure deficit (r = 0.54, p < 0.01) and transpiration rate (r = 0.53, p < 0.01). Cyano-fertilizer had the highest yield and WUE, likely due to the high amount of SA applied, although fish emulsion was comparable in year one. These relationships require further exploration to elucidate the mechanisms impacting WUE. Full article
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19 pages, 363 KiB  
Article
The Effect of Mycorrhiza Fungi and Various Mineral Fertilizer Levels on the Growth, Yield, and Nutritional Value of Sweet Pepper (Capsicum annuum L.)
Agriculture 2023, 13(4), 857; https://doi.org/10.3390/agriculture13040857 - 12 Apr 2023
Cited by 3 | Viewed by 2224
Abstract
Mycorrhizal fungi can increase the effectiveness of a mineral fertilizer top dressing, positively affecting sweet pepper yield and quality. For this reason, an experiment was carried out between 2014 and 2016 to study the effect of top dressing doses and the inoculation of [...] Read more.
Mycorrhizal fungi can increase the effectiveness of a mineral fertilizer top dressing, positively affecting sweet pepper yield and quality. For this reason, an experiment was carried out between 2014 and 2016 to study the effect of top dressing doses and the inoculation of the root system with mycorrhizal fungi on the growth and yield of sweet pepper and the content of nutrients and macro- and microelements in the fruits. Root inoculation with Arbuscular Mycorrhizal Fungi (AMF) and mineral fertilizer doses were used as experimental factors with the following combinations: (1) mycorrhization: control (without AMF); AMF applied to the plant root zone during seedling production; AMF applied to the plant root zone after seedlings were transferred to pots; (2) top dressing doses: basic dose (100%); 50% of the basic dose; 25% of the basic dose. The sweet pepper fruits were harvested during physiological maturity. AMF inoculation of the root zone resulted in high sweet pepper yields of good quality. In particular, mycorrhizal fungi applied to the root system during seedling production positively affected the pepper yield and biometric characteristics, with fruits of the thickest pericarp and the largest mass. In the experimental units with AMF, the reduction in the top dressing fertilizer dose by 50% and 75% did not cause a statistically significant decrease in the yield of peppers and did not result in a deterioration of the biometric characteristics of the plants and fruits or a reduction in the biological value of the fruits. Despite the reduction in top dressing dose by 50% and 75%, AMF contributed to the accumulation of similar amounts of phosphorus in the sweet pepper fruits. The top dressing dose of 50% applied during seedling production to the experimental units with mycorrhizal fungi resulted in a significant increase in the content of potassium, calcium, and magnesium. A significant increase in the amount of sodium in the fruits was noted in the experimental units with mycorrhizal fungi applied to the roots when the seedlings were transferred to pots. To summarize, the application of mycorrhizal fungi to the pepper root zone during seedling production is recommended because it has a positive effect on the yield and its quality. In the unit with mycorrhiza, a lower dose of mineral fertilizers did not result in a significant decrease in the yield of pepper fruits. Full article
(This article belongs to the Special Issue Arbuscular Mycorrhiza and Its Influence on Crop Production)
18 pages, 5378 KiB  
Article
Design and Experiment of an Underactuated Broccoli-Picking Manipulator
Agriculture 2023, 13(4), 848; https://doi.org/10.3390/agriculture13040848 - 11 Apr 2023
Cited by 4 | Viewed by 1683
Abstract
Mature broccoli has large flower balls and thick stems. Therefore, manual broccoli picking is laborious and energy-consuming. However, the big spheroid vegetable-picking manipulator has a complex structure and poor enveloping effect and easily causes mechanical damage. Therefore, a broccoli flower ball-picking manipulator with [...] Read more.
Mature broccoli has large flower balls and thick stems. Therefore, manual broccoli picking is laborious and energy-consuming. However, the big spheroid vegetable-picking manipulator has a complex structure and poor enveloping effect and easily causes mechanical damage. Therefore, a broccoli flower ball-picking manipulator with a compact structure and simple control system was designed. The manipulator was smart in structure and stable in configuration when enveloped in flower balls. First, a physical damage test was carried out on broccoli according to the underactuated manipulator’s design scheme. The maximum surface pressure of the flower ball was 30 N, and the maximum cutting force of the stem was 35 N. Then, kinematic analysis was completed, and the statical model of the underactuated mechanism was established. The dimension of the underactuated mechanism for each connecting rod was determined based on the damage test results and design requirements. The sizes of each connecting rod were 50 cm, 90 cm, 50 cm, 90 cm, 50 cm, 60 cm, and 65 cm. The statical model calculated the required thrust of the underactuated mechanism as 598.66–702.88 N. Then, the manipulator was simulated to verify its reliability of the manipulator. Finally, the manipulator’s motion track, speed, and motor speed were determined in advance in the laboratory environment. One-hundred picking tests were carried out on mature broccoli with a 135–185 mm diameter. Results showed that the manipulator had an 84% success rate in picking and a 100% lossless rate. The fastest single harvest time in the test stand was 11.37 s when the speed of the robot arm was 3.4 m/s, and the speed of the stepper motor was 60 r/min. Full article
(This article belongs to the Special Issue 'Eyes', 'Brain', 'Feet' and 'Hands' of Efficient Harvesting Machinery)
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11 pages, 313 KiB  
Article
QTL×QTL×QTL Interaction Effects for Total Phenolic Content of Wheat Mapping Population of CSDH Lines under Drought Stress by Weighted Multiple Linear Regression
Agriculture 2023, 13(4), 850; https://doi.org/10.3390/agriculture13040850 - 11 Apr 2023
Cited by 5 | Viewed by 1616
Abstract
This paper proposes the use of weighted multiple linear regression to estimate the triple3interaction (additive×additive×additive) of quantitative trait loci (QTLs) effects. The use of unweighted regression yielded an improvement (in absolute value) in the QTL×QTL×QTL interaction effects compared to assessment based on phenotypes [...] Read more.
This paper proposes the use of weighted multiple linear regression to estimate the triple3interaction (additive×additive×additive) of quantitative trait loci (QTLs) effects. The use of unweighted regression yielded an improvement (in absolute value) in the QTL×QTL×QTL interaction effects compared to assessment based on phenotypes alone in three cases (severe drought in 2010, control in 2012 and severe drought in 2012). In contrast, weighted regression yielded an improvement (in absolute value) in the evaluation of the aaagw parameter compared to aaap in five cases, with the exception of severe drought in 2012. The results show that by using weighted regression on marker observations, the obtained estimates are closer to the ones obtained by the phenotypic method. The coefficients of determination for the weighted regression model were significantly higher than for the unweighted regression and ranged from 46.2% (control in 2010) to 95.0% (control in 2011). Considering this, it is clear that a three-way interaction had a significant effect on the expression of quantitative traits. Full article
(This article belongs to the Special Issue Cereal Genetics, Breeding and Wide Crossing)
11 pages, 1446 KiB  
Article
Classification of Codling Moth-Infested Apples Using Sensor Data Fusion of Acoustic and Hyperspectral Features Coupled with Machine Learning
Agriculture 2023, 13(4), 839; https://doi.org/10.3390/agriculture13040839 - 08 Apr 2023
Cited by 1 | Viewed by 1363
Abstract
Codling moth (CM) is a major apple pest. Current manual method of detection is not very effective. The development of nondestructive monitoring and detection methods has the potential to reduce postharvest losses from CM infestation. Previous work from our group demonstrated the effectiveness [...] Read more.
Codling moth (CM) is a major apple pest. Current manual method of detection is not very effective. The development of nondestructive monitoring and detection methods has the potential to reduce postharvest losses from CM infestation. Previous work from our group demonstrated the effectiveness of hyperspectral imaging (HSI) and acoustic methods as suitable techniques for nondestructive CM infestation detection and classification in apples. However, both have limitations that can be addressed by the strengths of the other. For example, acoustic methods are incapable of detecting external CM symptoms but can determine internal pest activities and morphological damage, whereas HSI is only capable of detecting the changes and damage to apple surfaces and up to a few mm inward; it cannot detect live CM activity in apples. This study investigated the possibility of sensor data fusion from HSI and acoustic signals to improve the detection of CM infestation in apples. The time and frequency domain acoustic features were combined with the spectral features obtained from the HSI, and various classification models were applied. The results showed that sensor data fusion using selected combined features (mid-level) from the sensor data and three apple varieties gave a high classification rate in terms of performance and reduced the model complexity with an accuracy up to 94% using the AdaBoost classifier, when only six acoustic and six HSI features were applied. This result affirms that the sensor fusion technique can improve CM infestation detection in pome fruits such as apples. Full article
(This article belongs to the Special Issue Innovative Methods and Technology for Resilience Agrifood Systems)
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21 pages, 1374 KiB  
Article
Effect of Cropping Systems and Environment on Phenolic Acid Profiles and Yielding of Hybrid Winter Wheat Genotypes
Agriculture 2023, 13(4), 834; https://doi.org/10.3390/agriculture13040834 - 06 Apr 2023
Cited by 5 | Viewed by 1207
Abstract
Wheat is of significant economic importance due to its high yield potential and high nutritional value as well as the technological usefulness of the grain. Field experiments were carried out in the years 2015–2018 in southeastern Poland. A three-factor experiment was used to [...] Read more.
Wheat is of significant economic importance due to its high yield potential and high nutritional value as well as the technological usefulness of the grain. Field experiments were carried out in the years 2015–2018 in southeastern Poland. A three-factor experiment was used to study the influence of wheat cultivars (hybrid—cvs. Hybred and Hymack; common—cv. Batuta), cultivation systems (organic—ORG, integrated—INT, conventional—CON) and of environmental conditions (using two different locations: Dukla and Nowy Lubliniec) on wheat grains’ phenolic acid (PA) content and grain yield. The research confirms the genetic determinants of grain yield and PA composition in wheat grains, and their different accumulation levels of ferulic acid and other PAs—with the exception of sinapic, p-coumaric, and salicilic—with hybrid cultivars performing better than common cultivars. The ORG system, compared to the INT and CON systems, caused a larger increase in total acids (TPAs)—especially of ferulic, vanillic, and syringic acids—in grains of cv. Hybred, and of caffeic acid in cv. Hymack, compared to cv. Batuta. The lack of interaction between the cultivation systems and the cultivars indicates that similar reactions to increases in grain yield due to increases in the intensity of cultivation take place in cultivars. The more favourable environmental conditions in Dukla favoured the accumulation of ferulic, p-coumaric, vanillic, syringic, p-hydroxybenzoic, and protocatechuic acids in the grains. TPAs were higher by 4.3% and the grain yield by 4.0% on average. Variable conditions in the season 2015/2016 resulted in higher yields of hybrid cvs. grains than of common cv., which proves the greater yielding stability of these cultivars in years with adverse weather conditions. The season 2016/2017 had less rainfall and faced high temperatures during grain ripening, favouring a higher PA content and TPAs, especially in the grains of cv. Hybred. This suggests a need to further assess the genetic progress of hybrid wheat cultivars cultivated under different environmental conditions in terms of their PA composition and content. Full article
(This article belongs to the Section Crop Production)
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14 pages, 3673 KiB  
Article
Effect of Nitrogen Application Methods on Yield and Grain Quality of an Extremely Early Maturing Rice Variety
Agriculture 2023, 13(4), 832; https://doi.org/10.3390/agriculture13040832 - 05 Apr 2023
Cited by 1 | Viewed by 1459
Abstract
This study aimed to investigate the effect of nitrogen application methods on the yield and grain quality of an extremely early maturing rice variety. The experiment was conducted in the rice research field of Chungnam Agricultural Research and Extension Services, South Korea, in [...] Read more.
This study aimed to investigate the effect of nitrogen application methods on the yield and grain quality of an extremely early maturing rice variety. The experiment was conducted in the rice research field of Chungnam Agricultural Research and Extension Services, South Korea, in 2019 and 2020. Two nitrogen application methods, BD (100% as a basal dressing) and BTD (70% as a basal dressing + 30% as a top dressing), with three different nitrogen levels (70 kg/ha, 90 kg/ha, and 110 kg/ha), were employed. The results showed that BD treatment had comparable or higher head rice yields and improved grain quality compared to BTD treatment at all nitrogen levels. Additionally, the SPAD value at heading date was highly correlated with both the protein content (r2 = 0.838**) and glossiness of cooked rice (r2 = 0.630**). Therefore, this study suggests that BD treatment could be an effective approach to improve the productivity and quality of extremely early maturing rice varieties while saving on labor costs, and the SPAD value can be used as an index to infer the taste of rice. In conclusion, this study provides useful insights into nitrogen application methods that can be used to enhance the yield and quality of extremely early maturing rice varieties. Full article
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17 pages, 2745 KiB  
Article
Developing a Crop Water Production Function for Alfalfa under Deficit Irrigation: A Case Study in Eastern Colorado
Agriculture 2023, 13(4), 831; https://doi.org/10.3390/agriculture13040831 - 04 Apr 2023
Cited by 1 | Viewed by 1658
Abstract
Recent Colorado, USA water law provisions allow a portion of irrigation water to be leased between agricultural and other users. Reducing consumptive use (CU) through deficit irrigation while maintaining some crop production could allow farmers to earn revenue from leasing water rights. This [...] Read more.
Recent Colorado, USA water law provisions allow a portion of irrigation water to be leased between agricultural and other users. Reducing consumptive use (CU) through deficit irrigation while maintaining some crop production could allow farmers to earn revenue from leasing water rights. This observational study aimed to determine if deficit irrigation of alfalfa (Medicago sativa L.) can be used to reduce CU, provide parameters for an alfalfa crop water production function (WPF), and evaluate the potential for improved farm income by leasing water. Soil water balance, evapotranspiration (ET), and dry matter yield from eight commercial fields (1.70 to 2.14 ha zones), growing subsurface drip-irrigated alfalfa, were monitored for five seasons (2018–2022) at Kersey, Colorado. Four irrigation treatments [Standard Irrigation (SI) = irrigate when soil water deficit (D) exceeds management allowed depletion (MAD); Moderate Deficit Irrigation (MDI) = 70% of SI; Severe Deficit Irrigation (SDI) = 50% of SI; and Over Irrigation (OI) = 120% of SI] were applied, with two zones per treatment. Reductions in CU ranged from 205 to 260 mm per season. The shape of the alfalfa WPF (dry biomass yield vs. ET) was concave, indicating that water use efficiency (WUE) could be optimized through deficit irrigation. The average WUE was 0.17 Mg ha−1 cm−1 and tended to increase with greater deficits. Deficit irrigation also increased the relative feed value. If conserved CU from deficit irrigation can be leased into a transfer water market, farmers could profit when the water lease revenue exceeds the forgone profit from alfalfa production. We found incremental profit from deficit irrigation and water leasing to be positive, assuming 2020 prices for hay ($230 bale−1) and water prices above $0.50 m−3. Full article
(This article belongs to the Section Agricultural Water Management)
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22 pages, 330 KiB  
Article
Effect of Fiscal Expenditure for Supporting Agriculture on Agricultural Economic Efficiency in Central China—A Case Study of Henan Province
Agriculture 2023, 13(4), 822; https://doi.org/10.3390/agriculture13040822 - 02 Apr 2023
Cited by 4 | Viewed by 1476
Abstract
The policy guidance and financial support for industrial development from public finance provide an important guarantee for practicing green and circular development of agriculture. By sorting out the development context of fiscal support for agriculture in Henan province in different historical stages, this [...] Read more.
The policy guidance and financial support for industrial development from public finance provide an important guarantee for practicing green and circular development of agriculture. By sorting out the development context of fiscal support for agriculture in Henan province in different historical stages, this paper analyzes the development status of fiscal support for agriculture and the agricultural circular economy in the province. Relying on data envelopment analysis (DEA), it measures the efficiency of the agricultural circular economy in Henan province in 2013–2019 using the Charnes, Cooper, and Rhodes (CCR) model, the Banker, Charnes, and Cooper (BCC) model, and super-efficiency DEA models and empirically analyzes the effect of the fiscal expenditure for supporting agriculture on the efficiency of the agricultural circular economy using the fixed effect model. According to the results, (1) the expenditure on comprehensive agricultural development of Henan Province was mainly supported by the government’s fiscal funds to such a degree that the proportion of fiscal funds from the central government exceeded 40% throughout the year. Particular stress was laid on the land governance projects of comprehensive agricultural development in the province. (2) The overall development level of the agricultural circular economy in Henan Province was low, and there were considerable gaps between cities (counties). Under the super-efficiency DEA model, only Hebi City, which ranked first in terms of average efficiency, achieved relative efficiency. (3) The fiscal expenditure for supporting agriculture had a positive incentive effect on the efficiency of the agricultural circular economy in Henan province, and the incentive effect became more significant after the time effect was controlled. Accordingly, this paper puts forward some targeted policy suggestions, which enrich the existing research on fiscal support for agriculture and agricultural circular economy at both theoretical and practical levels. Full article
(This article belongs to the Section Agricultural Economics, Policies and Rural Management)
14 pages, 1152 KiB  
Review
The Impact of Auxin and Cytokinin on the Growth and Development of Selected Crops
Agriculture 2023, 13(3), 724; https://doi.org/10.3390/agriculture13030724 - 21 Mar 2023
Cited by 15 | Viewed by 13259
Abstract
With a very diverse structure and small molecules, phytohormones are regulators of plant growth and development. Despite the fact that they are synthesized by plants in small quantities, they are highly active physiologically. According to their action, phytohormones can be divided into two [...] Read more.
With a very diverse structure and small molecules, phytohormones are regulators of plant growth and development. Despite the fact that they are synthesized by plants in small quantities, they are highly active physiologically. According to their action, phytohormones can be divided into two categories, as either activators of plant growth and development or as inhibitors, with auxins and cytokinins belonging to the former group. Auxins are synthesized by plants in the apical meristems of shoots, but also in young leaves, seeds, and fruits. They stimulate the elongation growth of shoots and initiate the production of adventitious and lateral roots. Cytokinins, in turn, are formed in root tips and in unripe fruits and seeds. These hormones are responsible for stimulating the growth of lateral shoots, they also stimulate cytokinesis and, consequently, cell division. The aim of this review paper is to present the progress of the research on the effect of selected auxins and cytokinins on crops, considering the prospect of using them in plant growing methods. Full article
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24 pages, 4869 KiB  
Review
A Systematic Review on Automatic Insect Detection Using Deep Learning
Agriculture 2023, 13(3), 713; https://doi.org/10.3390/agriculture13030713 - 19 Mar 2023
Cited by 11 | Viewed by 7419
Abstract
Globally, insect pests are the primary reason for reduced crop yield and quality. Although pesticides are commonly used to control and eliminate these pests, they can have adverse effects on the environment, human health, and natural resources. As an alternative, integrated pest management [...] Read more.
Globally, insect pests are the primary reason for reduced crop yield and quality. Although pesticides are commonly used to control and eliminate these pests, they can have adverse effects on the environment, human health, and natural resources. As an alternative, integrated pest management has been devised to enhance insect pest control, decrease the excessive use of pesticides, and enhance the output and quality of crops. With the improvements in artificial intelligence technologies, several applications have emerged in the agricultural context, including automatic detection, monitoring, and identification of insects. The purpose of this article is to outline the leading techniques for the automated detection of insects, highlighting the most successful approaches and methodologies while also drawing attention to the remaining challenges and gaps in this area. The aim is to furnish the reader with an overview of the major developments in this field. This study analysed 92 studies published between 2016 and 2022 on the automatic detection of insects in traps using deep learning techniques. The search was conducted on six electronic databases, and 36 articles met the inclusion criteria. The inclusion criteria were studies that applied deep learning techniques for insect classification, counting, and detection, written in English. The selection process involved analysing the title, keywords, and abstract of each study, resulting in the exclusion of 33 articles. The remaining 36 articles included 12 for the classification task and 24 for the detection task. Two main approaches—standard and adaptable—for insect detection were identified, with various architectures and detectors. The accuracy of the classification was found to be most influenced by dataset size, while detection was significantly affected by the number of classes and dataset size. The study also highlights two challenges and recommendations, namely, dataset characteristics (such as unbalanced classes and incomplete annotation) and methodologies (such as the limitations of algorithms for small objects and the lack of information about small insects). To overcome these challenges, further research is recommended to improve insect pest management practices. This research should focus on addressing the limitations and challenges identified in this article to ensure more effective insect pest management. Full article
(This article belongs to the Special Issue Internet of Things (IoT) for Precision Agriculture Practices)
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16 pages, 12439 KiB  
Review
State of Major Vegetation Indices in Precision Agriculture Studies Indexed in Web of Science: A Review
Agriculture 2023, 13(3), 707; https://doi.org/10.3390/agriculture13030707 - 18 Mar 2023
Cited by 20 | Viewed by 4355
Abstract
Vegetation indices provide information for various precision-agriculture practices, by providing quantitative data about crop growth and health. To provide a concise and up-to-date review of vegetation indices in precision agriculture, this study focused on the major vegetation indices with the criterion of their [...] Read more.
Vegetation indices provide information for various precision-agriculture practices, by providing quantitative data about crop growth and health. To provide a concise and up-to-date review of vegetation indices in precision agriculture, this study focused on the major vegetation indices with the criterion of their frequency in scientific papers indexed in the Web of Science Core Collection (WoSCC) since 2000. Based on the scientific papers with the topic of “precision agriculture” combined with “vegetation index”, this study found that the United States and China are global leaders in total precision-agriculture research and the application of vegetation indices, while the analysis adjusted for the country area showed much more homogenous global development of vegetation indices in precision agriculture. Among these studies, vegetation indices based on the multispectral sensor are much more frequently adopted in scientific studies than their low-cost alternatives based on the RGB sensor. The normalized difference vegetation index (NDVI) was determined as the dominant vegetation index, with a total of 2200 studies since the year 2000. With the existence of vegetation indices that improved the shortcomings of NDVI, such as enhanced vegetation index (EVI) and soil-adjusted vegetation index (SAVI), this study recognized their potential for enabling superior results to those of NDVI in future studies. Full article
(This article belongs to the Special Issue Recent Advances in Agro-Geoinformatics)
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26 pages, 921 KiB  
Review
Strategies Used to Reduce Methane Emissions from Ruminants: Controversies and Issues
Agriculture 2023, 13(3), 602; https://doi.org/10.3390/agriculture13030602 - 01 Mar 2023
Cited by 13 | Viewed by 9011
Abstract
Methanogenesis plays a crucial role in the digestive process of ruminant animals. During this process, methanogenic archaea produce methane as a byproduct of their metabolism. However, the production of methane by ruminants is also a significant contributor to greenhouse gas emissions. Methane is [...] Read more.
Methanogenesis plays a crucial role in the digestive process of ruminant animals. During this process, methanogenic archaea produce methane as a byproduct of their metabolism. However, the production of methane by ruminants is also a significant contributor to greenhouse gas emissions. Methane is a potent greenhouse gas that has a 28-fold greater global warming potential than carbon dioxide. Around 15% of all anthropogenic greenhouse gas emissions are generated by livestock. Therefore, reducing methane emissions from ruminant livestock is an important goal for reducing the environmental impact of agriculture. There is a variety of strategies that can be used to reduce methane emissions, including dietary modifications, genetic selection, microbiome manipulation, and feed additives, such as plant secondary metabolites, methane inhibitors, lipids, essential oils, and algae. The main and important objective of this paper is to critically discuss the current strategies proposed to reduce methane emissions from livestock. Though many strategies, such as chemical intervention, have remarkably reduced methane emissions from ruminants, their usage remains unappealing because of health and safety concerns as well as consumer decisions. Hence, genetic animal selection and biological feed additives, such as probiotics and secondary plant metabolites, have emerged as promising techniques for mitigating enteric methane emissions. These strategies are highly promising, but more intensive research is needed to validate these approaches and assess their effectiveness in reducing methane production by ruminants. Full article
(This article belongs to the Special Issue Nutritional and Metabolic Regulation of Dairy Cow)
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16 pages, 3636 KiB  
Article
Germination and Seedling Development Responses of Sunflower (Helianthus annuus L.) Seeds to Temperature and Different Levels of Water Availability
Agriculture 2023, 13(3), 608; https://doi.org/10.3390/agriculture13030608 - 01 Mar 2023
Cited by 6 | Viewed by 5313
Abstract
Abiotic variables are crucial for seed germination and seedling development. In the present work, we attempted to determine the optimal conditions (temperature, water, seed density, and fungal growth) for sunflower seed development (Helianthus annus L. Larissza). The germination of sunflower seeds was [...] Read more.
Abiotic variables are crucial for seed germination and seedling development. In the present work, we attempted to determine the optimal conditions (temperature, water, seed density, and fungal growth) for sunflower seed development (Helianthus annus L. Larissza). The germination of sunflower seeds was investigated under controlled conditions at eight consistent temperatures: 5 °C, 10 °C, 15 °C, 20 °C, 25 °C, 30 °C, 35 °C, and 40 °C. For the water test, there were 12 water levels based on one-milliliter intervals and 18 water levels based on thousand kernel weight (TKW). In addition, four seed densities (6, 8, 10, and 12) and two antifungal application techniques (sterilization and growing medium) were examined. The results showed that temperature has a significant effect on seed germination, germination timing, and seedling development. Temperatures between 15 and 35 degrees Celsius were optimal for germination, with 25 degrees Celsius being the optimal temperature for significant germination and seedling development. Beginning at 0.6 mL, or 125% of the TKW, sunflower seeds can germinate under a wide range of water availability. The optimal range for seedling development (8.2–11.4) is wider than the optimal range for dry matter accumulation, which is 5.8–8.2 mL or 1000–1625% of the TKW. The finding that a density of 10 to 12 seeds per 9 cm Petri dish demonstrates the most exceptional values is advantageous for future research and breeding projects, particularly when seeds are scarce. Seed priming is a more effective antifungal application technique than other techniques. Full article
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20 pages, 4153 KiB  
Article
An Effective Pyramid Neural Network Based on Graph-Related Attentions Structure for Fine-Grained Disease and Pest Identification in Intelligent Agriculture
Agriculture 2023, 13(3), 567; https://doi.org/10.3390/agriculture13030567 - 26 Feb 2023
Cited by 12 | Viewed by 1833
Abstract
In modern agriculture and environmental protection, effective identification of crop diseases and pests is very important for intelligent management systems and mobile computing application. However, the existing identification mainly relies on machine learning and deep learning networks to carry out coarse-grained classification of [...] Read more.
In modern agriculture and environmental protection, effective identification of crop diseases and pests is very important for intelligent management systems and mobile computing application. However, the existing identification mainly relies on machine learning and deep learning networks to carry out coarse-grained classification of large-scale parameters and complex structure fitting, which lacks the ability in identifying fine-grained features and inherent correlation to mine pests. To solve existing problems, a fine-grained pest identification method based on a graph pyramid attention, convolutional neural network (GPA-Net) is proposed to promote agricultural production efficiency. Firstly, the CSP backbone network is constructed to obtain rich feature maps. Then, a cross-stage trilinear attention module is constructed to extract the abundant fine-grained features of discrimination portions of pest objects as much as possible. Moreover, a multilevel pyramid structure is designed to learn multiscale spatial features and graphic relations to enhance the ability to recognize pests and diseases. Finally, comparative experiments executed on the cassava leaf, AI Challenger, and IP102 pest datasets demonstrates that the proposed GPA-Net achieves better performance than existing models, with accuracy up to 99.0%, 97.0%, and 56.9%, respectively, which is more conducive to distinguish crop pests and diseases in applications for practical smart agriculture and environmental protection. Full article
(This article belongs to the Section Digital Agriculture)
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29 pages, 5961 KiB  
Review
Review of Discrete Element Method Simulations of Soil Tillage and Furrow Opening
Agriculture 2023, 13(3), 541; https://doi.org/10.3390/agriculture13030541 - 23 Feb 2023
Cited by 12 | Viewed by 2715
Abstract
In agricultural machinery design and optimization, the discrete element method (DEM) has played a major role due to its ability to speed up the design and manufacturing process by reducing multiple prototyping, testing, and evaluation under experimental conditions. In the field of soil [...] Read more.
In agricultural machinery design and optimization, the discrete element method (DEM) has played a major role due to its ability to speed up the design and manufacturing process by reducing multiple prototyping, testing, and evaluation under experimental conditions. In the field of soil dynamics, DEM has been mainly applied in the design and optimization of soil-engaging tools, especially tillage tools and furrow openers. This numerical method is able to capture the dynamic and bulk behaviour of soils and soil–tool interactions. This review focused on the various aspects of the application of DEM in the simulation of tillage and furrow opening for tool design optimization. Different contact models, particle sizes and shapes, and calibration techniques for determining input parameters for tillage and furrow opening research have been reviewed. Discrete element method predictions of furrow profiles, disturbed soil surface profiles, soil failure, loosening, disturbance parameters, reaction forces, and the various types of soils modelled with DEM have also been highlighted. This pool of information consolidates existing working approaches used in prior studies and helps to identify knowledge gaps which, if addressed, will advance the current soil dynamics modelling capability. Full article
(This article belongs to the Special Issue Design and Application of Agricultural Equipment in Tillage System)
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31 pages, 1356 KiB  
Review
Agricultural Strategies to Reduce Cadmium Accumulation in Crops for Food Safety
Agriculture 2023, 13(2), 471; https://doi.org/10.3390/agriculture13020471 - 16 Feb 2023
Cited by 9 | Viewed by 4386
Abstract
Cadmium (Cd) contamination in edible agricultural products, especially in crops, has raised worldwide concerns regarding food safety consumption. This review summarizes the current knowledge of the applicable methods and perspectives for reducing Cd contamination of agricultural products. Agricultural approaches of soil amendments, irrigation [...] Read more.
Cadmium (Cd) contamination in edible agricultural products, especially in crops, has raised worldwide concerns regarding food safety consumption. This review summarizes the current knowledge of the applicable methods and perspectives for reducing Cd contamination of agricultural products. Agricultural approaches of soil amendments, irrigation management, microbial agent, and cropping patterns were systematically concluded to illustrate the developments and achievements in crop contamination management. The use of traditional soil amendments as well as novel nano-materials has contributed to producing safe crops in agricultural soil contaminated with Cd. This review provides an inspiring and promising tool for maintaining food safety by reducing Cd accumulation in edible agricultural products. Full article
(This article belongs to the Topic Effect of Heavy Metals on Plants)
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30 pages, 3978 KiB  
Review
Phosphorus-Solubilizing Microorganisms: A Key to Sustainable Agriculture
Agriculture 2023, 13(2), 462; https://doi.org/10.3390/agriculture13020462 - 15 Feb 2023
Cited by 13 | Viewed by 7902
Abstract
Phosphorus (P) is one of the essential macronutrients for plant growth, being a highly required resource to improve the productive performance of several crops, especially in highly weathered soils. However, a large part of the nutrients applied in the form of fertilizers becomes [...] Read more.
Phosphorus (P) is one of the essential macronutrients for plant growth, being a highly required resource to improve the productive performance of several crops, especially in highly weathered soils. However, a large part of the nutrients applied in the form of fertilizers becomes “inert” in the medium term and cannot be assimilated by plants. Rationalizing the use of phosphorus is a matter of extreme importance for environmental sustainability and socioeconomic development. Therefore, alternatives to the management of this nutrient are needed, and the use of P-solubilizing microorganisms is an option to optimize its use by crops, allowing the exploration of less available fractions of the nutrient in soils and reducing the demand for phosphate fertilizers. The objective of this study is to discuss the importance of phosphorus and how microorganisms can intermediate its sustainable use in agriculture. In this review study, we present several studies about the role of microorganisms as phosphorus mobilizers in the soil. We describe the importance of the nutrient for the plants and the main problems related to the unsustainable exploitation of its natural reserves and the use of chemical fertilizers. Mainly we highlight how microorganisms constitute a fundamental resource for the release of the inert portion of the nutrient, where we describe several mechanisms of solubilization and mineralization. We also discussed the benefits that the inoculation of P-solubilizing microorganisms provides to crops as well as practices of using them as bioinoculants. The use of microorganisms as inoculants is a viable resource for the future of sustainable agriculture, mainly because its application can significantly reduce the application of P and, consequently, reduce the exploitation of phosphorus and its reserves. In addition, new research must be conducted for the development of new technologies, prospecting new biological products, and improvement of management practices that allow for higher efficiency in the use of phosphorus in agriculture. Full article
(This article belongs to the Section Agricultural Soils)
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19 pages, 1370 KiB  
Review
SOLARIA-SensOr-driven resiLient and adaptive monitoRIng of farm Animals
Agriculture 2023, 13(2), 436; https://doi.org/10.3390/agriculture13020436 - 13 Feb 2023
Cited by 7 | Viewed by 1747
Abstract
Sensor-enabled big data and artificial intelligence platforms have the potential to address global socio-economic trends related to the livestock production sector through advances in the digitization of precision livestock farming. The increased interest in animal welfare, the likely reduction in the number of [...] Read more.
Sensor-enabled big data and artificial intelligence platforms have the potential to address global socio-economic trends related to the livestock production sector through advances in the digitization of precision livestock farming. The increased interest in animal welfare, the likely reduction in the number of animals in relation to population growth in the coming decade and the growing demand for animal proteins pose an acute challenge to prioritizing animal welfare on the one hand, while maximizing the efficiency of production systems on the other. Current digital approaches do not meet these challenges due to a lack of efficient and lack of real-time non-invasive precision measurement technologies that can detect and monitor animal diseases and identify resilience in animals. In this opinion review paper, I offer a critical view of the potential of wearable sensor technologies as a unique and necessary contribution to the global market for farm animal health monitoring. To stimulate the sustainable, digital and resilient recovery of the agricultural and livestock industrial sector, there is an urgent need for testing and developing new ideas and products such as wearable sensors. By validating and demonstrating a fully functional wearable sensor prototype within an operational environment on the livestock farm that includes a miniaturized animal-borne biosensor and an artificial intelligence (AI)-based data acquisition and processing platform, the current needs, which have not yet been met, can be fulfilled. The expected quantifiable results from wearable biosensors will demonstrate that the digitization technology can perform acceptably within the performance parameters specified by the agricultural sector and under operational conditions, to measurably improve livestock productivity and health. The successful implementation of the digital wearable sensor networks would provide actionable real-time information on animal health status and can be deployed directly on the livestock farm, which will strengthen the green and digital recovery of the economy due to its significant and innovative potential. Full article
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29 pages, 1878 KiB  
Review
Selenium Biofortification: Strategies, Progress and Challenges
Agriculture 2023, 13(2), 416; https://doi.org/10.3390/agriculture13020416 - 10 Feb 2023
Cited by 14 | Viewed by 3736
Abstract
Selenium (Se) is an essential trace element for humans and animals. Its necessity for plants is still under examination. Due to the contradictory nature of Se and its significance, it has received much interest in recent years. Se deficiency can be harmful to [...] Read more.
Selenium (Se) is an essential trace element for humans and animals. Its necessity for plants is still under examination. Due to the contradictory nature of Se and its significance, it has received much interest in recent years. Se deficiency can be harmful to humans, yet almost a billion people are deficient. Its deficiency has been associated with cancers, impairment of organs, and a number of other ailments. The biofortification of plants and livestock is a guaranteed practice to increase human selenium consumption. Strategies such as foliar spraying, the direct application of Se in plants and Se feed, and injections in livestock have been employed. Se biofortification has been shown to have additional beneficial effects in plants and livestock. In plants, it has been reported to mitigate different types of stress and increase yield. In animal biofortification, Se has been shown to reduce the detrimental effects of ailments and promote healthy growth. Se biofortification, nevertheless, confronts a number of difficulties. For instance, the bulk of biofortified products must be prepared before consumption, lowering the Se concentration. The objective of this review is to convey the current understanding of the Se biofortification of plants and animals, as well as its difficulties, taking into account both the detrimental consequences of Se deficiency and benefits of Se biofortification. Full article
(This article belongs to the Section Crop Production)
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17 pages, 1613 KiB  
Article
The Role of Green Agriculture and Green Supply Chain Management in the Green Intellectual Capital–Sustainable Performance Relationship: A Structural Equation Modeling Analysis Applied to the Spanish Wine Industry
Agriculture 2023, 13(2), 425; https://doi.org/10.3390/agriculture13020425 - 10 Feb 2023
Cited by 15 | Viewed by 3569
Abstract
The objective of this research is to analyze the mediating role of Green Supply Chain Management (GSCM) in the main Green Intellectual Capital (GIC) and Sustainable Performance (SP) relationship, as well as the moderating role of Green Agriculture (GA) in the GSCM–SP relationship. [...] Read more.
The objective of this research is to analyze the mediating role of Green Supply Chain Management (GSCM) in the main Green Intellectual Capital (GIC) and Sustainable Performance (SP) relationship, as well as the moderating role of Green Agriculture (GA) in the GSCM–SP relationship. To achieve this objective, a theoretical model is proposed based on the literature review and then analyzed using structural equation modeling (PLS-SEM) based on a sample of 196 Spanish wineries collected from September 2022 to January 2023. The results reveal that while GSCM partially mediates the GIC–SP relationship, GA positively but not significantly moderates the GSCM–SP relationship. To the best of our knowledge, there are no previous studies that have contextualized the model proposed in the wine industry, so the study represents the generation of new knowledge about the meaning of the relationships presented. Furthermore, no previous research has analyzed the moderating role of GA in the GSCM–SP relationship, so the study advances understanding of the variables that may affect this link (GSCM–SP). Full article
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19 pages, 3686 KiB  
Review
Advanced Continuous Monitoring System—Tools for Water Resource Management and Decision Support System in Salt Affected Delta
Agriculture 2023, 13(2), 369; https://doi.org/10.3390/agriculture13020369 - 03 Feb 2023
Cited by 10 | Viewed by 2495
Abstract
The greatest environmental problem facing the world today is climate change, with a rise in sea level being one of the most important consequences, especially in low-lying coastal areas, such as river deltas where changes are exacerbated by human impacts, leading to increased [...] Read more.
The greatest environmental problem facing the world today is climate change, with a rise in sea level being one of the most important consequences, especially in low-lying coastal areas, such as river deltas where changes are exacerbated by human impacts, leading to increased seawater intrusion into coastal aquifers and the degradation of water quality. Water quality monitoring systems are being developed and deployed to monitor changes in the aquatic environment. With technological progress, traditional sampling-based water monitoring has been supplemented with sensors and automated data acquisition and transmission devices, resulting in the automation of water quality monitoring systems. This paper reviews the recent development and application of automated continuous water quality monitoring systems. It also draws on the results of our own experience in implementing such a system in the Neretva River Delta on the Croatian Adriatic coast. The installed system provides (near) real-time data on parameters such as temperature, pH, EC, TDS, and DO in the water, as well as a number of soil and weather variables, with data available at a high frequency through a developed database and web portal for various stakeholders. Continuous monitoring enables the collection of big data that can be used to develop models for predictions of water quality parameters and to develop guidelines for future management. Full article
(This article belongs to the Section Agricultural Water Management)
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18 pages, 1124 KiB  
Review
Potential of Fruits and Vegetable By-Products as an Alternative Feed Source for Sustainable Ruminant Nutrition and Production: A Review
Agriculture 2023, 13(2), 286; https://doi.org/10.3390/agriculture13020286 - 25 Jan 2023
Cited by 7 | Viewed by 3170
Abstract
The agro-food industry produces tons of waste at different stages in the food production process, creating a massive ecological crisis. If implemented, the use of fruit and vegetable by-products (FVBPs) in animal nutrition has the potential to lessen the environmental footprint of the [...] Read more.
The agro-food industry produces tons of waste at different stages in the food production process, creating a massive ecological crisis. If implemented, the use of fruit and vegetable by-products (FVBPs) in animal nutrition has the potential to lessen the environmental footprint of the food production chain, lower animal feeding costs, and improve the quality and sustainability of animal products. Recent research on the inclusion of FVBPs, naturally enriched with polyphenols, in the diets of small and large ruminants has shown some promising outcomes, which we discuss in this review. The effects of FVBPs on digestion, rumen fermentation, methane emissions, rumen liquor fatty acid profile, and milk production are examined. Due to the chemical composition and the presence of certain bioactive compounds, FVBPs are capable of influencing the ruminal and intestinal ecosystem through improved kinetics of fermentation. Several in vivo studies have demonstrated that the dietary inclusion of FVBPs resulted in improved milk production and composition without any negative effect on animal performance. Using FVBPs as an alternative to conventional feedstuffs may promote sustainable animal production and nutrition. However, it must be stressed that the efficacy of these feed supplements is conditional on the source, kind, and quantity employed. Full article
(This article belongs to the Special Issue Agriculture Policy and Tools for Global Dairy Sector in the Future)
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23 pages, 796 KiB  
Review
Precision Livestock Farming Applications (PLF) for Grazing Animals
Agriculture 2023, 13(2), 288; https://doi.org/10.3390/agriculture13020288 - 25 Jan 2023
Cited by 16 | Viewed by 4148
Abstract
Over the past four decades the dietary needs of the global population have been elevated, with increased consumption of animal products predominately due to the advancing economies of South America and Asia. As a result, livestock production systems have expanded in size, with [...] Read more.
Over the past four decades the dietary needs of the global population have been elevated, with increased consumption of animal products predominately due to the advancing economies of South America and Asia. As a result, livestock production systems have expanded in size, with considerable changes to the animals’ management. As grazing animals are commonly grown in herds, economic and labour constraints limit the ability of the producer to individually assess every animal. Precision Livestock Farming refers to the real-time continuous monitoring and control systems using sensors and computer algorithms for early problem detection, while simultaneously increasing producer awareness concerning individual animal needs. These technologies include automatic weighing systems, Radio Frequency Identification (RFID) sensors for individual animal detection and behaviour monitoring, body temperature monitoring, geographic information systems (GIS) for pasture evaluation and optimization, unmanned aerial vehicles (UAVs) for herd management, and virtual fencing for herd and grazing management. Although some commercial products are available, mainly for cattle, the adoption of these systems is limited due to economic and cultural constraints and poor technological infrastructure. This review presents and discusses PLF applications and systems for grazing animals and proposes future research and strategies to improve PLF adoption and utilization in today’s extensive livestock systems. Full article
(This article belongs to the Section Agricultural Technology)
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21 pages, 1870 KiB  
Article
Simulated Climate Change Impacts on Corn and Soybean Yields in Buchanan County, Iowa
Agriculture 2023, 13(2), 268; https://doi.org/10.3390/agriculture13020268 - 22 Jan 2023
Cited by 7 | Viewed by 2908
Abstract
Projections of climate patterns through the end of the 21st century indicate varying impacts across the U.S. However, a common thread of these projections calls for increasing atmospheric temperatures in every region, some more pronounced than others. The significance of these projections for [...] Read more.
Projections of climate patterns through the end of the 21st century indicate varying impacts across the U.S. However, a common thread of these projections calls for increasing atmospheric temperatures in every region, some more pronounced than others. The significance of these projections for corn and soybean production cannot be overestimated. This study contributes to our understanding of climate change impacts on production and farm revenues by projecting their impacts on corn and soybean yields in Buchanan County, Iowa, a county in the center of the Corn Belt. Projections indicate that as atmospheric temperatures rise and precipitation levels vary markedly, the result is a significant decline in corn and soybean yields, the latter to a lesser extent, as compared to long-term yield trends. Depending upon the climate change scenario that will materialize, corn yields are projected to decline by up to 29%, while soybean yields are projected to decline by up to 24% from their normal upward trends by the year 2100. Due to the long-term upward trends in yields, corn and soybean yields will increase in absolute terms by the end of the century. Depending upon the climate change scenario, actual corn and soybean yields will increase by 30 to 57% and 30 to 66%, respectively, by the end of the 21st century, significantly less than they would have in the absence of these climate projections. Full article
(This article belongs to the Special Issue Natural Resource and Environmental Economics in Agriculture)
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13 pages, 2247 KiB  
Article
Multi-Environment Trials and Stability Analysis for Yield-Related Traits of Commercial Rice Cultivars
Agriculture 2023, 13(2), 256; https://doi.org/10.3390/agriculture13020256 - 20 Jan 2023
Cited by 7 | Viewed by 2769
Abstract
Multi-environment trials (METs) are essential in plant breeding programs to evaluate crop productivity and adaptability in diverse environments. In this study, we demonstrated the practical use of METs to evaluate grain yield and yield-related traits using 276 Korean rice cultivars, divided into three [...] Read more.
Multi-environment trials (METs) are essential in plant breeding programs to evaluate crop productivity and adaptability in diverse environments. In this study, we demonstrated the practical use of METs to evaluate grain yield and yield-related traits using 276 Korean rice cultivars, divided into three maturity groups (81 early-, 90 medium-, and 105 medium–late-maturing cultivars) grown in three regions (Jeonju, Suwon, and Miryang) and two planting seasons (early and regular planting) for two years. Due to the narrow genetic variability of the commercial cultivars, which are cultivated in relatively similar environmental conditions, genotype-by-environment interaction (GEI) effects were not statistically significant. However, genotype and environment evaluation using GGE biplot analysis exhibited distinct patterns of mega-environment formation, winning genotypes, ranking genotypes, discriminating power, and representativeness according to the differences in planting seasons and regions. Moreover, the simultaneous selection of stable high-performance genotypes using a weighted average of absolute scores from the singular-value decomposition of the matrix of BLUPs (WAASB) and a multi-trait stability index (MTSI) revealed six recommended genotypes each for early-maturing (Manho, Namil, Unkwang, Odae 1ho, Sinunbong 1ho, and Jonong) and medium-maturing (Sobi, Cheongdam, Shinbaeg, Boramchal, Mimyeon, and Saemimyeon) cultivars, and four genotypes for medium–late-maturing cultivars (Hanmauem, Dami, Baegseolchal, and Hangangchalbyeo). The winning genotypes of each trait can be used as parents to develop regional specialty cultivars by fine-tuning favorable traits, and recommended genotypes can be utilized as elite climate-resilient parents that can aid breeders in improving yield potential and stability across the planting seasons and regions. Full article
(This article belongs to the Topic Plant Breeding, Genetics and Genomics)
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26 pages, 12218 KiB  
Article
Cooperative Heterogeneous Robots for Autonomous Insects Trap Monitoring System in a Precision Agriculture Scenario
Agriculture 2023, 13(2), 239; https://doi.org/10.3390/agriculture13020239 - 19 Jan 2023
Cited by 13 | Viewed by 2334
Abstract
The recent advances in precision agriculture are due to the emergence of modern robotics systems. For instance, unmanned aerial systems (UASs) give new possibilities that advance the solution of existing problems in this area in many different aspects. The reason is due to [...] Read more.
The recent advances in precision agriculture are due to the emergence of modern robotics systems. For instance, unmanned aerial systems (UASs) give new possibilities that advance the solution of existing problems in this area in many different aspects. The reason is due to these platforms’ ability to perform activities at varying levels of complexity. Therefore, this research presents a multiple-cooperative robot solution for UAS and unmanned ground vehicle (UGV) systems for their joint inspection of olive grove inspect traps. This work evaluated the UAS and UGV vision-based navigation based on a yellow fly trap fixed in the trees to provide visual position data using the You Only Look Once (YOLO) algorithms. The experimental setup evaluated the fuzzy control algorithm applied to the UAS to make it reach the trap efficiently. Experimental tests were conducted in a realistic simulation environment using a robot operating system (ROS) and CoppeliaSim platforms to verify the methodology’s performance, and all tests considered specific real-world environmental conditions. A search and landing algorithm based on augmented reality tag (AR-Tag) visual processing was evaluated to allow for the return and landing of the UAS to the UGV base. The outcomes obtained in this work demonstrate the robustness and feasibility of the multiple-cooperative robot architecture for UGVs and UASs applied in the olive inspection scenario. Full article
(This article belongs to the Special Issue Application of Robots and Automation Technology in Agriculture)
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30 pages, 4134 KiB  
Review
Soil Bioplastic Mulches for Agroecosystem Sustainability: A Comprehensive Review
Agriculture 2023, 13(1), 197; https://doi.org/10.3390/agriculture13010197 - 12 Jan 2023
Cited by 9 | Viewed by 4138
Abstract
The use of plastic mulch films is widespread in agriculture for specialty cropping systems because of several benefits. In this article, we critically review, for the first time under a holistic approach, the use of biodegradable plastic mulches (BdPMs) in soil as a [...] Read more.
The use of plastic mulch films is widespread in agriculture for specialty cropping systems because of several benefits. In this article, we critically review, for the first time under a holistic approach, the use of biodegradable plastic mulches (BdPMs) in soil as a sustainable alternative to conventional petroleum-based plastics, highlighting the current state of understanding of their degradation in soil and their effect on soil microorganisms, weed control, and soil properties. In addition, we provide a detailed focus on the history and economic importance of mulching. BdPMs are effective for use in vegetable production in that they improve physical, chemical, and biological soil properties, as well as enhancing microbial biodiversity, controlling weeds, and maintaining soil moisture. BdPMs could be useful to limit the use of agrochemicals and reduce tillage and irrigation supplies for sustainable management. Full article
(This article belongs to the Special Issue Advanced Research of Soil Microbial Functional Diversity)
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21 pages, 4557 KiB  
Article
Blockchain Traceability Adoption in Agricultural Supply Chain Coordination: An Evolutionary Game Analysis
Agriculture 2023, 13(1), 184; https://doi.org/10.3390/agriculture13010184 - 11 Jan 2023
Cited by 18 | Viewed by 3938
Abstract
Blockchain technology has brought about profound revolutions in supply chain management. Notably, in the agricultural sector, blockchain-based traceability has become an essential tool to maintain the safety and quality of farm commodities. However, the implementation of blockchain technology in agricultural traceability is not [...] Read more.
Blockchain technology has brought about profound revolutions in supply chain management. Notably, in the agricultural sector, blockchain-based traceability has become an essential tool to maintain the safety and quality of farm commodities. However, the implementation of blockchain technology in agricultural traceability is not prevalent. In this paper, mathematical modeling and simulation methods were used to investigate the decision making regarding the adoption of blockchain traceability in agriculture, which comprises producers, processors, and governments. This paper provides further analysis of the optimal blockchain-based traceability strategies of the members of the agricultural product supply chain in different scenarios. The results reveal the following: (1) Producers and processors should manage the traceability costs for adopting blockchains to improve their brand image and gain more benefits. (2) The government should encourage supply chain agents to participate in traceability by establishing an effective reward-and-punishment mechanism. In addition, the research will help agricultural supply chain agents to design strategies to implement traceability in agriculture and create a transparent and efficient data-driven agricultural products supply chain. Furthermore, these findings provide guidance to policymakers to develop policies to accelerate the implementation of blockchain-based traceability systems to guarantee fraud-free and sustainable agricultural supply chains. Full article
(This article belongs to the Section Agricultural Technology)
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22 pages, 2517 KiB  
Review
Role of Halotolerant Plant Growth-Promoting Rhizobacteria in Mitigating Salinity Stress: Recent Advances and Possibilities
Agriculture 2023, 13(1), 168; https://doi.org/10.3390/agriculture13010168 - 09 Jan 2023
Cited by 5 | Viewed by 3526
Abstract
Soil salinity is one of the major abiotic constraints in agricultural ecosystems worldwide. High salinity levels have negative impacts on plant growth and yield, and affect soil physicochemical properties. Salinity also has adverse effects on the distribution and abundance of soil microorganisms. Salinity [...] Read more.
Soil salinity is one of the major abiotic constraints in agricultural ecosystems worldwide. High salinity levels have negative impacts on plant growth and yield, and affect soil physicochemical properties. Salinity also has adverse effects on the distribution and abundance of soil microorganisms. Salinity problems have previously been addressed in research, but most approaches, such as breeding for salt tolerant varieties and soil amelioration, are expensive and require years of efforts. Halotolerant plant growth-promoting rhizobacteria (HT-PGPR) secrete secondary metabolites, including osmoprotectants, exopolysaccharides, and volatile organic compounds. The importance of these compounds in promoting plant growth and reducing adverse effects under salinity stress has now been widely recognised. HT-PGPR are emerging as effective biological strategies for mitigating the harmful effects of high salinity; improving plant growth, development, and yield; and remediating degraded saline soils. This review describes the beneficial effects and growth-promoting mechanisms of various HT-PGPR, which are carried out by maintaining ion homeostasis, increasing nutrient availability, and the producing secondary metabolites, osmoprotectants, growth hormones, and volatile organic compounds. Exploring suitable HT-PGPR and applications in agriculture production systems can play a crucial role in reducing the adverse impacts of salinity stress and sustainable crop productivity. Full article
(This article belongs to the Section Crop Production)
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20 pages, 5318 KiB  
Article
Simulation Analysis and Experiments for Blade-Soil-Straw Interaction under Deep Ploughing Based on the Discrete Element Method
Agriculture 2023, 13(1), 136; https://doi.org/10.3390/agriculture13010136 - 05 Jan 2023
Cited by 8 | Viewed by 2254
Abstract
The desirable sowing period for winter wheat is very short in the rice-wheat rotation areas. There are also lots of straw left in harvested land. Deep rotary tillage can cover rice straw under the surface to increase soil organic matter. Clarifying the effect [...] Read more.
The desirable sowing period for winter wheat is very short in the rice-wheat rotation areas. There are also lots of straw left in harvested land. Deep rotary tillage can cover rice straw under the surface to increase soil organic matter. Clarifying the effect of the rotary tillage blade on the soil and straw, as well as analyzing the movement patterns and forces on the straw and soil, are essential to investigate the deep rotary tillage process in order to solve the problems of energy consumption and poor straw burial effect of deep tillage and deep burial machinery. In this study, we built the interaction model of rotary blade-soil-straw through the discrete element method to conduct simulation and identified the factors that affect the power consumption and operation quality of the rotary blade. The simulation process reflects the law of rotary blade-soil-straw interaction, and the accuracy of the simulation model has been verified by field trials. The simulation test results show that the optimized structural parameters of the rotary tillage blade were 210 mm, 45 mm, 37° and 115° (R, H, α and β) designed based on this theoretical model can cultivate to a depth of 200 mm. The operating parameters were 8π rad/s for rotational speed and 0. 56 m/s for forward speed, respectively; the simulated and field comparison tests were conducted under the optimal combination of parameters, and the power, soil breaking rate, and straw burial rate were 1.73 kW, 71.34%, and 18.89%, respectively; the numerical error rates of simulated and field test values were 6.36%, 5.42%, and 8.89%, respectively. The accuracy of the secondary model was verified. The simulation model had good accuracy at all factor levels. The model constructed in this study can provide a theoretical basis and technical reference for the interaction mechanism between rotary tillage and soil straw, the optimization of machine geometry, and the selection of operating parameters. Full article
(This article belongs to the Special Issue 'Eyes', 'Brain', 'Feet' and 'Hands' of Efficient Harvesting Machinery)
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28 pages, 3007 KiB  
Review
Responses of Soybean to Selected Abiotic Stresses—Photoperiod, Temperature and Water
Agriculture 2023, 13(1), 146; https://doi.org/10.3390/agriculture13010146 - 05 Jan 2023
Cited by 12 | Viewed by 2957
Abstract
The sharp increase in soybean (Glycine max (L.) Merrill) acreage in the late 20th century and early 21st century is due to the demand for edible oil and feed protein. However, a limiting factor in the extent of soybean cultivation is its [...] Read more.
The sharp increase in soybean (Glycine max (L.) Merrill) acreage in the late 20th century and early 21st century is due to the demand for edible oil and feed protein. However, a limiting factor in the extent of soybean cultivation is its high heat requirements and response to photoperiod. Most varieties are short-day plants and are generally the best-yielding genotypes. At higher latitudes (longer day length), there is a delay in the occurrence of subsequent developmental stages and problems with plant maturation before the onset of autumn frost. Global warming allows the cultivation range of warm-season species (including soya) to be shifted; however, periodic droughts and very high temperatures limit crop production. Adverse weather events result in a reduction in soybean seed yield of around 30%. Environmental stresses related to day length, high and low temperatures and water shortage or excess have the greatest impact on soybean yields, as we have no influence on them and can only, to a very limited extent, offset their negative effects. This paper reviews the recent world literature on how soybean responds to these stress factors. The results of our own research were also used. Full article
(This article belongs to the Special Issue Legumes: Advances in Breeding, Productivity and Quality)
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17 pages, 387 KiB  
Article
Meat Quality in Rabbit (Oryctolagus cuniculus) and Hare (Lepus europaeus Pallas)—A Nutritional and Technological Perspective
Agriculture 2023, 13(1), 126; https://doi.org/10.3390/agriculture13010126 - 03 Jan 2023
Cited by 5 | Viewed by 4576
Abstract
This study aimed to nutritionally and technologically characterize the meat produced by rabbit (Oryctolagus cuniculus, Flemish Giant breed, 50 farmed individuals) and hare (Lepus europaeus Pallas, 50 hunted individuals). Muscles were sampled from several carcass regions: dorsal torso—Longissimus [...] Read more.
This study aimed to nutritionally and technologically characterize the meat produced by rabbit (Oryctolagus cuniculus, Flemish Giant breed, 50 farmed individuals) and hare (Lepus europaeus Pallas, 50 hunted individuals). Muscles were sampled from several carcass regions: dorsal torso—Longissimus dorsi (LD), thigh—Semimembranosus (SM), and upper arm—Triceps brachii (TB). To better depict the meat’s nutritional quality, the proximate composition and fatty acid profile were assessed, and then gross energy content and lipid sanogenic indices (Polyunsaturation—PI, atherogenic—AI, thrombogenic—TI, hypocholersyerolemic/hypercholesterolemic ratio—h/H, Nutritional Value Index—NVI) were calculated. pH values at 24 and 48 h post-slaughter, cooking loss (CL), and water-holding capacity (WHC) were the investigated technological quality traits. Gross energy was higher in rabbit TB samples, compared with hare, due to more accumulated lipids (p < 0.001). pH value was higher for TB muscles in both species; the WHC was higher for hare (p < 0.001), and CL was higher for rabbit (p < 0.001). The PI values were 6.72 in hare and 4.59 in rabbit, AI reached 0.78 in hare and 0.73 in rabbit, TI was calculated at 0.66 in hare and 0.39 in rabbit, and the h/H ratio reached 3.57 in hare and 1.97 in rabbit, while the NVI was 1.48 in hare and 1.34 in rabbit samples. Meat from both species is nutritionally valuable for human consumers, meeting nutritional values better than the meat of farmed or other wild species of fowl and mammals. Hare meat was found to be healthier than rabbit in terms of lower fat content, lighter energy, and better lipid health indices. Full article
(This article belongs to the Special Issue Animal Nutrition and Productions)
18 pages, 6965 KiB  
Article
Apple Grading Method Design and Implementation for Automatic Grader Based on Improved YOLOv5
Agriculture 2023, 13(1), 124; https://doi.org/10.3390/agriculture13010124 - 02 Jan 2023
Cited by 29 | Viewed by 3620
Abstract
Apple grading is an essential part of the apple marketing process to achieve high profits. In this paper, an improved YOLOv5 apple grading method is proposed to address the problems of low grading accuracy and slow grading speed in the apple grading process [...] Read more.
Apple grading is an essential part of the apple marketing process to achieve high profits. In this paper, an improved YOLOv5 apple grading method is proposed to address the problems of low grading accuracy and slow grading speed in the apple grading process and is experimentally verified by the designed automatic apple grading machine. Firstly, the Mish activation function is used instead of the original YOLOv5 activation function, which allows the apple feature information to flow in the deep network and improves the generalization ability of the model. Secondly, the distance intersection overUnion loss function (DIoU_Loss) is used to speed up the border regression rate and improve the model convergence speed. In order to refine the model to focus on apple feature information, a channel attention module (Squeeze Excitation) was added to the YOLOv5 backbone network to enhance information propagation between features and improve the model’s ability to extract fruit features. The experimental results show that the improved YOLOv5 algorithm achieves an average accuracy of 90.6% for apple grading under the test set, which is 14.8%, 11.1%, and 3.7% better than the SSD, YOLOv4, and YOLOv5s models, respectively, with a real-time grading frame rate of 59.63 FPS. Finally, the improved YOLOv5 apple grading algorithm is experimentally validated on the developed apple auto-grader. The improved YOLOv5 apple grading algorithm was experimentally validated on the developed apple auto grader. The experimental results showed that the grading accuracy of the automatic apple grader reached 93%, and the grading speed was four apples/sec, indicating that this method has a high grading speed and accuracy for apples, which is of practical significance for advancing the development of automatic apple grading. Full article
(This article belongs to the Special Issue Robots and Autonomous Machines for Agriculture Production)
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18 pages, 7567 KiB  
Article
Research on Flexible End-Effectors with Humanoid Grasp Function for Small Spherical Fruit Picking
Agriculture 2023, 13(1), 123; https://doi.org/10.3390/agriculture13010123 - 02 Jan 2023
Cited by 8 | Viewed by 2364
Abstract
The rapid, stable, and undamaged picking of small-sized spherical fruits are one of the key technologies to improve the level of intelligent picking robots and reduce grading operations. Cherry tomatoes were selected as the research object in this work. Picking strategies of two-stage [...] Read more.
The rapid, stable, and undamaged picking of small-sized spherical fruits are one of the key technologies to improve the level of intelligent picking robots and reduce grading operations. Cherry tomatoes were selected as the research object in this work. Picking strategies of two-stage “Holding-Rotating” and finger-end grasping were determined. The end-effector was designed to separate the fruit from the stalk based on the linear motion of the constraint part and the rotating gripper. This work first studied the human hand-grasping of cherry tomatoes and designed the fingers with sinusoidal characteristics. The mathematical model of a single finger of the gripper was established. The structural parameters of the gripper were determined to meet the requirements of the grabbing range from 0 to 61.6 mm. Based on the simulation model, the constraint part was set to 6 speeds, and the fruit sizes were set to 20 mm, 30 mm, and 40 mm, respectively. When the speed was 0.08m/s, the results showed that the grabbing time was 0.5381 s, 0.387 s, and 0.2761 s, respectively, and the maximum grabbing force was 0.9717 N, 3.5077 N, and 4.0003 N now of clamping, respectively. It met the picking requirements of high speed and low loss. The criterions of two-index stability and undamaged were proposed, including the grasping index of the fixed value and the slip detection of variance to mean ratio. Therefore, the control strategy and algorithm based on two-stage and two-index for rapid, stable, and non-destructive harvesting of small fruit were proposed. The results of the picking experiment for seventy-two cherry tomatoes showed that the picking success rate was 95.82%, the average picking time was 4.86 s, the picking damage rate was 2.90%, the browning rate was 2.90% in 72 h, and the wrinkling rate was 1.49% in 72 h, which can meet the actual small spherical fruit picking requirements. The research will provide an idea for the flexible end-effectors with humanoid grasp function and provides a theoretical reference for small spherical fruit picking. Full article
(This article belongs to the Special Issue 'Eyes', 'Brain', 'Feet' and 'Hands' of Efficient Harvesting Machinery)
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17 pages, 1262 KiB  
Article
Does Ecological Agriculture Moderate the Relationship between Wine Tourism and Economic Performance? A Structural Equation Analysis Applied to the Ribera del Duero Wine Context
Agriculture 2022, 12(12), 2143; https://doi.org/10.3390/agriculture12122143 - 13 Dec 2022
Cited by 13 | Viewed by 2111
Abstract
The purpose of this research is to analyze the effect of wine tourism activity on economic performance in the wine context of Ribera del Duero (Spain), as well as the mediating effect of ecological agriculture on this link. To this end, a conceptual [...] Read more.
The purpose of this research is to analyze the effect of wine tourism activity on economic performance in the wine context of Ribera del Duero (Spain), as well as the mediating effect of ecological agriculture on this link. To this end, a conceptual model is proposed based on the literature review carried out and contrasted through structural equation modelling (PLS-SEM) with data from 263 wineries, which in turn represent the population under study. The study results allow for us to empirically demonstrate the positive and significant relationship of wine tourism on performance, as well as the partial mediation of ecological agriculture in this relationship. The study thus contributes to the academic literature in a remarkable way given that, to our knowledge, there are no previous studies that have addressed the mediating role of ecological agriculture in the wine tourism–economic performance link. However, the research also suffers from certain limitations. In particular, given the relevance of the study, it is necessary to broaden its geographical scope so that, as a future line of research, it is proposed to contextualize the model proposed in the California wine industry, being able to subsequently establish similarities and differences in the Old and New World. Full article
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11 pages, 2493 KiB  
Article
Sustainable Bioconversion of Wetland Plant Biomass for Pleurotus ostreatus var. florida Cultivation: Studies on Proximate and Biochemical Characterization
Agriculture 2022, 12(12), 2095; https://doi.org/10.3390/agriculture12122095 - 07 Dec 2022
Cited by 25 | Viewed by 2256
Abstract
The abundant biomass growth of aquatic macrophytes in wetlands is one of the major concerns affecting their residing biota. Moreover, the biomass degenerates within the wetlands, thereby causing a remixing of nutrients and emission of greenhouse gases. Therefore, it is crucial to find [...] Read more.
The abundant biomass growth of aquatic macrophytes in wetlands is one of the major concerns affecting their residing biota. Moreover, the biomass degenerates within the wetlands, thereby causing a remixing of nutrients and emission of greenhouse gases. Therefore, it is crucial to find sustainable methods to utilize the biomass of aquatic macrophytes devoid of environmental concerns. The present study investigates the utilization of the biomass of three aquatic macrophytes, including the lake sedge (CL: Carex lacustris Willd.), water hyacinth (EC: Eichhornia crassipes Mart. Solms), and sacred lotus (NL: Nelumbo nucifera Gaertn.) to produce oyster (Pleurotus ostreatus var. florida) mushrooms. For this purpose, different combinations of wheat straw (WS: as control) and macrophyte’s biomass (WH) such as control (100% WH), CL50 (50% WH + 50% CL), CL100 (100% CL), EC50 (50% WH + 50% EC), EC100 (100% EC), NL50 (50% WH + 50% NL), and NL100 (100% NL) were used for P. florida cultivation under controlled laboratory conditions. The results showed that all selected combinations of wheat straw and macrophyte biomass supported the spawning and growth of P. florida. In particular, the maximum significant (p < 0.05) growth, yield, bioefficiency, proximate, and biochemical parameters were reported using the WH substrate followed by CL, NL, and EC biomass, which corresponds to the reduction efficiency of the substrate parameters. Therefore, the findings of this study reveal that the biomass of selected aquatic macrophytes can be effectively utilized for sustainable mushroom cultivation while minimizing the risk associated with their self-degeneration. Full article
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26 pages, 565 KiB  
Article
Re-Measurement of Agriculture Green Total Factor Productivity in China from a Carbon Sink Perspective
Agriculture 2022, 12(12), 2025; https://doi.org/10.3390/agriculture12122025 - 27 Nov 2022
Cited by 10 | Viewed by 1761
Abstract
Accurate measurement of agricultural total factor productivity (AGTFP) is crucial to measure the level of sustainable agricultural development, and agricultural carbon sink is an important element to leverage the development of green transformation. Few studies have incorporated agricultural carbon sink into the measurement [...] Read more.
Accurate measurement of agricultural total factor productivity (AGTFP) is crucial to measure the level of sustainable agricultural development, and agricultural carbon sink is an important element to leverage the development of green transformation. Few studies have incorporated agricultural carbon sink into the measurement framework of AGTFP, and the evolutionary dynamics and related spatial effects of Chinese AGTFP from the perspective of carbon sinks are unclear. On this basis, the paper used a provincial-level agricultural panel data set of China from 2000 to 2019 to measure the provincial indicators of agricultural carbon sinks, CO2 emissions and agricultural non-point source pollution. Then, we incorporated these environmental factors into the measurement framework of AGTFP and used the SBM-DEA model to calculate the Chinese AGTFP from the perspective of carbon sinks. We further analyzed the spatial and temporal divergence and convergence of AGTFP in China using Moran’I and spatial econometric models. We found that after measuring AGTFP, including agricultural carbon sinks, 28 out of 30 Chinese provinces showed an increased trend, but the development gap between regions was obvious. The spatial econometric model showed a significantly positive spatial correlation between the AGTFP of each province and did not have absolute α-convergence and absolute β-convergence characteristics. After adding the control variables of resource endowment of each province, it showed conditional β-convergence characteristics, and the spatial spillover effect of China’s AGTFP was increasing. Finally, the paper proposed policy recommendations for the sustainable and coordinated development of China’s agricultural regions in response to the research findings. Full article
(This article belongs to the Special Issue Sustainable Agriculture: Theories, Methods, Practices and Policies)
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17 pages, 4761 KiB  
Article
The Theory of Agriculture Multifunctionality on the Example of Private Households
Agriculture 2022, 12(11), 1870; https://doi.org/10.3390/agriculture12111870 - 08 Nov 2022
Cited by 16 | Viewed by 3058
Abstract
Having appeared in the European Union, the multifunctionality theory was quickly appreciated in most countries of the world. It determines the role of agriculture and its structural elements in the modern economy. This article is aimed at studying the multifunctionality theory in Russia. [...] Read more.
Having appeared in the European Union, the multifunctionality theory was quickly appreciated in most countries of the world. It determines the role of agriculture and its structural elements in the modern economy. This article is aimed at studying the multifunctionality theory in Russia. This study was conducted on the example of private farms in the Samara region by the authors’ classification and identifying their main functions can serve as the basis for a system of their state support. To process the study results, absolute, relative, and average values were used, as well as a regression analysis with the help of the STATISTICA package. The research results are presented in tabular and graphical forms. The growth of production volumes does not lead to an increase in the share of households according to total volume in the case of a steady trend. The impact of all factors on the indicator, except for the production volume amount, results in a 2.272% decrease in the proportion of household plots in the total volume of agricultural regional production annually. It was found that the parameters of households depend mainly not on the geographical location within the region but on the size of the settlements in which they are located. The research result shows that the main focus of state regulation for private farms should be aimed at their support in small settlements, thus ensuring a quick return on invested budget funds. The outcome of the multifunctionality theory in practice should be the strengthening of state support for private farms. Full article
(This article belongs to the Special Issue Agricultural Insurance, Risk Management and Sustainable Development)
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13 pages, 7859 KiB  
Article
Risk Assessment of Heavy Metals Contamination in Soil and Two Rice (Oryza sativa L.) Varieties Irrigated with Paper Mill Effluent
Agriculture 2022, 12(11), 1864; https://doi.org/10.3390/agriculture12111864 - 06 Nov 2022
Cited by 23 | Viewed by 2367
Abstract
Heavy metal pollution from industrial wastewaters has become an issue of global concern. These wastewaters are frequently used for inland irrigation which possess a serious risk of heavy metal contamination of both soil and cultivated crops. The problem is more common in developing [...] Read more.
Heavy metal pollution from industrial wastewaters has become an issue of global concern. These wastewaters are frequently used for inland irrigation which possess a serious risk of heavy metal contamination of both soil and cultivated crops. The problem is more common in developing countries like India where industrial wastewaters are often discharged without appropriate treatments. Therefore, this study aimed at assessing the impact of paper mill effluent for irrigation on the growth, productivity, and heavy metal accumulation potential of two rice (Oryza sativa L.) varieties (PB-1121 and PR-121). Water, soil, and rice crop samples were obtained from the vicinity of Saharanpur city, Uttar Pradesh, India, and subsequently analyzed for selected physicochemical and heavy metal parameters. Results showed that paper mill effluent and nearby Kali River water had significant (p < 0.05) loads of pollutants that impacted the soil properties. Moreover, the maximum plant height (123.48 ± 4.86 and 98.83 ± 2.02 cm); total chlorophyll (6.70 ± 0.25 and 6.64 ± 0.17 mg/g); leaf carotenoids (0.67 ± 0.08 and 0.63 ± 0.05 mg/g); starch content (71.08 ± 2.05 and 72.60 ± 1.63%); amylose content (25.10 ± 1.32 and 20.28 ± 1.24%); crop yield (4270.20 ± 75.12 and 5830.58 ± 63.10 kg/ha); and straw yield (5472.05 ± 93.90 and 6683.76 ± 61.26 kg/ha) of PB-1121 and PR-121, respectively, were observed using Kali River water irrigation source as compared to paper mill effluent and borewell water. The order of heavy metal accumulation in rice straw and grain followed: Fe > Mn > Zn > Cu > Cr > Cd. Similarly, the bioaccumulation factors for heavy metals in rice straw and grain were observed as >1 and <1, respectively. Moreover, the target hazard quotient (THQ) showed that there was no potential health risk of heavy metal in rice irrigated with contaminated water supply except for the PR-121 variety irrigated with Kali River water where the health risk index (HRI) value exceeded the limit (>1). As a result, the findings of this study provide useful information about the current state of heavy metal pollution and the health risks associated with rice crops irrigated with contaminated water sources. Full article
(This article belongs to the Special Issue Agricultural Environmental Pollution, Risk Assessment, and Control)
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16 pages, 3032 KiB  
Article
Measurement and Spatial–Temporal Characteristics of Agricultural Carbon Emission in China: An Internal Structural Perspective
Agriculture 2022, 12(11), 1749; https://doi.org/10.3390/agriculture12111749 - 22 Oct 2022
Cited by 17 | Viewed by 2160
Abstract
The focus of world governance on climate change has been on the industrial and transport sectors, yet the agricultural sector produces a lot of greenhouse gases, and this has always been ignored. This paper focuses on China, one of the world’s largest agricultural [...] Read more.
The focus of world governance on climate change has been on the industrial and transport sectors, yet the agricultural sector produces a lot of greenhouse gases, and this has always been ignored. This paper focuses on China, one of the world’s largest agricultural countries, and it investigates its agriculture carbon emission from a new perspective of the internal structure of it, which is relatively under-researched. Carbon metrology, the emission factor method and kernel density estimations are used to analyze China’s agricultural carbon emissions structure and its regional differences and its dynamic evolution characteristics. We find that: (1) China’s total amount of agricultural carbon emissions showed a ladder-like upward trend, but the growth rate of it has gradually slowed down; the inter-provincial heterogeneity of the agricultural carbon emissions was obvious. (2) From the standpoint of the grain functional areas, the annual total amount of agricultural carbon emissions and the amount of carbon emissions of each carbon source in the major grain producing areas were significantly higher than those in the major grain sales areas and the production–sales balance areas, and the carbon emission intensity in the major grain producing areas was the lowest overall. (3) In regard to the internal structure, China’s agricultural carbon emissions mainly came from the livestock and poultry, rice planting and agricultural energy sectors; the proportion of carbon emissions that were caused by the agricultural materials, agricultural energy and soil increased in general, and the inter-provincial differences between them expanded, while the inter-provincial differences between livestock and poultry gradually decreased. The proportion of carbon emissions from the six major agricultural carbon sources showed a convergence trend, and their kernel density had a right tail phenomenon. Our research deepens the understanding of China’s agricultural carbon emission structure, contributes to the rational optimization of the agricultural structure, and helps the agriculture sector and the rural areas to reach the carbon peak. Full article
(This article belongs to the Special Issue Energy Economics and Low Carbon Policy in the Agriculture Sector)
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26 pages, 3156 KiB  
Review
Smart Farming: Internet of Things (IoT)-Based Sustainable Agriculture
Agriculture 2022, 12(10), 1745; https://doi.org/10.3390/agriculture12101745 - 21 Oct 2022
Cited by 64 | Viewed by 73351
Abstract
Smart farming is a development that has emphasized information and communication technology used in machinery, equipment, and sensors in network-based hi-tech farm supervision cycles. Innovative technologies, the Internet of Things (IoT), and cloud computing are anticipated to inspire growth and initiate the use [...] Read more.
Smart farming is a development that has emphasized information and communication technology used in machinery, equipment, and sensors in network-based hi-tech farm supervision cycles. Innovative technologies, the Internet of Things (IoT), and cloud computing are anticipated to inspire growth and initiate the use of robots and artificial intelligence in farming. Such ground-breaking deviations are unsettling current agriculture approaches, while also presenting a range of challenges. This paper investigates the tools and equipment used in applications of wireless sensors in IoT agriculture, and the anticipated challenges faced when merging technology with conventional farming activities. Furthermore, this technical knowledge is helpful to growers during crop periods from sowing to harvest; and applications in both packing and transport are also investigated. Full article
(This article belongs to the Special Issue Digital Innovations in Agriculture)
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13 pages, 4001 KiB  
Article
Winter Wheat Yield Prediction Using an LSTM Model from MODIS LAI Products
Agriculture 2022, 12(10), 1707; https://doi.org/10.3390/agriculture12101707 - 17 Oct 2022
Cited by 22 | Viewed by 2719
Abstract
Yield estimation using remote sensing data is a research priority in modern agriculture. The rapid and accurate estimation of winter wheat yields over large areas is an important prerequisite for food security policy formulation and implementation. In most county-level yield estimation processes, multiple [...] Read more.
Yield estimation using remote sensing data is a research priority in modern agriculture. The rapid and accurate estimation of winter wheat yields over large areas is an important prerequisite for food security policy formulation and implementation. In most county-level yield estimation processes, multiple input data are used for yield prediction as much as possible, however, in some regions, data are more difficult to obtain, so we used the single-leaf area index (LAI) as input data for the model for yield prediction. In this study, the effects of different time steps as well as the LAI time series on the estimation results were analyzed for the properties of long short-term memory (LSTM), and multiple machine learning methods were compared with yield estimation models constructed by the LSTM networks. The results show that the accuracy of the yield estimation results using LSTM did not show an increasing trend with the increasing step size and data volume, while the yield estimation results of the LSTM were generally better than those of conventional machine learning methods, with the best R2 and RMSE results of 0.87 and 522.3 kg/ha, respectively, in the comparison between predicted and actual yields. Although the use of LAI as a single input factor may cause yield uncertainty in some extreme years, it is a reliable and promising method for improving the yield estimation, which has important implications for crop yield forecasting, agricultural disaster monitoring, food trade policy, and food security early warning. Full article
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24 pages, 11847 KiB  
Article
Salicylic Acid Modulates Okra Tolerance to Salt Stress in Hydroponic System
Agriculture 2022, 12(10), 1687; https://doi.org/10.3390/agriculture12101687 - 13 Oct 2022
Cited by 13 | Viewed by 2053
Abstract
Salinity is one of the most devastating abiotic stresses that limit plant growth and yield, especially in arid and semi-arid regions. The objective of this study was to evaluate the effect of foliar application of salicylic acid in mitigating the effects of salt [...] Read more.
Salinity is one of the most devastating abiotic stresses that limit plant growth and yield, especially in arid and semi-arid regions. The objective of this study was to evaluate the effect of foliar application of salicylic acid in mitigating the effects of salt stress on okra cultivation in a hydroponic system. The study was conducted in a greenhouse, consisting of two experiments. A completely randomized design was adopted in a split-plot scheme, with four levels of electrical conductivity of the nutrient solution—EC (2.1; 3.6; 5.1, and 6.6 dS m−1) considered the plots and four salicylic acid concentrations—SA (0, 1.2; 2.4, and 3.6 mM), the subplots, with four replications. The second experiment differed from the first only by the increase in the EC levels (3.0, 5.0, 7.0, and 9.0 dS m−1). An increase in the electrical conductivity of the nutrient solution negatively affected the physiology and production components of okra. However, foliar application of salicylic acid at concentrations between 1.2 and 2.3 mM reduced the harmful effects of salt stress. The salinity threshold for hydroponic cultivation of okra was 2.54 dS m−1, with a reduction of 7.98% per unit increment in EC above this level. Full article
(This article belongs to the Special Issue New Insights into Crop Response and Tolerance to Salinity Stress)
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18 pages, 6114 KiB  
Article
An Attention Mechanism-Improved YOLOv7 Object Detection Algorithm for Hemp Duck Count Estimation
Agriculture 2022, 12(10), 1659; https://doi.org/10.3390/agriculture12101659 - 10 Oct 2022
Cited by 64 | Viewed by 12554
Abstract
Stocking density presents a key factor affecting livestock and poultry production on a large scale as well as animal welfare. However, the current manual counting method used in the hemp duck breeding industry is inefficient, costly in labor, less accurate, and prone to [...] Read more.
Stocking density presents a key factor affecting livestock and poultry production on a large scale as well as animal welfare. However, the current manual counting method used in the hemp duck breeding industry is inefficient, costly in labor, less accurate, and prone to double counting and omission. In this regard, this paper uses deep learning algorithms to achieve real-time monitoring of the number of dense hemp duck flocks and to promote the development of the intelligent farming industry. We constructed a new large-scale hemp duck object detection image dataset, which contains 1500 hemp duck object detection full-body frame labeling and head-only frame labeling. In addition, this paper proposes an improved attention mechanism YOLOv7 algorithm, CBAM-YOLOv7, adding three CBAM modules to the backbone network of YOLOv7 to improve the network’s ability to extract features and introducing SE-YOLOv7 and ECA-YOLOv7 for comparison experiments. The experimental results show that CBAM-YOLOv7 had higher precision, and the recall, [email protected], and [email protected]:0.95 were slightly improved. The evaluation index value of CBAM-YOLOv7 improved more than those of SE-YOLOv7 and ECA-YOLOv7. In addition, we also conducted a comparison test between the two labeling methods and found that the head-only labeling method led to the loss of a high volume of feature information, and the full-body frame labeling method demonstrated a better detection effect. The results of the algorithm performance evaluation show that the intelligent hemp duck counting method proposed in this paper is feasible and can promote the development of smart reliable automated duck counting. Full article
(This article belongs to the Special Issue Internet and Computers for Agriculture)
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16 pages, 670 KiB  
Article
Impact of Off-Farm Employment on Farmland Transfer: Insight on the Mediating Role of Agricultural Production Service Outsourcing
Agriculture 2022, 12(10), 1617; https://doi.org/10.3390/agriculture12101617 - 05 Oct 2022
Cited by 20 | Viewed by 1489
Abstract
Understanding the effects of the off-farm employment of rural laborers on agricultural land use is essential to promote farmland transfer and enhance rural development in China. This study aims to investigate the direct impact of off-farm employment on farmland transfer and the mediating [...] Read more.
Understanding the effects of the off-farm employment of rural laborers on agricultural land use is essential to promote farmland transfer and enhance rural development in China. This study aims to investigate the direct impact of off-farm employment on farmland transfer and the mediating role of agricultural production services outsourcing (APSO) by using the Probit and Tobit model approaches. This study uses field survey data of 960 rural households in 12 counties of the four main grain producing provinces of China. Findings of this study show that off-farm employment has a significant positive effect on the transfer of land out from households and a significant negative effect on the transfer of land into households. Furthermore, APSO has a significant mediating effect on the influence of off-farm employment on farmland transfer behavior. Specifically, APSO can reduce the positive impact of off-farm employment on agricultural land transfer and weaken the negative impact of off-farm employment on agricultural land transfer-in. The findings of our study also show that the mediating effect of different outsourcing of production links services on the impact of off-farm employment on agricultural land transfer is heterogeneous. Based on the findings of the study, it is contended that the APSO can reshape the supply and demand structure of rural land rental markets and policymakers should focus on the role of ASPO in shaping policies to promote land transfer. Full article
(This article belongs to the Section Agricultural Economics, Policies and Rural Management)
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