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Selected Papers from 1st International Online Conference on Agriculture - Advances in Agricultural Science and Technology (IOCAg2022)

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A special issue of Agriculture (ISSN 2077-0472).

Deadline for manuscript submissions: closed (10 December 2022) | Viewed by 38867

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Prof. Dr. Bin Gao

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Department of Civil and Environmental Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, USA
Interests: biochar technology; environmental nanotechnology; contaminant fate and transport
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Agriculture was a major development in human history, leading to the rise and flourishing of civilization. It plays a critical role in human society, serving as the backbone of the economic system. Modern agriculture provides the raw materials for most of the world’s food and for many industrial products, including textiles. Significant scientific and technological advances over the years have led to great increases in agricultural productivity, as well as a reduction in the environmental impacts. Nevertheless, agricultural systems of the future face huge challenges in balancing and optimizing productivity and profitability against the stewardship of ecosystems and natural resources.

The MDPI journal Agriculture, a peer-reviewed open access international journal of MDPI, announced the first International Online Conference on Agriculture - Advances in Agricultural Science and Technology (IOCAg2022), which will be held online (Sciforum) from February 10 to February 25 in 2022. One of the main goals of this e-conference is to promote research and collaboration in agricultural science and technology.

To celebrate IOCAg2022 and call for the most advanced research in the field, Agriculture will dedicate one Special Issue to the conference, with a 20% discount on the Article Processing Charges (APC). All participants of IOCAg2022 are invited to submit a full paper to this issue. Specific topics of interest include, but are not limited to:

Crop production
Farm Animal Production
Genotype Evaluation and Breeding
Crop Protection, Diseases, Pest and Weeds
Agricultural Soils
Agricultural Technology
Ecosystem, Environment and Climate Change in Agriculture
Agricultural Product Quality and Safety
Agricultural Economics, Policies and Rural Management
Digital Agriculture
Agricultural Systems and Management
Agricultural Water Management
Seed Science and Technology

Prof. Dr. Bin Gao
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agriculture is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

agricultural science and technology
agricultural systems
agricultural production
smart farming and precision agriculture
sustainable agriculture
environmental impact

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Published Papers (9 papers)

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Research

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15 pages, 442 KiB

Open AccessArticle

Evaluation of the Effects of Introducing Risk Management Tools in Agricultural Development: The Case of PADAER Senegal

by Alice Bonou, Markus Olapade, Alessandra Garbero and Leonard Wantchekon

Agriculture 2023, 13(5), 989; https://doi.org/10.3390/agriculture13050989 - 29 Apr 2023

Cited by 2 | Viewed by 1830

Abstract

This study aims to assess the effects of risk management tools on the agricultural performance of rural producers benefiting from the joint support of the Senegalese state and the International Fund for Agricultural Development (IFAD) through the co-financed project PADAER. Data collection covers two regions in Senegal: Kolda and Tambacounda. The sample comprises 1167 farmers, including 379 beneficiaries of the index-based insurance facilitated by PADAER (Programme d’Appui au Développement Agricole et à l’Entreprenariat Rural). The quasi-experimental method known as the propensity score matching method was used to determine the impact of subscribing to index-based insurance on the farmer’s production, agricultural investments, and annual income. Although the results of the estimates show that the project has not yet had any effect on production, without the intervention of this project, farmers would have recorded a loss of about USD 115 (FCFA 57,600). Not only did the index-based insurance for the harvest facilitated by the PADAER allow the beneficiary to cover this loss and realize a gain estimated at USD 25 (FCFA 12,749), but the added value of this paper is that it measures the effects of agricultural index-based insurance in Africa using real-world statistical data. Full article

(This article belongs to the Special Issue Selected Papers from 1st International Online Conference on Agriculture - Advances in Agricultural Science and Technology (IOCAg2022))

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14 pages, 2963 KiB

Open AccessArticle

Fodder Grass Strips: An Affordable Technology for Sustainable Rainfed Agriculture in India

by Pushpanjali, Josily Samuel, Prabhat Kumar Pankaj, Konda Srinivas Reddy, Karunakaran Karthikeyan, Ardha Gopala Krishna Reddy, Jagriti Rohit, Kotha Sammi Reddy and Vinod Kumar Singh

Agriculture 2023, 13(2), 318; https://doi.org/10.3390/agriculture13020318 - 28 Jan 2023

Viewed by 2913

Abstract

Rainfed agriculture, though resource-poor, contributes to around 40 percent of total food production in India. Fodder grass-strip-based systems improve soil’s physical and biological properties, control soil erosion, and help in slope stabilization without compromising productivity. Permanent fodder grass strips can effectively check the depletion of soil nutrients and can also act as sediment traps vis-à-vis meeting the green fodder requirement for small ruminants. This study was carried out with the major objective to quantify the impact of grass-strip-based cropping systems on soil quality. Further fodder quality assessment was carried out using the grass quality index for small ruminant feed and the profitability of different treatments was analyzed. Random block design (RBD) with three treatments which included two types of fodder grass (Brachiaria ruziziensis and Stylosanthes hamata) on both sides of the cropped field was used for the study. The results showed that the soil quality increased from 0.39 to 0.52 and the runoff reduced significantly with soil loss reduction by 65-70 percent. The fodder quality assessment showed that the palatability of Stylosanthes hamata and Brachiaria ruziziensis was about 65 percent and 40 percent, respectively. The fodder grass strip increased the net returns by 30 percent. This easily adaptable natural resource management technology reduces soil nutrient loss and will help resource-poor rainfed farmers to maintain soil health and productivity under variable rainfall conditions with fair support to small ruminants. Full article

(This article belongs to the Special Issue Selected Papers from 1st International Online Conference on Agriculture - Advances in Agricultural Science and Technology (IOCAg2022))

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22 pages, 6524 KiB

Open AccessArticle

Smart Weather Data Management Based on Artificial Intelligence and Big Data Analytics for Precision Agriculture

by Chouaib El Hachimi, Salwa Belaqziz, Saïd Khabba, Badreddine Sebbar, Driss Dhiba and Abdelghani Chehbouni

Agriculture 2023, 13(1), 95; https://doi.org/10.3390/agriculture13010095 - 29 Dec 2022

Cited by 23 | Viewed by 11591

Abstract

Smart management of weather data is an essential step toward implementing sustainability and precision in agriculture. It represents an important input for numerous tasks, such as crop growth, development, yield, and irrigation scheduling, to name a few. Advances in technology allow collecting this weather data from heterogeneous sources with high temporal resolution and at low cost. Generating and using these data in their raw form makes no sense, and therefore implementing adequate infrastructure and tools is necessary. For that purpose, this paper presents a smart weather data management system evaluated using data from a meteorological station installed in our study area covering the period from 2013 to 2020 at a half-hourly scale. The proposed system makes use of state-of-the-art statistical methods, machine learning, and deep learning models to derive actionable insights from these raw data. The general architecture is made up of four layers: data acquisition, data storage, data processing, and application layers. The data sources include real-time sensors, IoT devices, reanalysis data, and raw files. The data are then checked for errors and missing values using a proposed method based on ERA5-Land reanalysis data and deep learning. The resulting coefficient of determination (R²) and Root Mean Squared Error (RMSE) for this method were 0.96 and 0.04, respectively, for the scaled air temperature estimate. The MongoDB NoSQL database is used for storage thanks to its ability to deal with real-world big data. The system offers various services such as (i) weather time series forecasts, (ii) visualization and analysis of meteorological data, and (iii) the use of machine learning to estimate the reference evapotranspiration (ET₀) needed for efficient irrigation. To this, the platform uses the XGBoost model to achieve the precision of the Penman–Monteith method while using a limited number of meteorological variables (air temperature and global solar radiation). Results for this approach give R² = 0.97 and RMSE = 0.07. This system represents the first incremental step toward implementing smart and sustainable agriculture in Morocco. Full article

(This article belongs to the Special Issue Selected Papers from 1st International Online Conference on Agriculture - Advances in Agricultural Science and Technology (IOCAg2022))

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16 pages, 2368 KiB

Open AccessArticle

Effect of Silicon on Oat Salinity Tolerance: Analysis of the Epigenetic and Physiological Response of Plants

by Barbara Stadnik, Renata Tobiasz-Salach and Marzena Mazurek

Agriculture 2023, 13(1), 81; https://doi.org/10.3390/agriculture13010081 - 28 Dec 2022

Cited by 8 | Viewed by 2837

Abstract

Environmental conditions are the primary factor determining the growth and yield of plants. As a result of climate change, the negative impact of abiotic factors is intensifying. One of them is salt stress. Soil salinity is one of the major problems in agriculture in the world and affects many cultivar species. The aim of this study was to evaluate the effect of silicon foliar application on the physiological and epigenetic reaction of oats (Avena sativa L.) under salt stress. The pot experiment was carried out in controlled conditions. Oat plants were subject to sodium chloride (NaCl) at a concentration of 200 mM and applied to the soil. Three concentrations of Optysil (200 g∙L⁻¹ SiO₂) were used for foliar fertilization. Measurements were made of the relative chlorophyll content in the leaves, the selected chlorophyll fluorescence parameters, and the gas exchange parameters. In this study, methylation-sensitive amplification polymorphisms (MSAP) analysis was used to investigate the effect of Si application during salinity stress on the DNA methylation level in oat plants. The results of this study indicated that the exogenous application of silicon improved the tolerance of the oat plants to salinity. The doses of 0.1% and 0.2% Optysil had the greatest effect on alleviating the impact of salt stress on the oat plants. In this research, the epigenetic as well as the physiological response of plants to the applied experimental factors were analyzed, which is a broad coverage of the research topic on the effects of salinity and silicon on plants. Full article

(This article belongs to the Special Issue Selected Papers from 1st International Online Conference on Agriculture - Advances in Agricultural Science and Technology (IOCAg2022))

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16 pages, 2816 KiB

Open AccessArticle

Grassland Reseeding: Impact on Soil Surface Nutrient Accumulation and Using LiDAR-Based Image Differencing to Infer Implications for Water Quality

by Emma Hayes, Suzanne Higgins, Josie Geris and Donal Mullan

Agriculture 2022, 12(11), 1854; https://doi.org/10.3390/agriculture12111854 - 4 Nov 2022

Cited by 1 | Viewed by 2031

Abstract

Long-term phosphorus (P) accumulation in agricultural soils presents a challenge for water quality improvement. P is commonly elevated in soils managed for intensive livestock production due to repeated overapplication of slurry and fertilisers. High legacy nutrient accumulations result in poor water quality via transport pathways such as surface runoff, subsurface drainage, and soil erosion. To achieve environmental water quality targets, improved management strategies are required for targeting and reducing excess agricultural P sources. Reseeding of old swards is known to improve grassland productivity and enhance overall soil health. However, soil disturbance associated with reseeding could have positive and negative impacts on other soil functions that affect the nutrient balance (including improved microbial activity, but also increasing the potential for sediment and nutrient losses). This study investigates the impact of reseeding and inversion tillage in addressing soil surface nutrient surpluses and identifies potential trade-offs between production, environment (through soil erosion and associated sediment and nutrient losses), and soil health. At a study site in the Blackwater catchment in Northern Ireland, we collected high-resolution (35 m) gridded soil samples pre- and post-reseeding for nutrient analyses and combined this with GIS-based interpolation. We found that decreases in sub-field scale surface nutrient content (0–7.5 cm depth) occurred following tillage and reseeding, but that this was spatially variable. In addition, the magnitude of changes in nutrient content was variable between P and other sampled nutrients. LiDAR-based image differencing indicated variability in the magnitude of soil erosion and sediment loss also at sub-field scale. Information on the identified deposition and erosion zones (from LiDAR analysis) was combined with mass wasting data to determine accumulation rates and losses of nutrients in-field and confirmed some of the identified patterns in soil surface nutrient content changes post-reseeding. We conclude that while inversion tillage and reseeding are essential agricultural practices, environmental trade-offs exist through potential nutrient and sediment losses. LiDAR-based image differencing was found to be a useful tool in helping to quantify these risks. Quantifying sediment and nutrient losses as a result of inversion tillage and reseeding induced soil erosion aids in understanding potential trends in water quality statuses. Full article

(This article belongs to the Special Issue Selected Papers from 1st International Online Conference on Agriculture - Advances in Agricultural Science and Technology (IOCAg2022))

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16 pages, 345 KiB

Open AccessArticle

Evaluating the Heterogeneous Impacts of Adoption of Climate-Smart Agricultural Technologies on Rural Households’ Welfare in Mali

by Bola Amoke Awotide, Adebayo Ogunniyi, Kehinde Oluseyi Olagunju, Lateef Olalekan Bello, Amadou Youssouf Coulibaly, Alexander Nimo Wiredu, Bourémo Kone, Aly Ahamadou, Victor Manyong and Tahirou Abdoulaye

Agriculture 2022, 12(11), 1853; https://doi.org/10.3390/agriculture12111853 - 4 Nov 2022

Cited by 10 | Viewed by 2591

Abstract

Climate change is negatively affecting agricultural production in the Sahel region. Climate-Smart Agricultural Technologies (CSATs) are disseminated to reduce these negative effects, and particularly those on resource-poor farm households. This article investigates the distributional impacts of the adoption of CSAT on-farm households’ welfare using a dataset that covers four regions, 32 communes, 320 villages, and 2240 households in Mali. Using an instrumental variable quantile treatment effects model, the paper addresses the potential endogeneity arising from the selection bias and the heterogeneity of the effect across the quantiles of the outcome variables’ distribution. The results show that the adoption of CSAT is positively associated with improved households’ welfare. The farmers’ decision to adopt any CSAT is influenced by access to credit, contact with extension agents, participation in training, access to information through the television, and being a member of any organization such as a cooperative society. Moreover, the effect of the adoption of CSAT on household welfare varies across the different households. In particular, the results show that the impact of the adoption of CSAT on households’ welfare is generally higher for the poorest (farmers located at the bottom tail of the distribution) end of the welfare distribution. The findings, therefore, highlight the pro-poor impact of the adoption of CSAT in the rural Malian context, as well as the need to tailor the CSAT interventions toward specific socio-economic segments of the rural population in Mali. Full article

(This article belongs to the Special Issue Selected Papers from 1st International Online Conference on Agriculture - Advances in Agricultural Science and Technology (IOCAg2022))

21 pages, 2743 KiB

Open AccessArticle

Effects of Automated Irrigation Systems and Water Regimes on Soil Properties, Water Productivity, Yield and Fruit Quality of Date Palm

by Mishari A. Alnaim, Magdy S. Mohamed, Maged Mohammed and Muhammad Munir

Agriculture 2022, 12(3), 343; https://doi.org/10.3390/agriculture12030343 - 28 Feb 2022

Cited by 19 | Viewed by 5631

Abstract

Applications of modern micro-irrigation methods are inevitable for optimum water use due to the limitations imposed by irrigation water resource scarcity. Regardless of water shortages and associated challenges in dry areas, the irrigation of date palm trees consumes an excessive quantity of water annually using conventional irrigation methods. Therefore, the present study was designed to evaluate the effects of modern surface and subsurface micro-irrigation systems, i.e., subsurface drip irrigation (SSDI), controlled surface irrigation (CSI), and surface drip-irrigation methods (SDI), with different irrigation water regimes, i.e., 50%, 75%, and 100% irrigation water requirements (IWRs), on the yield and fruit quality of date palms (cv. Khalas) and water conservation in the dryland region of Al-Ahsa, Saudi Arabia. The effects of three irrigation methods and IWRs were studied on macronutrients and soil chemical properties at three depths (0–30, 30–60, and 60–90 cm), as well as on water productivity, yield, and the fruit quality of date palms. The study was carried out over two years and was designed using a two-factorial randomized complete block design (RCBD) with nine replications. The results indicated that electrical conductivity (EC) increased as the depth of the soil increased. The soil chemical properties did not change much in all experimental treatments, while soil pH values decreased with the soil depth from 0–30 to 60–90 cm. Although the maximum fruit yield (96.62 kg palm⁻¹) was recorded when 100% irrigation water was applied in the SSDI system, other treatment combinations, such as SDI at 100% IWR (84.86 kg palm⁻¹), SSDI at 75% IWR (84.84 kg palm⁻¹), and CSI at 100% IWR (83.86 kg palm⁻¹) behaved alike and showed promising results. Similarly, the highest irrigation water productivity (2.11 kg m⁻³) was observed in the SSDI system at 50% IWR, followed by the SSDI at 75% IWR (1.64 kg m⁻³) and 100% IWR (1.40 kg m⁻³). Fruit quality attributes were also promoted with the SSDI system at 75% IWR. Hence, the SSDI method at 75% IWR appeared to be an optimal choice for date palm irrigation in arid areas due to its positive impact on water conservation and fruit characteristics without affecting soil chemical properties. Full article

(This article belongs to the Special Issue Selected Papers from 1st International Online Conference on Agriculture - Advances in Agricultural Science and Technology (IOCAg2022))

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11 pages, 2865 KiB

Open AccessArticle

A Preliminary Study on Flight Characteristics of the Longhorn Date Palm Stem Borer Jebusaea hammerschmidtii (Reiche 1878) (Coleoptera: Cerambycidae) Using a Computerized Flight Mill

by Hamadttu El-Shafie, Maged Mohammed and Nashi Alqahtani

Agriculture 2022, 12(1), 120; https://doi.org/10.3390/agriculture12010120 - 17 Jan 2022

Cited by 4 | Viewed by 2672

Abstract

The longhorn date palm stem borer, Jebusaea hammerschmidtii (Reiche), is a highly destructive beetle of edible date palm Phoenix dactylifera L. The flight capabilities and dispersal potential of this beetle are unknown, which hinders the planning for its proper management in date palm groves. In this study, the flight propensity of this insect pest was investigated using a computerized flight-testing system. The flight system consisted of a flight mill, a digitally controlled testing chamber, and a data logging and processing unit with a USB digital oscilloscope connected with a laptop. A total of 40 field-collected beetles of unknown sex and mating history were used in the experiments; about 34% of this number failed to fly on the flight mill. The relationship between temperature treatments (°C) and flight speed (m/min), cumulative flight time (min), and cumulative flight distance (km) of the test beetles were studied using regression equations with correlation coefficients (R²) of 0.91, 0.98, and 0.98, respectively. The maximum cumulative distance flown by the beetle was 11.5 km at a temperature of 35 °C, and a minimum distance of 2.4 km was recorded at 45 °C. The flight threshold of the beetle was 20 °C, at which flight activities ceased utterly. The velocity of the beetle increased with increasing temperature and reached a maximum of 107 m/min at 40 °C, before starting to decline. The obtained information on the flight characteristics of the J. hammerschmidtii may aid in understanding the dispersal of this pest in date palm plantations and in setting up management strategies. Full article

(This article belongs to the Special Issue Selected Papers from 1st International Online Conference on Agriculture - Advances in Agricultural Science and Technology (IOCAg2022))

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Review

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23 pages, 689 KiB

Open AccessReview

Multi-Omic Approaches to Investigate Molecular Mechanisms in Peach Post-Harvest Ripening

by Tiziana M. Sirangelo, Hilary J. Rogers and Natasha D. Spadafora

Agriculture 2022, 12(4), 553; https://doi.org/10.3390/agriculture12040553 - 13 Apr 2022

Cited by 13 | Viewed by 3327

Abstract

Peach post-harvest ripening is a complex developmental process controlled by a plethora of genetic and epigenetic factors. Specifically, it leads to protein, lipid and nucleic acid degradation, all resulting in cell death. Substantial research has been directed at investigating peach regulatory mechanisms underlying genomic, metabolomic and transcriptomic modifications occurring during this stage, and much progress has been made thanks to the advent of Next Generation Sequencing technologies. This review is focused on the latest multi-omics studies, with the aim of highlighting the most significant results and further investigating the regulation of the key genes involved in peach post-harvest processes and related physiology. By offering an exhaustive overview of peach omics profiles, it provides a comprehensive description of gene expression changes and their correlation with ripening stages, including some post-harvest treatments, as well as with volatile organic compound modifications. However, the present work highlights that, due to the complexity of the process, recent investigations do not elucidate all underlying molecular mechanisms, making further studies still necessary. For this reason, some key points for future research activities and innovative peach breeding programs are discussed, relying on trusted multi-omic approaches. Full article

(This article belongs to the Special Issue Selected Papers from 1st International Online Conference on Agriculture - Advances in Agricultural Science and Technology (IOCAg2022))

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