Search results for: insect crop pests

Authors: Ijaz Ahmad

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Weed competition is one of the major biotic constraints in wheat crop productivity. Avena fatua L. and Silybum marianum (L.) Gaertn. are among the worst weeds of wheat, greatly deteriorating wheat quality subsequently reducing its market value. In this connection, two-year experiments were conducted in 2018 & 2019. Different seeding rate wheat viz; 80, 100, 120 and 140 kg ha-1 and different weeds ratio (A. fatua: S. marianum ) sown at the rate 1:8, 2:7, 3:6, 4:5, 5:4, 6:3, 7:2, 8:1 and 0:0 respectively. The weeds ratio and wheat densities are indirectly proportional. However, the wheat seed at the rate of 140 kg ha-1 has minimal weeds interference. Yield losses were 17.5% at weeds density 1:8 while 7.2% at 8:1. However, in wheat density, the highest percent losses were computed on 80 kg ha-1 while the lowest was recorded on 140 kg ha-1. Since due to the large leaf canopy of S. marianum other species can't sustain their growth. Hence, it has been concluded that S. marianum is the hotspot that causes reduction to the yield-related parameters, followed by A. fatua and the other weeds. Due to the morphological mimicry of A. fatua with wheat crop during the vegetative growth stage, it cannot be easily distinguished. Therefore, managing A. fatua and S. marianum before seed setting is recommended for reducing the future weed problem. Based on current studies, it is suggested that sowing wheat seed at the rate of 140 kg ha-1 is recommended to better compete with all the field weeds.

Keywords: fat content, holly thistle, protein content, weed competition, wheat, wild oat

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Authors: Wassie Molla, Klaas Frankena, Mart De Jong

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Lumpy skin disease (LSD) is a severe viral disease of cattle, which often occurs in epidemic form. It is caused by lumpy skin disease virus of the genus capripoxvirus of family poxviridae. Mathematical models play important role in the study of infectious diseases epidemiology. They help to explain the dynamics and understand the transmission of an infectious disease within a population. Understanding the transmission dynamics of lumpy skin disease between animals is important for the implementation of effective prevention and control measures against the disease. This study was carried out in central and north-western part of Ethiopia with the objectives to understand LSD outbreak dynamics, quantify the transmission between animals and herds, and estimate the disease reproduction ratio in dominantly crop-livestock mixed and commercial herd types. Field observation and follow-up study were undertaken, and the transmission parameters were estimated based on a SIR epidemic model in which individuals are susceptible (S), infected and infectious (I), and recovered and immune or dead (R) using the final size and generalized linear model methods. The result showed that a higher morbidity was recorded in infected crop-livestock (24.1%) mixed production system herds than infected commercial production (17.5%) system herds whereas mortality was higher in intensive (4.0%) than crop-livestock (1.5%) system and the differences were statistically significant. The transmission rate among animals and between herds were 0.75 and 0.68 per week, respectively in dominantly crop-livestock production system. The transmission study undertaken in dominantly crop-livestock production system highlighted the presence of statistically significant seasonal difference in LSD transmission among animals. The reproduction numbers of LSD in dominantly crop-livestock production system were 1.06 among animals and 1.28 between herds whereas it varies from 1.03 to 1.31 among animals in commercial production system. Though the R estimated for LSD in different production systems at different localities is greater than 1, its magnitude is low implying that the disease can be easily controlled by implementing the appropriate control measures.

Keywords: commercial, crop-livestock, Ethiopia, LSD, reproduction number, transmission

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Authors: Samira Kilani-Morakchi, Amina Badi, Nadia Aribi

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German cockroach, Blattella germanica, is known to be an important pest due to its high reproductive potential and its ability to build up large infectious populations. The infestations were generally controlled by neurotoxic insecticides including organophosphates (OP), carbamate and pyrethroids. An alternative cockroach’s control approach is the use insect growth regulators (IGRs). The relative fewer effects of these chemicals on non-target insects and animals, and their favourable environmental fate, make them attractive insecticides for inclusion in integrated pest management programmes. The juvenoids and chitin synthesis inhibitors are two classes of IGRs that have received the most attention for useful chemicals to manage German cockroaches while ecdysone agonists were mostly used to control Lepidopteran species. In the present study, the sublethal effects of the non-sreroidal ecdysone agonist tebufenozide were evaluated topically on adults of the B. germanica. The effects on reproduction were observed in adults females of cockroaches that survived exposure to LD25 (146 µg/g of insect) of tebufenozide. Dissection of treated females showed a clear reduction in both the number of oocytes per paired ovaries and the size of basal oocytes, as compared to controls. In addition, tebufenozide significantly reduced the mating success of pairs and altered the fertility as shown through the reduction of ootheca development and total absence of viable nymph. Tebufenozide disrupted the German cockroach reproduction by interfering with homeostasis of the insect hormones. In conclusion, the overall results suggested that tebufenozide can be used as a biorational insecticide for controlling cockroaches.

Keywords: B. germanica, ecdysteroid agonist, tebufenozide, reproduction

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Authors: N. A. Ahmad Zubairi, H. Takaijudin, K. W. Yusof

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Pesticides have been used widely over the world in agriculture to protect from pests and reduce crop losses. However, it affects the environment with toxic chemicals. Exceed of toxic constituents in the ecosystem will result in bad side effects. The hydrological cycle is related to the existence of pesticides and heavy metal which it can penetrate through varieties of sources into the soil or water bodies, especially runoff. Therefore, proper mechanisms of pesticide and heavy metal removal should be studied to improve the quality of ecosystem free or reduce from unwanted substances. This paper reviews the use of treatment train and its mechanisms to minimize pesticides and heavy metal from agricultural runoff. Organochlorine (OCL) is a common pesticide that was found in the agricultural runoff. OCL is one of the toxic chemicals that can disturb the ecosystem such as inhibiting plants' growth and harm human health by having symptoms as asthma, active cancer cell, vomit, diarrhea, etc. Thus, this unwanted contaminant gives disadvantages to the environment and needs treatment system. Hence, treatment train by bioretention system is suitable because removal efficiency achieves until 90% of pesticide removal with selected vegetated plant and additive.

Keywords: pesticides, heavy metal, agricultural runoff, bioretention, mechanism removal, treatment train

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Authors: S. K. Kakraliya, R. D. Jat, H. S. Jat, P. C. Sharma, M. L. Jat

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The traditional rice-wheat (RW) system in the IGP of South Asia is tillage, water, energy, and capital intensive. Coupled with more pumping of groundwater over the years to meet the high irrigation water requirement of the RW system has resulted in over-exploitation of groundwater. Replacement of traditional rice with less water crops such as maize under climate-smart agriculture (CSA) based management (tillage, crop establishment and residue management) practices are required to promote sustainable intensification. Furthermore, inefficient nutrient management practices are responsible for low crop yields and nutrient use efficiencies in maize-wheat (MW) system. A 7-year field experiment was conducted in farmer’s participatory strategic research mode at Taraori, Karnal, India to evaluate the effects of tillage and crop establishment (TCE) methods, residue management, mungbean integration, and nutrient management practices on crop yields, water productivity and profitability of MW system. The main plot treatments included four combinations of TCE, residue and mungbean integration [conventional tillage (CT), conventional tillage with mungbean (CT + MB), permanent bed (PB) and permanent bed with MB (PB + MB] with three nutrient management practices [farmer’s fertilizer practice (FFP), recommended dose of fertilizer (RDF) and site-specific nutrient management (SSNM)] using Nutrient Expert® as subplot treatments. System productivity, water use efficiency (WUE) and net returns under PB + MB were significantly increased by 25–30%, 28–31% and 35–40% compared to CT respectively, during seven years of experimentation. The integration of MB in MW system contributed ~25and ~ 28% increases in system productivity and net returns compared with no MB, respectively. SSNM based nutrient management increased the mean (averaged across 7 yrs) system productivity by 12- 15% compared with FFP. The study revealed that CSA based sustainable intensification (PB + MB) and SSNM approach provided opportunities for enhancing crop productivity, WUE and profitability of the MW system in India.

Keywords: Conservation Agriculture, Precision water and nutrient management, Permanent beds, Crop yields

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Authors: Enze Zhang

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One of the most challenging steps in implementing virtual water content (VWC) analysis of crops is to get properly the total volume of consumptive water use (CWU) and, therefore, the choice of a reliable crop CWU estimation method. In practice, lots of previous researches obtaining CWU of crops follow a classical procedure for calculating crop evapotranspiration which is determined by multiplying reference evapotranspiration by appropriate coefficient, such as crop coefficient and water stress coefficients. However, this manner of calculation requires lots of field experimental data at point scale and more seriously, when current growing conditions differ from the standard conditions, may easily produce deviation between the calculated CWU and the actual CWU. Since evapotranspiration caused by crop planting always plays a vital role in surface water-energy balance in an agricultural region, this study decided to alternatively estimates crop evapotranspiration by Budyko framework. After brief introduce the development process of Budyko framework. We choose a modified Budyko framework under unsteady-state to better evaluated the actual CWU and apply it in an agricultural irrigation area in North China Plain which rely on underground water for irrigation. With the agricultural statistic data, this calculated CWU was further converted into VWC and its subdivision of crops at the annual scale. Results show that all the average values of VWC, VWC_blue and VWC_green show a downward trend with increased agricultural production and improved acreage. By comparison with the previous research, VWC calculated by Budyko framework agree well with part of the previous research and for some other research the value is greater. Our research also suggests that this methodology and findings may be reliable and convenient for investigation of virtual water throughout various agriculture regions of the world.

Keywords: virtual water content, Budyko framework, consumptive water use, crop evapotranspiration

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Authors: Bing-Bing E. Goh

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Plant counting is a labour intensive and time-consuming task for the farmers. However, it is an important indicator for farmers to make decisions on subsequent field management. This study is to evaluate the potential of Sentinel-2 images using statistical analysis to retrieve information on plant density for monitoring, especially during critical period at the beginning of March. The model was calibrated with in-situ data from 19 winter wheat fields in Republic of Ireland during the crop growing season in 2019-2020. The model for plant density resulted in R2 = 0.77, RMSECV = 103 and NRMSE = 14%. This study has shown the potential of using Sentinel-2 to estimate plant density and quantify plant establishment to effectively monitor crop progress and to ensure proper field management.

Keywords: winter wheat, remote sensing, crop monitoring, multivariate analysis

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Authors: Ethel E. Phiri, Lionel Hartzenberg, Percy Chimwamuromba, Emmanuel Nepolo, Jens Kossmann, James R. Lloyd

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Orphan crops are underresearched and underutilized food plant species that have not been categorized as major food crops, but have the potential to be economically and agronomically significant. They have been documented to have the ability to tolerate extreme environmental conditions. However, limited research has been conducted to uncover their potential as food crop species. The New Partnership for Africa’s Development (NEPAD) has classified Marama bean, Tylosema esculentum, as an orphan crop. The plant is one of the 101 African orphan crops that must have their genomes sequenced, assembled, and annotated in the foreseeable future. Marama bean is a perennial leguminous plant that primarily grows in poor, arid soils in southern Africa. The plants produce large tubers that can weigh as much as 200kg. While the foliage provides fodder, the tuber is carbohydrate rich and is a staple food source for rural communities in Namibia. Also, the edible seeds are protein- and oil-rich. Marama Bean plants respond rapidly to increased temperatures and severe water scarcity without extreme consequences. Advances in molecular biology and biotechnology have made it possible to effectively transfer technologies between model- and major crops to orphan crops. In this research, the aim was to assemble the first transcriptomic analysis of Marama Bean RNA-sequence data. Many model plant species have had their genomes sequenced and their transcriptomes assembled. Therefore the availability of transcriptome data for a non-model crop plant species will allow for gene identification and comparisons between various species. The data has been sequenced using the Ilumina Hiseq 2500 sequencing platform. Data analysis is underway. In essence, this research will eventually evaluate the potential use of Marama Bean as a crop species to improve its value in agronomy. data for a non-model crop plant species will allow for gene identification and comparisons between various species. The data has been sequenced using the Ilumina Hiseq 2500 sequencing platform. Data analysis is underway. In essence, this researc will eventually evaluate the potential use of Marama bean as a crop species to improve its value in agronomy.

Keywords: 101 African orphan crops, RNA-Seq, Tylosema esculentum, underutilised crop plants

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Authors: F. Lops, G. Disciglio, A. Carlucci, G. Gatta, L. Frabboni, A. Tarantino, E. Tarantino

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Phelipanche ramosa L. Pomel is a root holoparasitic weed plant of many cultivations, particularly of tomato (Lycopersicum esculentum L.) crop. In Italy, Phelipanche problem is increasing, both in density and in acreage. The biological control of this parasitic weed involves the use of living organisms as numerous fungi and bacteria that can infect the parasitic weed, while it may improve the crop growth. This paper deals with the biocontrol with microorganism, including Arbuscular mycorrhizal (AM) fungi and fungal pathogens as Fusarium oxisporum spp. Colonization of crop roots by AM fungi can provide protection of crops against parasitic weeds because of a reduction in their seed germination and attachment, while F. oxisporum, isolated from diseased broomrape tubercles, proved to be highly virulent on P. ramosa. The experimental trial was carried out in open field at Foggia province (Apulia Region, Southern Italy), during the spring-summer season 2016, in order to evaluate the effect of four biological treatments: AM fungi and Fusarium oxisporum applied in the soil alone or combined together, and Rizosum Max^® product, compared with the untreated control, to reduce the P. ramosa infestation in processing tomato crop. The principal results to be drawn from this study under field condition, in contrast of those reported previously under laboratory and greenhouse conditions, show that both AM fungi and F. oxisporum do not provide the reduction of the number of emerged shoots of P. ramosa. This can arise probably from the low efficacy seedling of the agent pathogens for the control of this parasite in the field. On the contrary, the Rizosum Max^® product, containing AM fungi and some rizophere bacteria combined with several minerals and organic substances, appears to be most effective for the reduction of P. ramosa infestation.

Keywords: Arbuscular mycorrhized fungi, biocontrol methods, Phelipanche ramosa, tomato crop

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Authors: Mami Nishida

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This paper presented a study on the development and control of a small biped soft robot using shape memory alloys (SMAs). Author proposed a flexible flat plate (FFP) actuators consisting of a thin　polyethylene plate and SMAs. This actuator has a nail like an insect. This robot moves from the front to back and from left to right using two nails. The walking robot has two degrees of freedom and is controlled by switching the ON-OFF current signals to the SMA based FFPs. The resulting small biped soft robot weighs a mere 4.7 g (with a height of 67 mm). The small robot realizes biped walking by transferring the elastic potential energy (generated by deflections of the SMA based FFPs) to kinematic energy. Experimental results demonstrated the viability and utility of the small biped soft robot with the proposed SMA-based FFPs and the control strategy to achieve walking behavior.

Keywords: biped soft robot with nails, flexible flat plate (FFP) actuators, ON-OFF control strategy, shape memory alloys (SMA)

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Authors: Yilmaz Bayhan, Emin Güzel, Ömer Barış Özlüoymak, Ahmet İnce, Abdullah Sessiz

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In this study, determining of reduced tillage techniques in green bean farming as a second crop after harvesting wheat was targeted. To this aim, four different soil tillage methods namely, heavy-duty disc harrow (HD), rotary tiller (ROT), heavy-duty disc harrow plus rotary tiller (HD+ROT) and no-tillage (NT) (seeding by direct drill) were examined. Experiments were arranged in a randomized block design with three replications. The highest green beans yields were obtained in HD+ROT and NT as 5,862.1 and 5,829.3 Mg/ha, respectively. The lowest green bean yield was found in HD as 3,076.7 Mg/ha. The highest fuel consumption was measured 30.60 L ha^-1 for HD+ROT whereas the lowest value was found 7.50 L ha^-1 for NT. No tillage method gave the best results for fuel consumption and effective power requirement. It is concluded that no-tillage method can be used in second crop green bean in the Thrace Region due to economic and erosion conditions.

Keywords: green bean, soil tillage, yield, vegetative

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Authors: Anil Giri, Kyle Lovercamp, Sankalp Sharma

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Farm level incomes fluctuate significantly due to extreme weather events such as drought. In the light of recent extreme weather events it is important to understand the implications of extreme weather events, flood and drought, on farm level incomes. This study examines the variation in farm level incomes for the United States in drought and no- drought years. Factoring heterogeneity in different enterprises (crop, livestock) and geography this paper analyzes the impact of drought in farm level incomes at state and national level. Livestock industry seems to be affected more by the lag in production of input feed for production, crops, as preliminary results show. Furthermore, preliminary results also show that while crop producers are not affected much due to drought, as price and quantity effect worked on opposite direction with same magnitude, that was not the case for livestock and horticulture enterprises. Results also showed that even when price effect was not as high the crop insurance component helped absorb much of shock for crop producers. Finally, the effect was heterogeneous for different states more on the coastal states compared Midwest region. This study should generate a lot of interest from policy makers across the world as some countries are actively seeking to increase subsidies in their agriculture sector. This study shows how subsidies absorb the shocks for one enterprise more than others. Finally, this paper should also be able to give an insight to economists to design/recommend policies such that it is optimal given the production level of different enterprises in different countries.

Keywords: farm level income, United States, crop, livestock

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Authors: Ashwinder K. Dhaliwal, G. P. S. Dhillon

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Eucalyptus is one of the most important forest tree species that can tolerate and grow well on degraded and unfertile soils which are not suitable for other tree species. Besides this, these trees have a short rotation and good economic value. However, the gall inducing wasp Leptocybe invasa Fisher and La Salle has been reported from many countries throughout the world. The spread of L. invasa is of huge economic concern as more than 20,000 ha of young Eucalyptus trees have already been affected in southern states of India. The host plant resistance being the first line of defense against insect pests demands the screening of different germplasm source against L. invasa. Keeping this in view, fourteen different clones of Eucalyptus spp. were evaluated for their susceptibility to L. invasa from a replicated clonal trial planted at Punjab Agricultural University, Ludhiana. The degree of gall infestation was recorded from three plants of each clone in each replication. Three branches selected from the lower, middle and upper canopy of the trees were selected for recording the total number of galls induced by L. invasa. The statistical analysis was done as per the procedure laid down for completely randomised block design (CRBD), analysis of variance (ANOVA), critical difference (CD) and variance components using Proc GLM (SAS software 9.3, SAS Institute Ltd. U.S.A). All possible treatment means were compared with Duncan’s multiple range test (DMRT) at 1 % probability level. The results showed that the clones C-9, C-45 and C-42 were completely free from the infestation of L. invasa. However, there was minor infestation of L. invasa on C-2135, C-413, C-407, C-35, C-72 and C-37 clones. The clone C-6 was severely infested by L. invasa followed by C-11, C-12, F-316 and C-25 clones. The information generated by this study will be helpful for future breeding and use in afforestation programmes.

Keywords: eucalyptus clones, gall wasp, Leptocybe invasa, screening, susceptibility

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Authors: Byron Baron

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Malta is a Mediterranean archipelago presenting a combination of environmental conditions which are less suitable for agriculture. This has resulted in a heavy dependence on agricultural chemicals, as well as over-extraction of groundwater, compounded by concomitant destruction of natural habitat surrounding the land areas used for agriculture. Such prolonged intensive land use has resulted in even greater degradation of Maltese soils. This study was thus designed with the goal of assessing the viability of implementing a sustainable agricultural system based on permaculture practices compared to the traditional local practices applied for intensive farming. The permaculture model was implemented over a period of two years for a number of locally-grown staple crops. The tangible targets included improved soil health, reduced water consumption, increased reliance on renewable energy, increased wild plant and insect diversity, and sustained crop yield. To achieve this in the permaculture test area, numerous practices were introduced. In line with permaculture principles land, tillage was reduced, only natural fertilisers were used, no herbicides or pesticides were used, irrigation was linked to a desalination system with sensors for monitoring soil parameters, mulching was practiced, and a photovoltaic system was installed. Furthermore, areas for wild plants were increased and controlled only by trimming, not mowing. A variety of environmental parameters were measured at regular intervals as well as crop yield (in kilos of produce) in order to quantify if any improvements in crop output and environmental conditions were obtained. The results obtained show a very slight improvement in overall soil health due to the brevity of the test period. Water consumption was reduced by over 50% with no apparent losses or ill effects on the crops. Renewable energy was sufficient to provide all electric power on-site, so apart from the initial investment costs, there were no limitations. Moreover, surrounding the commercial crops with borders of wild plants whilst only taking up less than 15% of the total land area assisted pollination, increased animal visitors, and did not give rise to any pest infestations. The conclusion from this study was that whilst results are promising, more detailed and long-term studies are required to understand the full extent of the implications brought about by such a transition, which hints towards the untapped potential of investing in the available resources on the island with the goal of improving the balance between economic prosperity and ecological sustainability.

Keywords: agronomic measures, ecological amplification, sustainability, permaculture

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Authors: Riccardo Zanni, Maria Galvez-Llompart, Ramon Garcia-Domenech, Jorge Galvez

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Biopesticides, such as naturally occurring chemicals, pheromones, fungi, bacteria and insect predators are often a winning choice in crop protection because of their environmental friendly profile. They are considered to have lower toxicity than traditional pesticides. After almost a century of pesticides use, resistances to traditional insecticides are wide spread, while those to bioinsecticides have raised less attention, and resistance management is frequently neglected. This seems to be a crucial mistake since resistances have already occurred for many marketed biopesticides. With an eye to the future, we present here a selection of new natural occurring chemicals as potential bioinsecticides. The molecules were selected using a consolidated mathematical paradigm called molecular topology. Several QSAR equations were depicted and subsequently applied for the virtual screening of hundred thousands molecules of natural origin, which resulted in the selection of new potential bioinsecticides. The most innovative aspect of this work does not only reside in the importance of the identification of new molecules overcoming biopesticides’ resistances, but on the possibility to promote shared knowledge in the field of green chemistry through this unique in silico discipline named molecular topology.

Keywords: green chemistry, QSAR, molecular topology, biopesticide

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Authors: Sabiha Shahid Antora, Young Ki Chang

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Along with various farm management technologies, imagery is an important tool that facilitates crop assessment, monitoring, and management. As a consequence, drone imaging technology is playing a vital role to capture the state of the entire field for yield mapping, crop scouting, weed detection, and so on. Although it is essential to inspect the cultivable lands in real-time for making rapid decisions regarding field variable inputs to combat stresses and diseases, drone imagery is still evolving in this area of interest. Cost margin and post-processing complexions of the image stream are the main challenges of imaging technology. Therefore, this proposed project involves the cost-effective field programmable gate array (FPGA) based image processing device that would process the image stream in real-time as well as providing the processed output to support on-the-spot decisions in the crop field. As a result, the real-time FPGA-based image processing system would reduce operating costs while minimizing a few intermediate steps to deliver scalable field decisions.

Keywords: real-time, FPGA, drone imagery, image processing, crop monitoring

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Authors: Nicola D. Cannon

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A range of field experiments have been conducted since 1991 to 2017 on organic land at the Royal Agricultural University’s Harnhill Manor Farm near Cirencester, UK to explore the impact of different management practices on weed infestation in organic winter and spring wheat. The experiments were designed using randomised complete block and some with split plot arrangements. Sowing date, variety choice, crop height and crop establishment technique have all shown a significant impact on weed infestations. Other techniques have also been investigated but with less clear, but, still often significant effects on weed control including grazing with sheep, undersowing with different legumes and mechanical weeding techniques. Tillage treatments included traditional plough based systems, minimum tillage and direct drilling. Direct drilling had significantly higher weed dry matter than the other two techniques. Taller wheat varieties which do not contain Rht1 or Rht2 had higher weed populations than the wheat without dwarfing genes. Early sown winter wheat had greater weed dry matter than later sown wheat. Grazing with sheep interacted strongly with sowing date, with shorter varieties and also late sowing dates providing much less forage but, grazing did reduce weed biomass in June. Undersowing had mixed impacts which were related to the success of establishment of the undersown legume crop. Weeds are most successfully controlled when a range of techniques are implemented to give the wheat crop the greatest chance of competing with weeds.

Keywords: crop establishment, drilling date, grazing, undersowing, varieties, weeds

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Authors: Hanna Mamo Ergando

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Climate change is already having a severe influence on agriculture, affecting crop yields, the nutritional content of main grains, and livestock productivity. Significant adaptation investments will be necessary to sustain existing yields and enhance production and food quality to fulfill demand. Climate-smart agriculture (CSA) provides numerous potentials in this regard, combining a focus on enhancing agricultural output and incomes while also strengthening resilience and responding to climate change. To improve agriculture production and productivity, the Ethiopian government has adopted and implemented a series of strategies, including the recent agricultural cluster farming that is practiced as an effort to change, improve, and transform subsistence farming to modern, productive, market-oriented, and climate-smart approach through farmers production cluster. Besides, greater attention and focus have been given to wheat production and productivity by the government, and wheat is the major crop grown in cluster farming. Therefore, the objective of this assessment was to examine various opportunities and challenges farmers face in a cluster farming system. A qualitative research approach was used to generate primary and secondary data. Respondents were chosen using the purposeful sampling technique. Accordingly, experts from the Federal Ministry of Agriculture, the Ethiopian Agricultural Transformation Institute, the Ethiopian Agricultural Research Institute, and the Ethiopian Environment Protection Authority were interviewed. The assessment result revealed that farming in clusters is an economically viable technique for sustaining small, resource-limited, and socially disadvantaged farmers' agricultural businesses. The method assists farmers in consolidating their products and delivering them in bulk to save on transportation costs while increasing income. Smallholders' negotiating power has improved as a result of cluster membership, as has knowledge and information spillover. The key challenges, on the other hand, were identified as a lack of timely provision of modern inputs, insufficient access to credit services, conflict of interest in crop selection, and a lack of output market for agro-processing firms. Furthermore, farmers in the cluster farming approach grow wheat year after year without crop rotation or diversification techniques. Mono-cropping has disadvantages because it raises the likelihood of disease and insect outbreaks. This practice may result in long-term consequences, including soil degradation, reduced biodiversity, and economic risk for farmers. Therefore, the government must devote more resources to addressing the issue of environmental sustainability. Farmers' access to complementary services that promote production and marketing efficiencies through infrastructure and institutional services has to be improved. In general, the assessment begins with some hint that leads to a deeper study into the efficiency of the strategy implementation, upholding existing policy, and scaling up good practices in a sustainable and environmentally viable manner.

Keywords: cluster farming, smallholder farmers, wheat, challenges, opportunities

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Authors: Aschalew C. Workneh, K. S. Hari Prasad, C. S. P. Ojha

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The crop water stress index (CWSI) is a cost-effective, non-destructive, and simple technique for tracking the start of crop water stress. This study investigated the feasibility of CWSI derived from canopy temperature to detect the water status of wheat crops. Artificial intelligence (AI) techniques have become increasingly popular in recent years for determining CWSI. In this study, the performance of two AI techniques, adaptive neuro-fuzzy inference system (ANFIS) and self-organizing maps (SOM), are compared while determining the CWSI of paddy crops. Field experiments were conducted for varying irrigation water applications during two seasons in 2022 and 2023 at the irrigation field laboratory at the Civil Engineering Department, Indian Institute of Technology Roorkee, India. The ANFIS and SOM-simulated CWSI values were compared with the experimentally calculated CWSI (EP-CWSI). Multiple regression analysis was used to determine the upper and lower CWSI baselines. The upper CWSI baseline was found to be a function of crop height and wind speed, while the lower CWSI baseline was a function of crop height, air vapor pressure deficit, and wind speed. The performance of ANFIS and SOM were compared based on mean absolute error (MAE), mean bias error (MBE), root mean squared error (RMSE), index of agreement (d), Nash-Sutcliffe efficiency (NSE), and coefficient of correlation (R²). Both models successfully estimated the CWSI of the paddy crop with higher correlation coefficients and lower statistical errors. However, the ANFIS (R²=0.81, NSE=0.73, d=0.94, RMSE=0.04, MAE= 0.00-1.76 and MBE=-2.13-1.32) outperformed the SOM model (R²=0.77, NSE=0.68, d=0.90, RMSE=0.05, MAE= 0.00-2.13 and MBE=-2.29-1.45). Overall, the results suggest that ANFIS is a reliable tool for accurately determining CWSI in wheat crops compared to SOM.

Keywords: adaptive neuro-fuzzy inference system, canopy temperature, crop water stress index, self-organizing map, wheat

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Authors: Adegoke A. Adeyelu, Adeola T. Adeyelu, S. D. Y. Alfred, O. O. Fasina

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This study examines the use of traditional medicines for the treatment of selected illnesses among crop-farming households in Edo State, Nigeria. A sample size of ninety (90) households were randomly selected for the study. Data were collected with a structured questionnaire alongside focus group discussions (FGD). Result shows that the mean age was 50 years old, the majority (76.7%) of the sampled farmers were below 60 years old. The majority (80.0%) of the farmers were married, about (92.2%) had formal education. It exposes that the majority of the respondents (76.7%) had household size of between 1-10 persons, about 55.6% had spent 11 years and above in crop farming. malaria (8th ), waist pains (7th ), farm injuries ( 6th ), cough (5th), acute headache(4th), skin infection (3rd), typhoid (2nd) and tuberculosis (1st ) were the most and least treated illness. Respondents (80%) had spent N10,000.00 ($27) and less on treatment of illnesses, 8.9% had spent N10,000.00-N20,000.0027 ($27-$55) 4.4% had spent between N20,100-N30,000.00 ($27-$83) while 6.7% had spent more than N30,100.00 ($83) on treatment of illnesses in the last one (1) year prior to the study. Age, years of farming, farm size, household size, level of income, cost of treatment, level of education, social network, and culture are some of the statistically significant factors influencing the utilization of traditional medicine. Farmers should be educated on methods of preventing illnesses, which is far cheaper than the curative.

Keywords: crop farming-households, selected illnesses, traditional medicines, Edo State

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Authors: Hazel James P. Agngarayngay, Arnold R. Elepaño

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Mango is the third most important export fruit in the Philippines. Despite the expanding mango trade in world market, problems on postharvest losses caused by pests and diseases are still prevalent. Many disease control and pest disinfestation methods have been studied and adopted. Heat treatment is necessary to eliminate pests and diseases to be able to pass the quarantine requirements of importing countries. During heat treatments, temperature and time are critical because fruits can easily be damaged by over-exposure to heat. Modeling the process enables researchers and engineers to study the behaviour of temperature distribution within the fruit over time. Understanding physical processes through modeling and simulation also saves time and resources because of reduced experimentation. This research aimed to simulate the heat transfer mechanism and predict the temperature distribution in ‘Carabao' mangoes during hot water treatment (HWT) and extended hot water treatment (EHWT). The simulation was performed in ANSYS CFD Software, using ANSYS CFX Solver. The simulation process involved model creation, mesh generation, defining the physics of the model, solving the problem, and visualizing the results. Boundary conditions consisted of the convective heat transfer coefficient and a constant free stream temperature. The three-dimensional energy equation for transient conditions was numerically solved to obtain heat flux and transient temperature values. The solver utilized finite volume method of discretization. To validate the simulation, actual data were obtained through experiment. The goodness of fit was evaluated using mean temperature difference (MTD). Also, t-test was used to detect significant differences between the data sets. Results showed that the simulations were able to estimate temperatures accurately with MTD of 0.50 and 0.69 °C for the HWT and EHWT, respectively. This indicates good agreement between the simulated and actual temperature values. The data included in the analysis were taken at different locations of probe punctures within the fruit. Moreover, t-tests showed no significant differences between the two data sets. Maximum heat fluxes obtained at the beginning of the treatments were 394.15 and 262.77 J.s-1 for HWT and EHWT, respectively. These values decreased abruptly at the first 10 seconds and gradual decrease was observed thereafter. Data on heat flux is necessary in the design of heaters. If underestimated, the heating component of a certain machine will not be able to provide enough heat required by certain operations. Otherwise, over-estimation will result in wasting of energy and resources. This study demonstrated that the simulation was able to estimate temperatures accurately. Thus, it can be used to evaluate the influence of various treatment conditions on the temperature-time history in mangoes. When combined with information on insect mortality and quality degradation kinetics, it could predict the efficacy of a particular treatment and guide appropriate selection of treatment conditions. The effect of various parameters on heat transfer rates, such as the boundary and initial conditions as well as the thermal properties of the material, can be systematically studied without performing experiments. Furthermore, the use of ANSYS software in modeling and simulation can be explored in modeling various systems and processes.

Keywords: heat transfer, heat treatment, mango, modeling and simulation

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Authors: Radha Rajamma, Susheela Palanisamy

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The use of chemical fertilizers and pesticides has posed a serious threat to the environment, cause disturbance to the soil ecosystem, pollute the water causing serious health problems. The indigenous practices such as herbal spray, phyto-alternatives, etc. offer harmless alternatives in integrated pest management. The use of plant materials has become an integral part of insect pest management because of their cheap and non-toxic nature. Hence an investigation has been made to determine the bio-efficacy of vermiwash and two leaf extracts, Azadirachta indica and Vitex negundo against mealy bug, Paracoccus marginatus. The results on the effect of vermitechnologies on the activity of mealy bug indicated the effectiveness of vermiwash foliar application in suppressing the pest activity. Accumulative mortality of mealy bug increased gradually with the increase of exposure intervals. The combined treatment of vermiwash with Azadirachta indica reported the highest mortality percentage of 96% followed by the individual treatment of leaf extracts. Hence vermiwash was proved to be the most effective in enhancing the potency of mealy bug and decreased LC50 of the target insect.

Keywords: Azadirachta indica, Paracoccus marginatus, vermiwash, Vitex negundo

Procedia PDF Downloads 267

Authors: Kesavan Markkandan, Ha Young Park, Seung-Il Yoo, Sin-Gi Park, Junhyung Park

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For genetic identification of crop cultivars, insertions/deletions (InDel) markers have been preferred currently because they are easy to use, PCR based, co-dominant and relatively abundant. However, new InDels need to be developed for genetic studies of new varieties due to the difference of allele frequencies in InDels among the population groups. These new varieties are evolved with low levels of genetic diversity in specific genome loci with high recombination rate. In this study, we described soybean barcode system approach based on InDel makers, each of which is specific to a variation block (VB), where the genomes split by all assumed recombination sites. Firstly, VBs in crop cultivars were mined for transferability to VB-specific InDel markers. Secondly, putative InDels in the VB regions were identified for the development of barcode system by analyzing particular cultivar’s whole genome data. Thirdly, common VB-specific InDels from all cultivars were selected by gel electrophoresis, which were converted as 2D barcode types according to comparing amplicon polymorphisms in the five cultivars to the reference cultivar. Finally, the polymorphism of the selected markers was assessed with other cultivars, and the barcode system that allows a clear distinction among those cultivars is described. The same approach can be applicable for other commercial crops. Hence, VB-based genetic identification not only minimize the molecular markers but also useful for assessing cultivars and for marker-assisted breeding in other crop species.

Keywords: variation block, polymorphism, InDel marker, genetic identification

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Authors: Zahra Safaeian, Shila Goldasteh, Rouhollah Radjabi

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Flowerflies of Syrphidae family is one of the largest families among the Diptera order that due to predatory habit of some species in larva stage has an important role for controlling aphids of the fields. In the present study, flowerflies fauna in the alfalfa fields of the north of Khouzestan were studied during 2012-2013. The species of the family were collected using appropriate methods including insect collecting sweeping net and Malaise traps. According to the fact that the shape of male genitalia in the male insect is important in identification of these species the male genitalia was separated from the body and microscopical slide was prepared then species identification was done considering the male genitalia, the patterns and figures on the abdomen and using available keys. Based on the finding four species of Sphaerophoria scripta, Sphaerophoria turkmenica, Melanostoma mellinu, Sphaerophoria ruppelli were collected and according to the abundance frequency of the collected species the most abundance was related to Sphaerophoria scripta, then Sphaerophoria turkmenica had the most abundance and the least abundance was related to Sphaerophoria ruppelli.

Keywords: syrphidae, fauna, alfalfa, Iran

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Authors: Himanshu Sharma, Karthik Kumar, Harish Kumar

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The major problem in crop cultivation is the occurrence of multiple crop diseases. During the growth stage, timely identification of crop diseases is paramount to ensure the high yield of crops, lower production costs, and minimize pesticide usage. In most cases, crop diseases produce observable characteristics and symptoms. The Surveyors usually diagnose crop diseases when they walk through the fields. However, surveyor inspections tend to be biased and error-prone due to the nature of the monotonous task and the subjectivity of individuals. In addition, visual inspection of each leaf or plant is costly, time-consuming, and labour-intensive. Furthermore, the plant pathologists and experts who can often identify the disease within the plant according to their symptoms in early stages are not readily available in remote regions. Therefore, this study specifically addressed early detection of leaf scald, red rot, and eyespot types of diseases within sugarcane plants. The study proposes a computer vision-based approach using a convolutional neural network (CNN) for automatic identification of crop diseases. To facilitate this, firstly, images of sugarcane diseases were taken from google without modifying the scene, background, or controlling the illumination to build the training dataset. Then, the testing dataset was developed based on the real-time collected images from the sugarcane field from India. Then, the image dataset is pre-processed for feature extraction and selection. Finally, the CNN-based Visual Geometry Group (VGG) model was deployed on the training and testing dataset to classify the images into diseased and healthy sugarcane plants and measure the model's performance using various parameters, i.e., accuracy, sensitivity, specificity, and F1-score. The promising result of the proposed model lays the groundwork for the automatic early detection of sugarcane disease. The proposed research directly sustains an increase in crop yield.

Keywords: automatic classification, computer vision, convolutional neural network, image processing, sugarcane disease, visual geometry group

Procedia PDF Downloads 93

Authors: W. A. M. Abdel Kawy, Kh. M. Darwish

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Adequate land use selection is an essential step towards achieving sustainable development. The main object of this study is to develop a new scale for land suitability system, which can be compatible with the local conditions. Furthermore, it aims to adapt the conventional land suitability systems to match the actual environmental status in term of soil types, climate and other conditions to evaluate land suitability for newly reclaimed areas. The new system suggests calculation of land suitability considering 20 factors affecting crop selection grouping into five categories; crop-agronomic, land management, development, environmental conditions and socio – economic status. Each factor is summed by each other to calculate the total points. The highest rating for each factor indicates the highest preference for the evaluated crop. The highest rated crops for each group are those with the highest points for the actual suitability. This study was conducted to assess the application efficiency of the new land suitability scale in recently reclaimed sites in Egypt. Moreover, 35 representative soil profiles were examined, and soil samples were subjected to some physical and chemical analysis. Actual and potential suitabilities were calculated by using the new land suitability scale. Finally, the obtained results confirmed the applicability of a new land suitability system to recommend the most promising crop rotation that can be applied in the study areas. The outputs of this research revealed that the integration of different aspects for modeling and adapting a proposed model provides an effective and flexible technique, which contribute to improve land suitability assessment for several crops to be more accurate and reliable.

Keywords: analytic hierarchy process, land suitability, multi-criteria analysis, new reclaimed areas, soil parameters

Procedia PDF Downloads 113

Authors: M. M. Ali, Ahmed Al- Ani, Derek Eamus, Daniel K. Y. Tan

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In this glasshouse study, we developed the new image-based non-destructive technique for detecting leaf P status of different crops such as cotton, tomato and lettuce. Plants were allowed to grow on nutrient media containing different P concentrations, i.e. 0%, 50% and 100% of recommended P concentration (P0 = no P, L; P1 = 2.5 mL 10 L-1 of P and P2 = 5 mL 10 L-1 of P as NaH2PO4). After 10 weeks of growth, plants were harvested and data on leaf P contents were collected using the standard destructive laboratory method and at the same time leaf images were collected by a handheld crop image sensor. We calculated leaf area, leaf perimeter and RGB (red, green and blue) values of these images. This data was further used in the linear discriminant analysis (LDA) to estimate leaf P contents, which successfully classified these plants on the basis of leaf P contents. The data indicated that P deficiency in crop plants can be predicted using the image and morphological data. Our proposed non-destructive imaging method is precise in estimating P requirements of different crop species.

Keywords: image-based techniques, leaf area, leaf P contents, linear discriminant analysis

Procedia PDF Downloads 351

Authors: S. K. Kakraliya, H. S. Jat, Manish Kakraliya, P. C. Sharma, M. L. Jat

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The biggest challenge in agriculture is to produce more food for the continually increasing world population with in the limited land and water resources. Serious water deficits and reducing natural resources are some of the major threats to the agricultural sustainability in many regions of South Asia. Food and water security may be gained by bringing improvement in the crop water productivity and the amount produced per unit of water consumed. Improvement in the crop water productivity may be achieved by pursuing alternative modern agronomics approaches, which are more friendly and efficient in utilizing natural resources. Therefore, a research trial on conservation agriculture (CA) and precision water management (PWM) was conducted in 2018-19 at Karnal, India to evaluate the effect on crop productivity and irrigation in sodic soils under rice-wheat (RW) systems of Indo-Gangetic Plains (IGP). Eight scenarios were compared varied in the tillage, crop establishment, residue and irrigarion management i.e., {First four scenarios irrigated with flood irrigation method;Sc1-Conventional tillage (CT) without residue, Sc2-CT with residue, Sc3- Zero tillage (ZT) without residue, Sc4-ZT with residue}, and {last four scenarios irrigated with sub-surface drip irrigation method; Sc5-ZT without residue, Sc6- ZT with residue, Sc7-ZT inclusion legume without residue and Sc8- ZT inclusion legume with residue}. Results revealed that CA-flood irrigation (S3, Sc4) and CA-PWM system (Sc5, Sc6, Sc7 and Sc8) recorded about ~5% and ~15% higher wheat yield, respectively compared to Sc1. Similar, CA-PWM saved ~40% irrigation water compared to Sc1. Rice yield was not different under different scenarios in the first year (kharif 2019) but almost half irrigation water saved under CA-PWM system. Therefore, results of our study on modern agronomic practices including CA and precision water management (subsurface drip irrigation) for RW rotation would be addressed the existing and future challenges in the RW system.

Keywords: Sub-surface drip, Crop residue, Crop yield , Zero tillage

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Authors: Maria E. Laconi, Kyla D. Scherr, Mary A. Jamieson

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Human populations in urban environments have rapidly grown in recent decades. Consequently, the intensity of land-use and development has also increased in many urban and peri-urban environments. Some cities, such as Detroit, Michigan, USA, have embraced urban agriculture and local food production. Little is known, however, about how the local and landscape scale environmental factors influence crop productivity on urban farms. Our study aims to evaluate factors influencing the productivity of strawberries on community farms and gardens in the Detroit metropolitan area. Strawberries are one of few fruits that can provide an abundant harvest just after the first season of being planted, which is ideal for urban gardeners in developed areas. In the spring of 2016, we planted six different strawberry cultivars (three everbearing and three June bearing varieties) at five farm sites in Wayne and Oakland County (six replicate plants per cultivar per site). We surveyed flower and fruit phenology and production for everbearing varieties weekly (flowers for June bearing varieties were removed to enhance productivity in the coming growing season). Additionally, we conducted one initial 36hr pollinator survey in mid-September during peak fruit production and characterized local and landscape scale land-cover data. Preliminary results and observations from this first year of our study revealed that strawberry production varied significantly by site. Specifically, productivity at our most northern site appeared to suffer from delayed phenology and early frost damage to ripening strawberries. Bee abundance and diversity also differed among farms, though further surveys are needed to adequately inventory the pollinator community. Finally, strawberry cultivars demonstrated significant differences in the number and size of fruits produced. We plan to continue this study in the coming years, increasing the number of sites surveyed and number of pollinator sampling events. Our study aims to inform strategies for enhancing crop productivity on urban and peri-urban farms.

Keywords: insect pollination, strawberry productivity, sustainable agriculture, urban gardening

Procedia PDF Downloads 249

Authors: Xiangtuo Chen, Paul-Henry Cournéde

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Crop yield prediction is a paramount issue in agriculture. The main idea of this paper is to find out efficient way to predict the yield of corn based meteorological records. The prediction models used in this paper can be classified into model-driven approaches and data-driven approaches, according to the different modeling methodologies. The model-driven approaches are based on crop mechanistic modeling. They describe crop growth in interaction with their environment as dynamical systems. But the calibration process of the dynamic system comes up with much difficulty, because it turns out to be a multidimensional non-convex optimization problem. An original contribution of this paper is to propose a statistical methodology, Multi-Scenarios Parameters Estimation (MSPE), for the parametrization of potentially complex mechanistic models from a new type of datasets (climatic data, final yield in many situations). It is tested with CORNFLO, a crop model for maize growth. On the other hand, the data-driven approach for yield prediction is free of the complex biophysical process. But it has some strict requirements about the dataset. A second contribution of the paper is the comparison of these model-driven methods with classical data-driven methods. For this purpose, we consider two classes of regression methods, methods derived from linear regression (Ridge and Lasso Regression, Principal Components Regression or Partial Least Squares Regression) and machine learning methods (Random Forest, k-Nearest Neighbor, Artificial Neural Network and SVM regression). The dataset consists of 720 records of corn yield at county scale provided by the United States Department of Agriculture (USDA) and the associated climatic data. A 5-folds cross-validation process and two accuracy metrics: root mean square error of prediction(RMSEP), mean absolute error of prediction(MAEP) were used to evaluate the crop prediction capacity. The results show that among the data-driven approaches, Random Forest is the most robust and generally achieves the best prediction error (MAEP 4.27%). It also outperforms our model-driven approach (MAEP 6.11%). However, the method to calibrate the mechanistic model from dataset easy to access offers several side-perspectives. The mechanistic model can potentially help to underline the stresses suffered by the crop or to identify the biological parameters of interest for breeding purposes. For this reason, an interesting perspective is to combine these two types of approaches.

Keywords: crop yield prediction, crop model, sensitivity analysis, paramater estimation, particle swarm optimization, random forest

Procedia PDF Downloads 208