Can combine headers and travel speeds affect the quality of soybean harvesting operations?

Menezes, Patricia Candida de; Silva, Rouverson Pereira da; Carneiro, Franciele Morlin; Gírio, Lucas Augusto da Silva; Oliveira, Maílson Freire de; Voltarelli, Murilo Aparecido

doi:10.1590/1807-1929/agriambi.v22n10p732-738

Cited by 21 publications

(21 citation statements)

References 12 publications

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“…Statistical Quality Control (SQC) was also used to study the growth stages of peanut, a statistic that has shown good results but is "not usually applied" in precision agriculture. This statistic is being used in the area of agricultural mechanization and has yielded good results in monitoring operational quality, as observed by Carneiro et al (2017b), Cassia et al (2015), Menezes et al (2018), Ormond et al (2016), Tavares et al (2015), Voltarelli et al (2015), and others.…”

Section: Introductionmentioning

confidence: 96%

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Correlations Among Vegetation Indices and Peanut Traits During Different Crop Development Stages

et al. 2019

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Active optical sensors have been widely used for the spatial and temporal monitoring of peanut culture because they are accurate, non-destructive methods for rapidly obtaining data. The objective of this study was to determine the optimal stage of crop growth for collecting sensor readings based on correlations between quality indicators. In addition, we compared vegetation indices (Normalized Difference Vegetation Index [NDVI], Normalized Difference Red-Edge Index, [NDRE], and Inverse Ratio Vegetation Index, [IRVI]) by monitoring temporal variability in the peanut crop in order to determine which of them obtained the best reading quality throughout the process. The experiment was performed on the 2016/17 crop in the agricultural area of the municipality of Dumont in the state of São Paulo, Brazil. The experimental design was based on the basic assumptions of statistical quality control and contained 63 sample points in a 30 × 30 m grid. The parameters were evaluated at 30, 45, 60, 75, and 119 days after sowing (DAS) using proximal sensing with GreenSeeker and OptRX sensors. We found that 45 and 60 DAS were the optimal times for monitoring peanut crop variability. For spatiotemporal monitoring of the culture with control charts, NDRE showed the best readings throughout the process when compared to NDVI and IRVI.

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Section: Introductionmentioning

confidence: 96%

“…Growth stage of peanuts with evaluation dates. Source: Rural Liquid Fertilizers -RLF Global (2017), adapted fromCarneiro (2018).…”

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confidence: 99%

Correlations Among Vegetation Indices and Peanut Traits During Different Crop Development Stages

et al. 2019

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“…Unfortunately, because of rapidly changing weather conditions, with unexpectedly long periods of drought or rainfall and therefore delayed harvest, soybean shattering in the field, or during harvest, are becoming more frequent. These factors have been directly correlated to higher losses ( Menezes et al, 2018 ; Zhang et al, 2018 ; Silveira et al, 2019 ), averaging 120 kg/ha in Brazil ( Schanoski et al, 2011 ), or up to 319 kg/ha in the Southeastern United States ( Philbrook and Oplinger, 1989 ).…”

Section: Introductionmentioning

confidence: 99%

Ascophyllum nodosum Extract (SealicitTM) Boosts Soybean Yield Through Reduction of Pod Shattering-Related Seed Loss and Enhanced Seed Production

et al. 2021

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Soybean is one of the most valuable commercial crops because of its high protein, carbohydrate, and oil content. The land area cultivated with soybean in subtropical regions, such as Brazil, is continuously expanding, in some instances at the expense of carbon storing natural habitats. Strategies to decrease yield/seed losses and increase production efficiency are urgently required to meet global demand for soybean in a sustainable manner. Here, we evaluated the effectiveness of an Ascophyllum nodosum extract (ANE), SealicitTM, in increasing yields of different soybean varieties, in two geographical regions (Canada and Brazil). In addition, we investigated the potential of SealicitTM to reduce pod shattering at the trials in Brazil. Three different concentrations of SealicitTM were applied to pod shatter-susceptible (SS) UFUS 6901 and shatter-resistant (SR) UFUS 7415 varieties to assess their impact on pod firmness. SS variety demonstrated a significant decrease in pod shattering, which coincided with deregulation of GmPDH1.1 and GmSHAT1–5 expression, genes that determine pod dehiscence, and higher seed weight per pod. SealicitTM application to the SR variety did not significantly alter its inherent pod shatter resistance, but provided higher increases in seed yield at harvest. This yield increase maybe associated with to other yield components stimulated by the biostimulant. This work demonstrates that SealicitTM, which has previously been shown to improve pod firmness in Arabidopsis and selected commercial oilseed rape varieties through IND gene down-regulation, also has the potential to improve pod resistance and seed productivity in soybean, a member of the legume family sharing a similar strategy for seed dispersal.

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“…Improvement in peanut harvesting techniques can provide higher operational efficiency, but the determination of harvest losses is necessary to achieve this (Butts et al, 2009). In crops such as soybean and corn, the loss ratio is practically defined by monitoring and adjusting internal mechanisms as well as the harvester's displacement speed, which can reduce losses and increase the quality process (Menezes et al, 2018Paixão et al, 2017a).…”

Section: Introductionmentioning

confidence: 99%

Does Moisture in Pods Interfere With Mechanized Harvesting of Peanuts?

et al. 2021

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Although peanut harvesting results in significant losses, it has rarely been investigated. Thus, this study aimed to analyze the interference of different pod moisture contents on peanut harvesting and their influence on the process quality based on losses and impurities. An experiment was performed in a peanut seed producing area, in Luzitânia, district of Jaboticabal-SP, using average moisture contents of 15% and 20% in the pods; 16 and 14 data points were collected for the 20% and 15% treatments, respectively. The experimental design used statistical process control (SPC) to analyze the collected variables. The results indicated higher losses in the platform than in the machine. In addition, the harvest quality was not affected by the pod moisture content. However, the correct adjustment of machines can restrict total losses to approximately 1% of the yield. Pods with moisture contents of 15% and 20% can be used for peanut harvesting. However, although a pod moisture content of 15% reduced the amount of mineral and vegetal impurities inside the bulk tank, the number of open pods increased, whereas a pod moisture content of 20% provided a greater number of whole pods.

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Can combine headers and travel speeds affect the quality of soybean harvesting operations?

Cited by 21 publications

References 12 publications

Correlations Among Vegetation Indices and Peanut Traits During Different Crop Development Stages

Correlations Among Vegetation Indices and Peanut Traits During Different Crop Development Stages

Ascophyllum nodosum Extract (SealicitTM) Boosts Soybean Yield Through Reduction of Pod Shattering-Related Seed Loss and Enhanced Seed Production

Does Moisture in Pods Interfere With Mechanized Harvesting of Peanuts?

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