24 research outputs found
Rapid Prediction of Nutrient Concentration in Citrus Leaves Using Vis-NIR Spectroscopy
[EN] The nutritional diagnosis of crops is carried out through costly foliar ionomic analysis in laboratories. However, spectroscopy is a sensing technique that could replace these destructive analyses for monitoring nutritional status. This work aimed to develop a calibration model to predict the foliar concentrations of macro and micronutrients in citrus plantations based on rapid non-destructive spectral measurements. To this end, 592 'Clementina de Nules' citrus leaves were collected during several months of growth. In these foliar samples, the spectral absorbance (430-1040 nm) was measured using a portable spectrometer, and the foliar ionomics was determined by emission spectrometry (ICP-OES) for macro and micronutrients, and the Kjeldahl method to quantify N. Models based on partial least squares regression (PLS-R) were calibrated to predict the content of macro and micronutrients in the leaves. The determination coefficients obtained in the model test were between 0.31 and 0.69, the highest values being found for P, K, and B (0.60, 0.63, and 0.69, respectively). Furthermore, the important P, K, and B wavelengths were evaluated using the weighted regression coefficients (BW) obtained from the PLS-R model. The results showed that the selected wavelengths were all in the visible region (430-750 nm) related to foliage pigments. The results indicate that this technique is promising for rapid and non-destructive foliar macro and micronutrient prediction.This work is co-financed by the PNDR and GVA-IVIA (projects 52203, 52204 and by the EU through the ERDF of GVA 2021-2027).
Maylin Acosta thanks IFARHU-SENACYT for the Professional Excellence Scholarships, contract No. 270-2021-020. Sandra Munera thanks the Juan de la Cierva-Formación contract (FJC2021-047786-I) co-funded by MCIN/AEI/10.13039/501100011033 and European Union NextGenerationEU/PRTR.Acosta, M.; Quiñones, A.; Munera, S.; De Paz, JM.; Blasco, J. (2023). Rapid Prediction of Nutrient Concentration in Citrus Leaves Using Vis-NIR Spectroscopy. Sensors. 23(14):1-11. https://doi.org/10.3390/s23146530111231
Rapid Prediction of Nutrient Concentration in Citrus Leaves Using Vis-NIR Spectroscopy
The nutritional diagnosis of crops is carried out through costly foliar ionomic analysis in laboratories. However, spectroscopy is a sensing technique that could replace these destructive analyses for monitoring nutritional status. This work aimed to develop a calibration model to predict the foliar concentrations of macro and micronutrients in citrus plantations based on rapid non-destructive spectral measurements. To this end, 592 ‘Clementina de Nules’ citrus leaves were collected during several months of growth. In these foliar samples, the spectral absorbance (430–1040 nm) was measured using a portable spectrometer, and the foliar ionomics was determined by emission spectrometry (ICP-OES) for macro and micronutrients, and the Kjeldahl method to quantify N. Models based on partial least squares regression (PLS-R) were calibrated to predict the content of macro and micronutrients in the leaves. The determination coefficients obtained in the model test were between 0.31 and 0.69, the highest values being found for P, K, and B (0.60, 0.63, and 0.69, respectively). Furthermore, the important P, K, and B wavelengths were evaluated using the weighted regression coefficients (BW) obtained from the PLS-R model. The results showed that the selected wavelengths were all in the visible region (430–750 nm) related to foliage pigments. The results indicate that this technique is promising for rapid and non-destructive foliar macro and micronutrient prediction
Non-destructive evaluation of external and internal table grape quality
Thesis (PhDAgric)--Stellenbosch University, 2021.ENGLISH ABSTRACT: Determining the correct harvest maturity parameters of table grapes is an essential step before
harvesting. The chemical analysis of table grapes to determine harvest and quality parameters
such as total soluble solids (TSS), titratable acidity (TA) and pH, is very time-consuming,
expensive, and destructive. Developing faster and more cost-effective methods to obtain the
information can benefit the table grape industry by reducing losses suffered at the postharvest
stage. There are multitudes of factors that can influence table grape postharvest quality leading
to huge losses. These losses are exacerbated even further by the long list of postharvest
external and internal defects that can occur, including browning in all its various manifestations.
The application of cutting-edge technologies such as Fourier Transform Near-Infrared (FT-NIR)
spectroscopy that can accurately assess the external and internal quality of fruit is, therefore,
essential. This particularly concerns the identification of defects or assessment of the risks of
defects that are likely to develop during post storage. The aim of this application would thus be
to evaluate these new technologies to monitor table grape quality non-destructively, before,
during, and/or after harvest.
This study, therefore, focussed on the development and optimisation of faster, cost-
effective, and fit-for-purpose methods to monitor harvest maturity and quality of table grapes in
the vineyard before harvesting and during packaging and cold storage. Harvest of three
different cultivars, namely, Thompson Seedless, Regal Seedless and Prime, happened over two
seasons (2016 and 2017) from six different commercial vineyards. Five of these vineyards were
in the Western Cape (two in the Hex River Valley, three in Wellington) and one in the Northern
Cape (Kakamas), South Africa. Harvest occurred twice at each vineyard, at optimum ripeness
and two weeks later (after the optimum harvest date). The incidence and intensity of browning
on each berry on a bunch were evaluated for different defects and browning phenotypes.
Quantitative harvest maturity and indicative quality parameters such as TSS, TA and pH, as well
as the sensory-related parameters – sugar:acid ratio (TSS:TA ratio) and BrimA, were
investigated by scanning whole table grape bunches contactless with Bruker’s MATRIX-F
spectrometer in the laboratory. Partial Least Squares (PLS) regression was used to build
prediction models for each parameter. Two different infrared spectrometers, namely the Bruker
Multipurpose Analyser Fourier Transform Near-Infrared (MPA FT-NIR) and MicroNIR Pro 1700
were also used to determine TSS on whole table grape berries. The MicroNIR Pro 1700 was
utilised in the vineyard and the laboratory and the MPA only in the laboratory. The same
spectral dataset used to build the quantitative models was used to build classification models for
two browning phenotypes, namely chocolate browning and friction browning. Partial Least
Squares Discriminant Analysis (PLS-DA) and Artificial Neural Networks (ANN) were used for the
classification tasks.
Key results showed that the incidence and intensity of different defects and browning
phenotypes such as sulphur dioxide (SO2) damage were prevalent on all three white seedless
table grape cultivars. The incidences of fungal infection, sunburn and abrasion damage were
high on Regal Seedless and Thompson Seedless in 2016. Contact browning, mottled browning
and friction browning and bruising damage had higher incidences in 2017 than in 2016. Overall,
the intensity of defects was very high in 2016 except on Regal Seedless from Hex River Valley.
Prime from Kakamas and Wellington had the highest intensity of defects in 2017, which
appeared on the grapes after 7 weeks of cold storage.
Prediction models were successfully developed for TSS, TA, TSS:TA, pH, and BrimA minus
acids on intact table grape bunches using FT-NIR spectroscopy in a contactless measurement
mode, and applying spectral pre-processing techniques for regression analysis with PLS. The
combination of Savitzky-Golay first derivative coupled with multiplicative scatter correction on
the original spectra delivered the best models. Statistical indicators used to evaluate the models
were the number of latent variables (LV) used to build the model, the prediction correlation
coefficient (R2p) and root mean square error of prediction (RMSE). For the respective
parameters TSS, TA, TSS:TA ratio, pH, and BrimA, the number of LV used when the models
were build according to a random split of the calibration and validation set were 6, 4, 5, 5 and
10, the R2p = 0.81, 0.43, 0.66, 0.27, and 0.71, and the RMSEP = 1.30 °Brix, 1.09 g/L, 7.08,
0.14, and 1.80. When 2016 was used as the calibration set and 2017 as the validation set in
model building the number of LV used were 9, 5, 5, 4 and the R2p = 0.44, 0.06, 0.17, 0.05, and
0.05 and the RMSEP = 3.22 °Brix, 2.41 g/L, 14.53, 0.21, and 8.03 for for the respective
parameters.
Determining TSS of whole table grape berries in the vineyard before and after harvesting
using handheld and benchtop spectrometers on intact table grape berries showed that spectra
taken in the laboratory with the MicroNIR were more homogenous than those taken in the
vineyard with the same spectrometer, over the two years investigated. The results obtained with
the MPA were not as good as those obtained with the MicroNIR in the laboratory were. The
model constructed with the combined data of 2016 and 2017 taken in the laboratory with the
MicroNIR had the best statistics in terms of R2p (0.74) and RPDp (1.97). The model constructed
with the 2017 data obtained in the laboratory with the MicroNIR had the lowest prediction error
(RMSEP = 1.13°Brix).
Good models were obtained using PLS-DA and ANN to classify bunches as either clear or
as having chocolate browning and friction browning based on the spectra obtained from intact
table grape bunches with the MATRIX-F spectrometer. The classification error rate (CER),
specificity and sensitivity were used to evaluate the models constructed using PLS-DA and the
kappa score was used for ANN. The CER for chocolate browning (25%) was better than that of
friction browning (46%) after Weeks 3 and 4 in cold storage for both class 0 (absence of
browning) and class 1 (presence of browning). Both the specificity and sensitivity of class 0 and
class 1 of friction browning were not as good as for chocolate browning. With ANN, the testing
kappa score to classify table grape bunches as clear or having chocolate browning or friction
browning showed that chocolate browning could be classified with the strong agreement after
Weeks 3 and 4 and Weeks 5 and 6 and that friction browning could be classified with moderate
agreement after three and four weeks in cold storage. Classification of chocolate browning and
friction browning phenotypes was done using PLS-DA and ANN and the result showed that both
types of browning can be classified with moderate agreement.
The implications of the results of this study for the table grape industry are that the industry
can move beyond just assessing methods and techniques in the laboratory towards
implementation in the vineyard and the packhouse. Much quicker decisions regarding grape
quality and destination of export can now be made using a combination of the MicroNIR
handheld and MATRIX-F instruments for onsite quality measurement and the models to predict
internal (e.g. TSS) and external (browning) quality attributes.AFRIKAANSE OPSOMMING: Die bepaling van die korrekte oesrypheidsparameters van tafeldruiwe is 'n noodsaaklike stap
voor oes. Chemiese ontleding van tafeldruiwe om oes- en kwaliteitsparameters te bepaal, soos
totale oplosbare vaste stowwe (TOVS), titreerbare suur (TS) en pH, is baie tydrowend, duur en
vernietigend. Die ontwikkeling van vinniger en kostedoeltreffender maniere om die inligting te
bekom, kan die tafeldruifbedryf bevoordeel deur verliese wat in die na-oesstadium gely word, te
verminder. Dit sluit die menigte faktore in wat die gehalte van tafeldruiwe ná oes kan beïnvloed
en tot verliese lui. Hierdie verliese word nog verder vererger deur die lang lys van verskillende
na-oes-verwante gebreke wat kan voorkom, insluitend verbruining in al sy verskillende
manifestasies. Die toepassing van toonaangewende tegnologieë soos Fourier-transform-naby-
infrarooi (FT-NIR) spektroskopie wat die eksterne en interne kwaliteit van vrugte akkuraat kan
beoordeel, is dus noodsaaklik. Dit is veral die identifisering van gebreke, of die beoordeling van
die risiko's van gebreke, wat waarskynlik tydens die opberging kan ontstaan. Die doel van
hierdie toepassing was dus om hierdie nuwe tegnologieë te evalueer om die kwaliteit van
tafeldruiwe nie-vernietigend te monitor, voor, tydens en/of ná oes.
Hierdie studie het dus gefokus op die ontwikkeling en optimalisering van vinniger, koste-
effektiewe en geskikte doeleindes om oesrypheid en kwaliteit van tafeldruiwe in die wingerd te
monitor voor oes en tydens verpakking en koelopberging. Druiwe-oes van drie verskillende
kultivars (Thompson Seedless, Regal Seedless en Prime) het gedurende twee jare (2016 en
2017) uit ses verskillende kommersiële wingerde plaasgevind. Vyf van hierdie wingerde was in
die Wes-Kaap (twee in die Hexriviervallei, drie in Wellington) en een in die Noord-Kaap
(Kakamas), Suid-Afrika. Die oes het twee keer by elke wingerd plaasgevind, dit wil sê op die
beste rypheid en twee weke later ná die optimale oesdatum. Die voorkoms en intensiteit van
verbruining op elke korrel op 'n tros is op verskillende defekte en verbruiningsfenotipes
geëvalueer. Kwantitatiewe oesrypheid en kwaliteitsindikatiewe parameters, naamlik TOVS, TS
en pH, sowel as sensoriese verwante parameters suiker:suur-verhouding (TOVS:TS-
verhouding) en BrimA is ondersoek deur heel tafeldruiftrosse sonder kontak met die Bruker se
MATRIX-F-spektrometer in die laboratorium te skandeer. Gedeeltelike minste kwadrate (GMK)
regressie is gebruik om modelle vir die parameters te bou. Twee verskillende infrarooi-
spektrometers naamlik (a) die Bruker Multipurpose Analyzer Fourier Transform Near-Infrared
(MPA FT-NIR) en (b) MicroNIR Pro 1700 is ook gebruik om TOVS op heel tafeldruifkorrels te
bepaal. Die MicroNIR Pro 1700 is in die wingerd en in die laboratorium gebruik en die MPA
slegs in die laboratorium. Met behulp van dieselfde spektrale datastel as die een wat gebruik
word om die kwantitatiewe modelle op te stel, is klassifikasiemodelle vir twee verskillende
verbruiningsfenotipes (sjokoladeverbruining en wrywingverbruining) gebou. Hierdie keer is
gedeeltelike minste-kwadrate-diskriminant-analise (GMK-DA) en kunsmatige neurale netwerke
(KNN) gebruik.
Die belangrike resultate het getoon dat die voorkoms en intensiteit van verskillende defekte
en verbruiningsfenotipes soos swaeldioksied (SO2)-skade op al drie wit pitlose tafeldruifkultivars
voorgekom het. Die voorkoms van swaminfeksie, sonbrand en skaafskuur was hoog op Regal
Seedless en Thompson Seedless in 2016. Kontak-, gevlekte- en wrywing verbruining sowel as
kneusplekke het in 2017 'n hoër voorkoms as in 2016 gehad. Oor die algemeen was die
intensiteit van defekte baie hoog in 2016 behalwe op Regal Seedless vanaf die Hexriviervallei.
Prime van Kakamas en Wellington het in 2017 die hoogste intensiteit van gebreke gehad wat
ná 7 weke se koelopberging op die druiwe verskyn het.
Die suksesvolle ontwikkeling van modelle vir TOVS, TS, TOVS:TS verhouding, pH en
BrimA op heel tafeldruiftrosse met behulp van FT-NIR-spektroskopie is bewys as inderdaad
moontlik – veral as GMK met verskillende spektrale voorverwerkingstegnieke gepaard gaan.
Statistiese aanwysers wat gebruik is om die modelle te evalueer, was die aantal latente
veranderlikes (LV) wat gebruik is om die model te bou, die voorspellingskorrelasiekoëffisiënt
(R2p) en wortelgemiddelde vierkante voorspellingsfout (WGVVF). Die kombinasie van die eerste
afgeleide Savitzky-Golay tesame met die vermenigvuldigende verstrooiingskorreksie op die
oorspronklike spektra het die beste modelle gelewer. Statistiese aanwysers wat gebruik is om
die modelle te evalueer, was die aantal latente veranderlikes (LV) wat gebruik is om die model
te bou, die voorspellingskorrelasiekoëffisiënt (R2p) en wortelgemiddelde vierkante
voorspellingsfout (RMSE). Vir die onderskeie parameters TSS, TA, TSS: TA-verhouding, pH en
BrimA, was die aantal LV wat gebruik is toe die modelle volgens 'n ewekansige verdeling van
die kalibrasie- en valideringstel gebou is, 6, 4, 5, 5 en 10, die R2p = 0,81, 0,43, 0,66, 0,27 en
0,71, en die RMSEP = 1,30 ° Brix, 1,09 g / l, 7,08, 0,14 en 1,80. Toe 2016 as die kalibrasiestel
gebruik is en 2017 as die validasieset in modelbou, was die aantal gebruikte LV 9, 5, 5, 4 en die
R2p = 0,44, 0,06, 0,17, 0,05 en 0,05 en die RMSEP = 3,22 ° Brix, 2,41 g / l, 14,53, 0,21 en 8,03
vir die onderskeie parameters. Die bepaling van TOVS van heel tafeldruifkorrels in die wingerd
voor en ná oes oor twee jaar met behulp van hand- en tafelbladspektrometers het getoon dat
spektra wat in die laboratorium met die MicroNIR geneem is meer homogeen was as dié wat in
die wingerd met dieselfde spektrometer geneem is. Die resultate wat met die MPA behaal is,
was nie so goed soos met die MicroNIR in die laboratorium nie. Die model wat saamgestel is
met die gekombineerde data van 2016 en 2017 wat in die laboratorium met die MicroNIR
geneem is, het die beste statistieke gehad in terme van die R2p (0.74) en die RPDp (1.97). Die
model wat opgestel is met die 2017 data wat in die laboratorium met die MicroNIR verkry is, het
die laagste voorspellingsfout (RMSEP = 1.13°Brix) gehad.
Goeie modelle is verkry met behulp van GMK-DA en KNN om trosse as skoon te
klassifiseer, of as sjokoladeverbruining en wrywingsverbruining gebaseer op die spektra van die
heel tafeldruiftrosse wat met die MATRIX-F-spektrometer geneem is. Die klassifikasiesyfer
(KS), spesifisiteit en sensitiwiteit is gebruik om die modelle wat met behulp van GMK-DA
saamgestel is, te evalueer en die kappa-telling is vir KNN gebruik. Die KS vir
sjokoladeverbruining (25%) was beter as dié van wrywingsverbruining (46%) vir week 3 en
week 4 vir beide klas 0 (afwesigheid van verbruining) en klas 1 (teenwoordigheid van
verbruining). Beide die spesifisiteit en sensitiwiteit van klas 0 en klas 1 vir wrywingverbruining
was nie so goed soos vir sjokoladeverbruining nie. Met KNN het die toetskappa-telling om
tafeldruiftrosse as skoon of sjokoladeverbruining of wrywingsverbruining te klassifiseer, getoon
dat sjokoladeverbruining tydens Week 3 en Week 4 en Week 5 en Week 6 met 'n matige
ooreenstemming geklassifiseer kan word en dat wrywingsverbruining met matige
ooreenstemming tydens Week 3 en Week 4 geklassifiseer kan word.
Die implikasies van hierdie resultate vir die tafeldruifbedryf is van so 'n aard dat die bedryf
nou verder kan gaan as om net metodes en tegnieke in die laboratorium te beoordeel, maar kan
beweeg na implementering in die wingerd en die pakhuis. Die neem van baie vinniger besluite
rakende die kwaliteit van die druiwe, dit wil sê in watter klas druiwe geplaas kan word en na
watter uitvoermark druiwe gestuur kan word, is nou moontlik. Veel vinniger besluite rakende
druiwekwaliteit en bestemming van uitvoer kan nou geneem word met behulp van 'n kombinasie
van die MicroNIR-hand- en MATRIX-F-instrumente vir kwaliteitsmeting in situ en die modelle om
interne (bv. TOVS) en eksterne (verbruining) kwaliteitseienskappe te voorspel.Doctora
Proceedings of the European Conference on Agricultural Engineering AgEng2021
This proceedings book results from the AgEng2021 Agricultural Engineering Conference under auspices of the European Society of Agricultural Engineers, held in an online format based on the University of Évora,
Portugal, from 4 to 8 July 2021.
This book contains the full papers of a selection of abstracts that were the base for the oral presentations and posters presented at the conference.
Presentations were distributed in eleven thematic areas: Artificial Intelligence, data processing and
management; Automation, robotics and sensor technology; Circular Economy; Education and Rural development; Energy and bioenergy; Integrated and sustainable Farming systems; New application
technologies and mechanisation; Post-harvest technologies; Smart farming / Precision agriculture; Soil, land and water engineering; Sustainable production in Farm buildings
Water productivity indices of the soybean grown on silty clay soil under sprinkler irrigation
The objective of this research was to compare the effects of different irrigation treatments on soybean [Glycine max (L.) Merr.] productivity and water use efficiency on experimental fields of the Maize Research Institute of Zemun Polje(Serbia), in 2007 and 2008. Four irrigation levels were investigated: full irrigation (I100), 65% and 40% of I100 (I65 and I40) and a rain-fed (I0) system. The crop water use efficiency (CWUE, also known as crop water productivity –CWP), irrigation water use efficiency (IWUE) and evapotranspiration water use efficiency (ETWUE) were used to assess the water productivity of each studied treatment. The efficiency of the same treatment differed between the years as it depended on seasonal water availability, weather conditions and their impact on seed yields. Maximum and minimum yields were obtained in the I65 and I0 treatments, averaging 3.41 t ha–1 and 2.26 t ha–1, respectively. Water use efficiency values were influenced by the irrigation levels. In general, CWUE values increased with the increased level of irrigation. In both growing seasons, IWUE and ETWUE decreased with increasing the seasonal water consumption and irrigation depth. On average, treatments I40 and I65 resulted in similar or higher CWUE and ETWUE than I100, in both growing seasons. I65 resulted in the highest IWUE, averaged over the two seasons, while I100 had the lowest IWUE. I65 could be proper for the soybean irrigated in Vojvodina when there is no water shortage and I45 could be used as a good basis for reduced sprinkler irrigation strategy development under water shortage
Project based-learning based on I-STEM (Islamic, Science, Technology, and Mathematics) to facilitate the development of geometric critical thinking skills of first middle students
In line with the 21st century, mathematics learning innovations continue to be developed to facilitate students' critical thinking skills by adjusting the context of their religious life. The purpose of this study is to provide ideas that teachers can do to implement Project Based Learning (PjBL) with a STEM (I-STEM) approach that is used to facilitate the development of students' critical thinking skills. The pattern of integration that is designed lies in the flat plane geometry material with the integration of the verses of the Koran and the internalization of Islamic values, with the hope of being able to create meaningful learning activities for students. This research is a qualitative research with library research. Data collection techniques are carried out through reviewing the literature, both from articles, books, and other documents that can be used to describe theories and information needed in research. The data analysis technique used is content analysis (content analysis). The results of this study are the I-STEM-based PjBL syntax includes 1) basic questions (integration with the verses of the Koran presented in the LKPD); 2) designing project plans (miniature Kaaba); 3) draw up a project completion schedule; 4) monitor project progress; 5) test project results (and compare with other problems); and 6) evaluate the learning experience. I-STEM-based PjBL was developed to facilitate the development of students' critical thinking skills through syntax and LKPD which were developed adapted to the context of Islamic life and the Koran at the junior high school level
Project based-learning based on I-STEM (Islamic, Science, Technology, and Mathematics) to facilitate the development of geometric critical thinking skills of first middle students
In line with the 21st century, mathematics learning innovations continue to be developed to facilitate students' critical thinking skills by adjusting the context of their religious life. The purpose of this study is to provide ideas that teachers can do to implement Project Based Learning (PjBL) with a STEM (I-STEM) approach that is used to facilitate the development of students' critical thinking skills. The pattern of integration that is designed lies in the flat plane geometry material with the integration of the verses of the Koran and the internalization of Islamic values, with the hope of being able to create meaningful learning activities for students. This research is a qualitative research with library research. Data collection techniques are carried out through reviewing the literature, both from articles, books, and other documents that can be used to describe theories and information needed in research. The data analysis technique used is content analysis (content analysis). The results of this study are the I-STEM-based PjBL syntax includes 1) basic questions (integration with the verses of the Koran presented in the LKPD); 2) designing project plans (miniature Kaaba); 3) draw up a project completion schedule; 4) monitor project progress; 5) test project results (and compare with other problems); and 6) evaluate the learning experience. I-STEM-based PjBL was developed to facilitate the development of students' critical thinking skills through syntax and LKPD which were developed adapted to the context of Islamic life and the Koran at the junior high school level