Table 1 Summary table of reported to date Raman studies on botanicals

Disease diagnostics

 Tomato, leaf

Liberibacter disease in tomatoes [8]

Handheld spectrometer (λ = 830 nm; P = 495 mW; T = 1 s)

–

747 cm⁻¹ (pectin); 1000, 1115, 1155, 1184, 1218 and 1525 cm⁻¹ (carotenoids)

Liberibacter disease in tomatoes is associated with degradation and fragmentation of host carotenoids and pectin

 Orange and grapefruit, leaves

Huanglongbing (HLB) or citrus greening [23]

Handheld spectrometer (λ = 830 nm; P = 495 mW; T = 1 s)

1601–1630 cm⁻¹ (phenylpropanoids; 1440–1455 cm⁻¹ (aliphatic)

1184 and 1218 cm⁻¹ (xylan, carotenoids); 1525 cm⁻¹ (carotenoids), as well as 1288 cm⁻¹ (aliphatic); 1155 and 1326 cm⁻¹ (cellulose)

HLB is associated with an increase in phenylpropanoids and decrease in xylan, carotenoids and cellulose

 Orange and grapefruit, leaves

Nutrient deficiency in citrus trees [23]

Handheld spectrometer (λ = 830 nm; P = 495 mW; T = 1 s)

1247, 1601–1630 cm⁻¹ (phenylpropanoids; 1440–1455 cm⁻¹ (aliphatic)

1184 and 1218 cm⁻¹ (xylan, carotenoids)

ND is associated with an increase in phenylpropanoids

 Orange, leaf

Canker [22]

Handheld spectrometer (λ = 830 nm; P = 495 mW; T = 1 s)

–

1601–1630 cm⁻¹ (phenylpropanoids)

Canker is associated with a decrease in phenylpropanoids content

 Orange, leaf

HLB and blight [22]

Handheld spectrometer (λ = 830 nm; P = 495 mW; T = 1 s)

–

–

Diagnostics was achieved via the use of PLS-DA

 Wheat, grain

Ergot [15]

Handheld spectrometer (λ = 1064 nm; P = 200 mW; T = 30 s)

1650 and 1667 cm⁻¹ (proteins)

–

ergot infection may be associated with expression and deposition of alpha-helical and beta-sheet proteins

 Wheat, grain

Black tip [15]

Handheld spectrometer (λ = 1064 nm; P = 200 mW; T = 30 s)

1348 cm⁻¹ (monomeric sugars) and 1600 cm⁻¹ (lignin); shift of 862 peak to 856 cm⁻¹ (pectin)

862 and 937 cm⁻¹ (starch)

black tip may degrade lignin and ferment starch into monomeric sugars; esterification of pectin

 Sorghum, grain

Mold [15]

Handheld spectrometer (λ = 1064 nm; P = 200 mW; T = 30 s)

shift of 856 peak to 862 cm⁻¹ (pectin); change in ratio between 1518 cm⁻¹ and 1541 cm⁻¹ peaks (carotenoids)

1600 and 1630 cm⁻¹ (phenylpropanoids)

Degradation of phenylpropanoids; a decrease in methylesterfication of pectin caused by the infections; suggest a decrease in the length of conjugated double bonds of carotenoids

 Sorghum, grain

Ergot [15]

Handheld spectrometer (λ = 1064 nm; P = 200 mW; T = 30 s)

1150, 940, 1124 and 1083 cm⁻¹ (monomeric sugars); shift of 856 peak to 862 cm⁻¹ (pectin); change in ratio between 1518 cm⁻¹ and 1541 cm⁻¹ peaks (carotenoids)

1600 and 1630 cm⁻¹ (phenylpropanoids)

ergot hydrolyzes starches to produce monomeric sugars; a decrease in methylesterfication of pectin caused by the infections; suggest a decrease in the length of conjugated double bonds of carotene

 Maize, grain

Fusarium spp [16]

Handheld spectrometer (λ = 1064 nm; P = 200 mW; T = 30 s)

1658 cm⁻¹ (protein); 1153 cm⁻¹ (starch)

1600 and 1633 cm⁻¹ (phenylpropanoids); 1547 cm⁻¹ (shifted from 1523 cm⁻¹ in healthy) species (carotenoids)

Fusarium infection is associated with degradation of phenylpropanoids and deposition of protein in maize kernels; pathogen converts monomeric sugars polymeric carbohydrates

 Maize, grain

Aspergillus flavus [16]

Handheld spectrometer (λ = 1064 nm; P = 200 mW; T = 30 s)

1003–1115 cm⁻¹ (monomeric sugars); 1600–1633 (phenylpropanoids)

1600 and 1633 cm⁻¹ (phenylpropanoids); 1547 cm⁻¹ (shifted from 1523 cm⁻¹ in healthy) species (carotenoids); 1153 cm⁻¹ (starch)

A. flavus is associated with a breakdown maize starch into monomeric sugars

 Maize, grain

A. niger [16]

Handheld spectrometer (λ = 1064 nm; P = 200 mW; T = 30 s)

1153 cm⁻¹ (starch); 1600–1633 (phenylpropanoids)

1600 and 1633 cm⁻¹ (phenylpropanoids); 1547 cm⁻¹ (shifted from 1523 cm⁻¹ in healthy) species (carotenoids)

A. niger converts monomeric sugars polymeric carbohydrates

 Maize, grain

Diplodia spp. [16]

Handheld spectrometer (λ = 1064 nm; P = 200 mW; T = 30 s)

1003–1115 cm⁻¹ (monomeric sugars)

1153 cm⁻¹ (starch)

Diplodia is associated with a breakdown maize starch into monomeric sugars

 Abutilon hybridum, leaf

Abutilon mosaic virus [29]

Handheld spectrometer (λ = 1064 nm; P = 200 mW; T = 8 s)

1605–1629 (phenylpropanoids); 1440–1460 cm⁻¹ (aliphatic)

–

Abutilon mosaic virus is associated with an increase in phenylpropanoids in Abutilon hybridum

 Tomatoes, leaf

Tomato yellow leaf curl Sardinia virus (TYCLSV) [45]

Benchtop spectrometer (λ = 780 nm; P = 2mW; T = 5–10 s)

1608 cm⁻¹ (phenolic); 1483 cm⁻¹ (aliphatic)

1526 cm⁻¹ (carotenoids); 1420, 1483 cm⁻¹ (aliphatic), 1500, 1608 cm⁻¹ (phenolic); 1353 cm⁻¹ (unidentified);

Small changes in plant biochemistry

 Tomatoes, leaf

Tomato spotted wilt virus (TSWV) [45]

Benchtop spectrometer (λ = 780 nm; P = 2mW; T = 5–10 s)

1608 cm⁻¹ (phenolic); 1438 cm⁻¹ (aliphatic); 1353 cm⁻¹ (unidentified);

1483 cm⁻¹ (aliphatic)

Small changes in plant biochemistry

 Wheat, leaf

Barley yellow dwarf virus (BYDV) [36]

Handheld spectrometer (λ = 830 nm; P = 495 mW; T = 1 s)

1601–1630 cm⁻¹ (phenylpropanoids)

1000, 1115, 1156, 1186, 1218 and 1525 cm⁻¹ (carotenoids)

BYDV is associated with an increase in phenylpropanoids and decrease in carotenoids

 Wheat, leaf

Wheat streak mosaic virus (WSMV) [36]

Handheld spectrometer (λ = 830 nm; P = 495 mW; T = 1 s)

1601–1630 cm⁻¹ (phenylpropanoids)

1000, 1115, 1156, 1186 and 1218 cm⁻¹ (carotenoids)

WSMV is associated with an increase in phenylpropanoids and decrease in carotenoids

 Potato, tubers

Zebra chip [112]

Handheld spectrometer (λ = 830 nm; P = 495 mW; T = 1 s)

–

1153 (carbohydrates)

Zebra chip is associated with degradation of carbohydrates in tubers

 Potato, tubers

Virus Y [112]

Handheld spectrometer (λ = 830 nm; P = 495 mW; T = 1 s)

1153 cm⁻¹ (carbohydrates)

Virus Y is associated with an increase in carbohydrates in tubers

Abiotic stresses

 Coleus lime (Plectranthus scutellarioides), leaves

Saline, light, drought and cold [26]

Benchtop spectrometer (λ = 532 nm; P = 10 mW; T = 10 s)

620 and 740 cm⁻¹ (anthocyanins)

1000 and 1170 cm⁻¹ (carotenoids)

Saline, light, drought and cold stresses cause an increase in anthocyanins and a decrease in carotenoids

 Arabidopsis thaliana, leaves

Nitrogen deficiency [10]

Postable spectrometer (λ = 830 nm; P = 100 mW; T = 10 s)

–

1064 cm⁻¹ (nitrate)

1046 cm^–1 peak intensity correlates with the nitrate content in Arabidopsis plants

 Rice, leaves

Nitrogen deficiency [8]

Handheld spectrometer (λ = 830 nm; P = 495 mW; T = 1 s)

1600–1630 cm⁻¹ (phenylpropanoids)

1115–1218 cm⁻¹ (carotenoids)

Nitrogen deficiency is associated with a decrease in carotenoids and increase in phenylpropanoids

 Rice, leaves

Phosphorus and potassium deficiencies [8]

Handheld spectrometer λ = 830 nm; P = 495 mW; T = 1 s)

Small changes in 1600–1630 cm⁻¹ (phenylpropanoids)

Small changes in 1115–1218 cm⁻¹ (carotenoids)

Phosphorus and potassium deficiencies are associated with a decrease in carotenoids and increase in phenylpropanoids

Identification of plant species and their varieties; nutritional analysis

 Poison ivy, leaves

Farber et al. [36]

Handheld spectrometer (λ = 830 nm; P = 495 mW; T = 1 s)

1717 cm⁻¹ (carboxyl or ester groups)

1717 cm⁻¹ band can be used to identify poison ivy

 Peanuts, leaves and seeds

Farber et al. [36]

Handheld spectrometer (λ = 830 nm; P = 495 mW; T = 1 s)

Identification: all bands

Nutritional analysis: 1005 cm⁻¹ (proteins), 1301 cm⁻¹ (carbohydrates), 1443 cm⁻¹ (oils), 1606 cm⁻¹ (fiber), 1656 cm⁻¹ (unsaturated fatty acids), and 1748 cm⁻¹ (esters)

Identification of peanut varieties can be achieved though spectroscopic analysis of leaves and seeds with 80% and 95% accuracy, respectively. RS can be used to predict relative concentration of proteins, carbohydrates, oils, fiber, unsaturated fatty acids and esters in peanut seeds

 Potato, tubers

Morey et al. [34]

Handheld spectrometer (λ = 830 nm; P = 495 mW; T = 1 s)

Identification: all bands

Nutritional analysis: 1126 cm⁻¹ (starch), 1527 cm⁻¹ (carotenoids), 1600 cm⁻¹ (phenylpropanoids), 1660 cm⁻¹ (proteins)

Identification of potato varieties can be achieved though spectroscopic analysis of tubers with 77.5% accuracy. RS can be used to predict relative concentration of proteins, carotenoids, starch and phenylpropanoids in potato tubers

 Corn, kernels

Krimmer et al. [21]

Handheld spectrometer (λ = 830 nm; P = 495 mW; T = 1 s)

Identification: all bands

Nutritional analysis: 479 cm⁻¹ (starch), 1527 cm⁻¹ (carotenoids), 1600/1632 cm⁻¹ (phenylpropanoids), 1000/1660 cm⁻¹ (proteins)

Identification of corn varieties can be achieved though spectroscopic analysis of kernels with 95% accuracy. RS can be used to predict relative concentration of proteins, carotenoids, and starch in corn kernels

 Citrus, fruits

Feng et al. [74]

Benchtop spectrometer (λ = 514 nm; P = 20 mW; T = 10 s)

All bands

RS can be used to identify citrus fruits

 Loquat, fruits

Zhu et al. [47]

Benchtop spectrometer (λ = 532 nm; P = 25 mW; T = 1 s)

1602 cm⁻¹ (lignin)

RS can be used to determine fruit ripening

 Tomatoes, fruits

Martin et al. [77]

Benchtop spectrometer (λ = 532 nm; P = 46–50 mW; T = 10 s)

1150, 1257 cm⁻¹ (carotenoids)

RS can be used to predict tomato ripeness

 Mandarin oranges, fruits

Nekvapil et al. [79]

Benchtop spectrometer (λ = 532 nm; P = 200 mW; T = 10 s)

1100–1250, 1527 cm⁻¹ (carotenoids)

RS can be used to predict fruit freshness

 Wheat, grain

Piot et al. [80]

Benchtop spectrometer (λ = ’red light’; P = 8 mW)

471–485 cm⁻¹ (starch), 1065–1140 cm⁻¹ (lipids), 1630–1670 cm⁻¹ (protein)

RS can be used to probe concentration of starch, lipids and proteins in the grain

 Coffee, beans

Keidel et al. [81]

Benchtop spectrometer (λ = 1064 nm; P = 300 mW)

Identification: all bands

Kahweol concentration: 1479 and 1567 cm⁻¹

RS can be used to predict the geographical origins of coffee beans

 Hemp and cannabis

Sanchez et al. [8]

Handheld spectrometer (λ = 830 nm; P = 495 mW; T = 1 s)

Identification: all bands

Cannabinoid content: 780, 1295, 1623, and 1666 cm⁻¹

RS can be used to identify cannabis varieties and determine concentrations of cannabinoids in the plant