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Biochar can improve soil nutrient retention and alleviate salinity; however, use is not widespread due to cost. Biochar is usually co-applied with a full-rate of supplementary fertiliser before planting. This study investigated co-application of bamboo biochar with organic fertiliser and amendments on nutrient cycling, plant growth, yield and commercial value of ginger. Four treatments were applied including no amendment, organic amendments and organic amendments co-applied with biochar at two applications rates of 10 t ha−1 and 30 t ha−1. Plant growth, biomass, foliar nutrient and water-extractable soil nutrients were examined. Co-applied high rate biochar increased available soil potassium (K) concentration (+ 89%) over 22 weeks and led to increased foliar K concentration (+ 25%) at harvest and after 30 weeks compared with organic amendments alone. Biochar high rate decreased soil sodium concentration (− 22%) over 22 weeks. Biochar high rate increased root mass fraction and plant height but decreased the number of stems, and therefore, did not increase aboveground biomass compared with all other treatments. In contrast, ginger rhizome yield, grade and commercial value were not affected by biochar treatments. Added biochar provided additional net K that improved foliar concentration late in the growing season following dissolution. The additional K supply then stimulated root growth and biomass re-allocation despite daily irrigation throughout the growing season. Therefore, we suggest biochar as a useful amendment to prevent nutrient loss and alleviate salinity for organic crops.

Fast and real-time prediction of leaf nutrient concentrations can facilitate decision-making for fertilisation regimes on farms and address issues raised with over-fertilisation. Cacao (Theobroma cacao L.) is an important cash crop and requires nutrient supply to maintain yield. This project aimed to use chemometric analysis and wavelength selection to improve the accuracy of foliar nutrient prediction. We used a visible-near infrared (400–1000 nm) hyperspectral imaging (HSI) system to predict foliar calcium (Ca), potassium (K), phosphorus (P) and nitrogen (N) of cacao trees. Images were captured from 95 leaf samples. Partial least square regression (PLSR) models were developed to predict leaf nutrient concentrations and wavelength selection was undertaken. Using all wavelengths, Ca (R2CV = 0.76, RMSECV = 0.28), K (R2CV = 0.35, RMSECV = 0.46), P (R2CV = 0.75, RMSECV = 0.019) and N (R2CV = 0.73, RMSECV = 0.17) were predicted. Wavelength selection increased the prediction accuracy of Ca (R2CV = 0.79, RMSECV = 0.27) and N (R2CV = 0.74, RMSECV = 0.16), while did not affect prediction accuracy of foliar K (R2CV = 0.35, RMSECV = 0.46) and P (R2CV = 0.75, RMSECV = 0.019). Visible-near infrared HSI has a good potential to predict Ca, P and N concentrations in cacao leaf samples, but K concentrations could not be predicted reliably. Wavelength selection increased the prediction accuracy of foliar Ca and N leading to a reduced number of wavelengths involved in developed models.

Hyperspectral image analysis in laboratory-based settings has the potential to estimate soil elements. This study aimed to explore the effects of soil particle size on element estimation using visible-near infrared (400–1000 nm) hyperspectral imaging. Images were captured from 116 sieved and ground soil samples. Data acquired from hyperspectral images (HSI) were used to develop partial least square regression (PLSR) models to predict soil available aluminum (Al), boron (B), calcium (Ca), copper (Cu), iron (Fe), potassium (K), magnesium (Mg), manganese (Mn), sodium (Na), phosphorus (P) and zinc (Zn). The soil available Al, Fe, K, Mn, Na and P were not predicted with high precision. However, the developed PLSR models predicted B (R2CV = 0.62 and RMSECV = 0.15), Ca (R2CV = 0.81 and RMSECV = 260.97), Cu (R2CV = 0.74 and RMSECV = 0.27), Mg (R2CV = 0.80 and RMSECV = 43.71) and Zn (R2CV = 0.76 and RMSECV = 0.97) in sieved soils. The PLSR models using reflectance of ground soil were also developed for B (R2CV = 0.53 and RMSECV = 0.16), Ca (R2CV = 0.81 and RMSECV = 260.79), Cu (R2CV = 0.73 and RMSECV = 0.29), Mg (R2CV = 0.79 and RMSECV = 45.45) and Zn (R2CV = 0.76 and RMSECV = 0.97). RMSE of different PLSR models, developed from sieved and ground soils for the corresponding elements did not significantly differ based on the Levene's test. Therefore, this study indicated that it was not necessary to grind soil samples to predict elements using HSI.

Biochar has agronomic potential but currently is too expensive for widespread adoption. New methodologies are emerging to reduce the cost such as enriching biochar with nutrients that match crops and soil requirements. However, the effects of biochar-based fertilisers on plant yield and soil nutrient availability have not been widely examined. This study investigated the effects of a novel organo-mineral biochar fertiliser in comparison to organic and commercial biochar fertiliser on ginger (Zingiber officinale Canton). There were four treatments: (1) commercial organic fertiliser (5 t ha−1), as the control; (2) commercial biochar-based fertiliser (5 t ha−1); (3) organo-mineral biochar fertiliser at low rate (3 t ha−1); and (4) organo-mineral biochar fertiliser at high rate (7.5 t ha−1). A replicated pot trial was established with black dermosol soil and ten replicate pots for each treatment. Ginger was planted and grown for 30 weeks. Plant growth, biomass, foliar nutrients and water extractable soil nutrients including phosphorus (P), potassium (K) and calcium (Ca) were examined. High rate organo-mineral biochar fertiliser increased soil P and K availability at week 30 (harvest) after planting, compared to all other treatments and low rate organo-mineral biochar fertiliser performed similarly to the organic control for P and K. High rate organo-mineral biochar fertiliser increased total foliar nutrient content at week 30 in P, K and Ca compared to commercial biochar fertiliser. High rate organo-mineral biochar fertiliser improved the commercial value of ginger (+ 36%) due to a shift in the proportion of higher grade rhizomes. Low rate organo-mineral biochar fertiliser plants displayed similar yield, total dry and aboveground biomass to commercial organic fertiliser. Commercial biochar fertiliser had significantly lower biomass measures compared with other treatments as the rate applied had lower nutrient concentrations. Our results show organo-mineral biochar fertilisers could be substituted for commercial organic fertilisers at low rates to maintain similar yield or applied at high rates to increase commercial value where economically feasible.

Organo-mineral biochar fertiliser has the potential to replace conventional biochar and organic fertiliser to improve soil quality and increase plant photosynthesis. This study explored mechanisms involved in nitrogen (N) cycling in both soil and ginger plants (Zingiber officinale: Zingiberaceae) following different treatments including organic fertiliser, commercial bamboo biochar fertiliser, and organo-mineral biochar fertiliser. Soil received four treatments including (1) commercial organic fertiliser (5 t ha−1) as the control, (2) commercial bamboo biochar fertiliser (5 t ha−1), (3) organo-mineral biochar fertiliser at a low rate (3 t ha−1), and (4) organo-mineral biochar fertiliser at a high rate (7.5 t ha−1). C and N fractions of soil and plant, and gas exchange measurements were analysed. Initially, organo-mineral biochar fertiliser applied at the low rate increased leaf N. Organo-mineral biochar fertiliser applied at the high rate significantly increased N use efficiency (NUE) of the aboveground biomass compared with other treatments and improved photosynthesis compared with the control. There was N fractionation during plant N uptake and assimilation since the 15N enrichment between the root, leaf, and stem were significantly different from zero; however, treatments did not affect this N fractionation. Organo-mineral biochar fertiliser has agronomic advantages over inorganic and raw organic (manure-based) N fertiliser because it allows farmer to put high concentrations of nutrients into soil without restricting N availability, N uptake, and plant photosynthesis. We recommend applying the low rate of organo-mineral biochar fertiliser as a substitute for commercial organic fertiliser.

Hyperspectral image (HSI) analysis has the potential to estimate organic compounds in plants and foods. Curcumin is an important compound used to treat a range of medical conditions. Therefore, a method to rapidly determine rhizomes with high curcumin content on-farm would be of significant advantage for farmers. Curcumin content of rhizomes varies within, and between varieties but current chemical analysis methods are expensive and time consuming. This study compared curcumin in three turmeric (Curcuma longa) varieties and examined the potential for laboratory-based HSI to rapidly predict curcumin using the visible–near infrared (400–1000 nm) spectrum. Hyperspectral images (n = 152) of the fresh rhizome outer-skin and flesh were captured, using three local varieties (yellow, orange, and red). Distribution of curcuminoids and total curcumin was analysed. Partial least squares regression (PLSR) models were developed to predict total curcumin concentrations. Total curcumin and the proportion of three curcuminoids differed significantly among all varieties. Red turmeric had the highest total curcumin concentration (0.83 ± 0.21%) compared with orange (0.37 ± 0.12%) and yellow (0.02 ± 0.02%). PLSR models predicted curcumin using raw spectra of rhizome flesh and pooled data for all three varieties (R2c = 0.83, R2p = 0.55, ratio of prediction to deviation (RPD) = 1.51) and was slightly improved by using images of a single variety (orange) only (R2c = 0.85, R2p = 0.62, RPD = 1.65). However, prediction of curcumin using outer-skin of rhizomes was poor (R2c = 0.64, R2p = 0.37, RPD = 1.28). These models can discriminate between ‘low’ and ‘high’ values and so may be adapted into a two-level grading system. HSI has the potential to help identify turmeric rhizomes with high curcumin concentrations and allow for more efficient refinement into curcumin for medicinal purposes.