ACS agricultural science & technology最新文献

Pandanus amaryllifolius Roxb. (pandan) and Cocos nucifera L. (coconut) are traditional economic crops widely cultivated in tropical and subtropical regions, with intercropping being common in South and Southeast Asia. However, the effect of intercropping with coconut on the growth and quality of pandan has received little attention at present. Therefore, a field experiment was conducted to evaluate the effects of intercropping modes on soil physicochemical properties, agronomic traits, photosynthetic characteristics, and volatile compound content of pandan. The results revealed that intercropping significantly enhanced soil moisture, leaf area, chlorophyll content, net photosynthetic characteristics, and carbon use efficiency of pandan. Furthermore, intercropping with coconut significantly enhanced the content of volatile compounds, including ketones, alcohols, esters, furanones, pyrroles, acids, and phenols. The increases in soil moisture, improvement in leaf structure, and enhancement of the photosynthetic process under intercropping were the primary drivers of the accumulation of volatile compounds, particularly key quality indicators such as 2-acetyl-1-pyrroline and phytol, in pandan leaves. These findings contribute to the identification of key regulatory factors for enhancing the growth and quality of pandan in intercropping mode.

Dioecious plant species have great agricultural, industrial, and ecological value, though their sexual diamorphism is reflected only at the reproductive stage, making early sex identification a tough job. At early stage (seedling) sex identification in dioecious plants is very important for the breeder, farmer, and economic agricultural productivity. The present review presents a comprehensive methodology of sex determination mechanisms in dioecious plants consisting of cytological, biochemical, morphological, and molecular traits which is an unquestionable requirement required for sexual distinction in dioecious plant species. A special emphasis is focused on molecular marker approaches like Inter-Simple Sequence Repeat (ISSR), Random Amplified Polymorphic DNA (RAPD), Amplified Fragment Length Polymorphism (AFLP), and Sequence Characterized Amplified Region (SCAR) molecular markers, which have potentially enhanced sex determination accuracy and efficiency. These markers have been utilized successfully in a range of dioecious crops such as Pandanus spp., Carica papaya, Cannabis sativa, and Asparagus officinalis. The review also points out the RAPD and ISSR conversion into SCAR for enhancing reproducibility and specificity, along with modern transcriptomic techniques for identifying floral sex-specific genes in economically important plants. Collectively, this review highlights the growing application of molecular marker-based approaches in early and reliable plant sex determination and suggests a future roadmap for high-throughput and genome-assisted strategies in breeding programs.

Sugar cane is one of the most important agricultural commodities globally, serving as a vital source of sugar, bioethanol, and employment for millions of people across more than 100 countries. Rising rainfall due to climate change, evolving environmental regulations, and cost-driven harvesting practices have increased extraneous matter (EM) in sugar cane, reducing factory efficiency and sugar recovery. Despite its significant impact, EM cannot be regularly quantified in sugar factories due to the lack of practical measurement methods and is therefore still excluded from cane payment systems. We introduce near-infrared (NIR) spectroscopy as a rapid, nondestructive solution to this challenge. NIR calibration models for leaf content in shredded cane were developed using mixtures of clean cane, soil, and leaves with known EM concentrations, and soil content calibrations were built using incinerated ash as the reference method. Partial least-squares regression models with k-fold cross-validation were developed to correlate NIR spectra with reference values. Soil content based on ash analysis yielded strong calibration results (R² = 0.88), markedly outperforming sediment analysis (R² = 0.12). For the first time, NIR successfully predicted brown leaves (R² = 0.72), green leaves (R² = 0.73), and total leaves (R² = 0.88). These findings prove the potential of NIR spectroscopy to revolutionize EM analysis, providing a practical pathway for its integration into cane payment systems and improving sugar cane quality assessment.

Curcuma longa L. (turmeric) is a versatile crop of significant culinary and medicinal value. In the present study, 152 accessions were evaluated to assess morphological diversity for two years (2022–2023 and 2023–2024) at the CSIR NEIST experimental farm, Jorhat. All studied traits exhibited significant variation (p ≤ 0.001), indicating substantial genetic variability among the genotypes. The genetic coefficient of variation (GCV) ranged from 3.46 to 63.06, while the phenotypic coefficient of variation (PCV) ranged from 5.08 to 63.15, reflecting a wide spectrum of variability. Most traits plant height (PH), number of tillers/plant (NOT), number of leaves/plant (NOL), leaf length (LL), leaf width (LW), initial rhizome weight (IRW), rhizome yield per plot (RY)) demonstrated moderate to high heritability (33.64–99.74) and high genetic advance as a percentage of the mean (129.75), except for days to maturity. Correlation analysis revealed strong associations among traits where leaf essential oil yield showed the highest positive correlation with curcuminoid content (r = 0.54 and r = 0.53) at the genotypic and phenotypic levels, respectively, and the rhizome yield per plot showed significant and positive correlation with most of the characters (PH, NOT, NOL, LL, LW, IRW), where plant height (r = 0.37) and initial rhizome weight (r = 0.30) were found to have the highest significant correlation both genotypically and phenotypically, respectively. Path coefficient analysis indicated that plant height (1.66) and days to maturity (0.37) had a direct positive effect on rhizome yield, whereas plant height (0.40) had a negative direct effect on curcuminoid content. This suggests the potential for developing dwarf genotypes with a higher curcuminoid concentration. Using Mahalanobis D² statistics, 16 distinct clusters were identified, and principal component analysis (PCA) revealed 10 principal components contributing to the observed variability (69.03%). This is the first comprehensive report incorporating correlation and path analysis for traits such as leaf essential oil yield, curcuminoid content, and rhizome yield per plot together across such a large number of C. longa accessions from Northeast India. These findings provide valuable insights into the genetic diversity, breeding strategies, and conservation efforts for turmeric.

Manganese (Mn) and zinc (Zn) are essential elements for plants. However, deficiencies of these elements are common, reducing crop yields globally. In this context, foliar application of Mn and Zn fertilizers has gained attention due to its precision and efficiency compared to conventional soil fertilization methods. Herein, we aimed to establish an overview of the foliar fertilization with Zn and Mn through a quantitative metadata analysis from 162 peer-reviewed papers published between 2012 and 2023. The study revealed that the most widely employed sources of Zn and Mn were sulfate salts and commercial formulations, respectively. The experimental conditions varied greatly among the studies; most of them were conducted under field conditions. Relative air humidity, an important factor influencing foliar nutrient absorption, was inconsistently reported across the studies. Notably, although crop yield evaluations were scarce, the majority of studies reported positive effects of Mn and Zn foliar applications on plant parameters, underscoring the potential for enhancing agricultural productivity. Further research is warranted to elucidate optimal application strategies and address the limitations in current methodologies.

This study has investigated the effect of the removal of phytochemicals from sugar cane bagasse (after acid/alkali pretreatment) on the yield of enzymatic hydrolysis. Hydrolysis experiments were conducted at preoptimized conditions using a mixture of endoglucanase and β-glucosidase. Two biomasses were used: (1) acid/alkali pretreated sugar cane bagasse (ApSCB) and (2) ApSCB after extraction of phytochemicals using acetonitrile and methanol (ApSCBx). Hydrolysis of ApSCB and ApSCBx yielded 17 and 21.2 g of total reducing sugar (TRS) per 100 g of raw biomass, respectively. Molecular docking simulations were conducted for the complexation of phytochemicals with hydrolyzing enzymes. Many phytochemicals, viz., chlorogenic acid, luteolin, tricin, and diosmetin, have smaller binding energies and inhibition constants for complexation with endoglucanase and β-glucosidase enzymes than their substrates. Molecular dynamics simulations revealed that phytochemicals formed stable complexes with both enzymes, intensifying the inhibitory effects. Molecular simulations indicated a higher susceptibility of β-glucosidase to inhibition by phytochemicals. Removal of phytochemicals through solvent extraction before enzymatic hydrolysis enhanced TRS yield by ∼25%.

Nutrient availability for crops is not limited to the topsoil; deeper layers also serve as significant sources. Rapid determination of soil properties at different depths is essential for the precision management of farming inputs. Most existing studies focus on predicting surface soil properties using spectral data from a single sensor, while research exploring the potential of multisensor spectral fusion for soil analysis at varying depths remains limited. This study evaluated the predictive performance of: (1) single-spectrum modeling using visible and near-infrared (vis–NIR) and mid-infrared (MIR) spectrophotometers and (2) two spectral fusion methods─direct concatenation and outer product analysis of full-spectral absorbance─for five key soil properties: pH, total organic carbon (TOC), available phosphorus (AP), available potassium (AK), and magnesium (Mg), across three soil depths. The data set comprised 176 fresh soil samples collected from 59 locations across five arable cropping fields. Prediction models were developed using partial least-squares regression (PLSR) and support vector machine (SVM), whose performance was assessed using the coefficient of determination (R²), root-mean-square error (RMSE), and ratio of performance to interquartile distance (RPIQ). Results showed that vis–NIR spectra generally outperformed MIR, with validation R² ranging from 0.39 to 0.67 and RPIQ from 0.84 to 3.25, compared to MIR (R² = 0.42–0.62, RPIQ = 0.97–3.08). Notably, spectral fusion using the OPA–SVM method yielded the best predictions for TOC (R² = 0.75, RPIQ = 3.35) and AP (R² = 0.83, RPIQ = 4.72), while the DC-PLSR model achieved the highest performance for pH (R² = 0.65, RPIQ = 2.43). However, fusion was not always superior to single-spectrum models; for example, vis–NIR-SVM and MIR-SVM gave the best results for AK (R² = 0.53, RPIQ = 1.45) and Mg (R² = 0.61, RPIQ = 1.30), respectively. Given these varying results, we recommend selecting spectroscopic techniques based on both predictive performance and practical considerations such as cost-effectiveness and operational feasibility.

The mixture of amino acids and mineral nutrients has already been employed by farmers to improve the efficiency of foliar fertilization, although systematic studies to support the practice are scarce. We deployed an in vivo X-ray fluorescence spectrometry setup to measure the uptake and short-range transport of Mn and Zn complexed with histidine and glutamate. As positive controls, we used stand-alone amino acids and sulfate-based micronutrients. The results showed that under high relative humidity (70–86%), the histidine and glutamate complexes presented transport performance similar to that of sulfates. However, under nonoptimal relative humidity (35–45%), the amino acid complexes presented twice the transport of sulfates. The glutamate complex increased the concentration of Mn in the treated tissue by 670 mg kg^–1; it also induced higher translocation of Mn and Zn to older leaves. The complexes also reduced the phytotoxicity. Thus, the study concludes that such types of biocomplexes offer advantages over standalone salts.

In an attempt to enhance the upcycling potential of industrial fruit juice waste streams, beta-carotene-enriched carotenoid extraction from carrot pomace has been applied. Both enzyme and ultrasound pretreatments improved the extraction efficiency. Among them, enzymatic pretreatment with pectinase was found to be the most effective, which increased total flavonoid content and antioxidant activity by 2-fold while increasing beta-carotene and total phenolic content by 5-fold compared to conventional solvent extraction. The alpha- and beta-carotene contents of the enzyme pretreated extract were found to be 8.6 and 32.5 mg/100 g of dry weight, respectively. All pretreatments improved the antimicrobial activity of the extracts. The minimum bactericidal concentration of the enzyme pretreated extract was recorded as 8 and 16 mg/mL against Escherichia coli and Salmonella typhimurium, respectively, which was 8 and 4 times more effective than the conventionally extracted one, respectively. The carotenoid-rich extracts obtained are promising value-added ingredients for the improvement of the nutritional value, bioactivity, and shelf life of foods.