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Having a short postharvest life, cucumber undergoes rapid loss of quality. In this research, the effects of temperature, oxygen, and postharvest storage time on the respiration rate of Royal cucumbers were investigated. To design a Modified Atmosphere Packaging (MAP) for cucumber in order to extend its shelf-life, a mathematical model using Michaelis-Menten's equation, with the model constants described by means of an Arrhenius-type relationship, was applied to predict respiration rate at various temperatures (4, 10, and 20°C) and O2 concentrations. Results revealed that all three factors affected respiration rate of the cucumbers, but the influence of temperature was most pronounced. The model was validated in a commercial passive and active MAP. The model could well predict the O2 change in the package but the modeling of CO2 change, mainly at 20°C, was not satisfactory, which might be due to occurrence of anaerobic condition. The mathematical model was verified as long as the O2 concentration did not reach anaerobic levels at 20°C. Applying the corresponding respiration, the model will also be applicable for other variety of cucumbers with similar metabolic and respiratory behavior to design the optimal MAP conditions. [ABSTRACT FROM AUTHOR]

Tomato is an important commercial product which is perishable by nature and highly susceptible to fungal incidence once it is harvested. Not all tomatoes are equally vulnerable to pathogenic fungi, and an early detection of the vulnerable ones can help in taking timely preventive actions, ranging from isolating tomato batches to adjusting storage conditions, but also in making right business decisions like dynamic pricing based on quality or better shelf life estimate. More importantly, early detection of vulnerable produce can help in taking timely actions to minimize potential post-harvest losses. This paper investigates Near-infrared (NIR) hyperspectral imaging (1000-1700 nm) and machine learning to build models to automatically predict the susceptibility of sepals of recently harvested tomatoes to future fungal infections. Hyperspectral images of newly harvested tomatoes (cultivar Brioso) from 5 different growers were acquired before the onset of any visible fungal infection. After imaging, the tomatoes were placed under controlled conditions suited for fungal germination and growth for a 4-day period, and then imaged using normal color cameras. All sepals in the color images were ranked for fungal severity using crowdsourcing, and the final severity of each sepal was fused using principal component analysis. A novel hyperspectral data processing pipeline is presented which was used to automatically segment the tomato sepals from spectral images with multiple tomatoes connected via a truss. The key modelling question addressed in this research is whether there is a correlation between the hyperspectral data captured at harvest and the fungal infection observed 4 days later. Using 10-fold and group k-fold cross-validation, XG-Boost and Random Forest based regression models were trained on the features derived from the hyperspectral data corresponding to each sepal in the training set and tested on hold out test set. The best model found a Pearson correlation of 0.837, showing that there is strong linear correlation between the NIR spectra and the future fungal severity of the sepal. The sepal specific predictions were aggregated to predict the susceptibility of individual tomatoes, and a correlation of 0.92 was found. Besides modelling, focus is also on model interpretation, particularly to understand which spectral features are most relevant to model prediction. Two approaches to model interpretation were explored, feature importance and SHAP (SHapley Additive exPlanations), resulting in similar conclusions that the NIR range between 1390-1420 nm contributes most to the model's final decision., (© 2021. The Author(s).)

Near-infrared (NIR) spectroscopy models for fresh fruit quality prediction often fail when used on a new batch or scenario having new variability which was absent in the primary calibration. To handle the new variability often model updating is required. In this study, to solve the challenge of updating NIR models related to fresh fruit quality properties, the use of a semi-supervised parameter-free calibration enhancement (PFCE) approach was proposed. Model updating with PFCE was shown in two ways: first where the model on the primary batch was updated individually for each new fruit batch, and second where the model was sequentially updated for the next batches. Furthermore, for the first time, a case of updating an instrument transferred model was also presented. The PFCE approach was shown in two real cases related to moisture and total soluble solids prediction in pear and kiwi fruit. In the case of pear, the model was later updated for 3 new measurement batches, while, for kiwi, a commercial model was updated to incorporate the variability of a new experiment carried out with a new instrument in the laboratory environment. For each modelling demonstration, the performance was benchmarked with the partial least-square (PLS) regression analysis on the primary batch. The results showed that the models updated with a semi-supervised approach kept a high predictive performance on new measurement batches, without any extra parameter optimization. An instrument transferred model was also updated to maintain its performance on different batches. Further, the sequential updating approach was found to be performing better than the update for individual batches, as the models were able to learn from multiple batches. Model updating with a semi-supervised approach can allow the NIR spectroscopy of fresh fruit to be scalable, where models can be shared between scientific or application community., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 The Author(s). Published by Elsevier B.V. All rights reserved.)

Herein we describe the discovery, mode of action, and preclinical characterization of the soluble guanylate cyclase (sGC) activator runcaciguat. The sGC enzyme, via the formation of cyclic guanosine monophoshphate, is a key regulator of body and tissue homeostasis. sGC activators with their unique mode of action are activating the oxidized and heme-free and therefore NO-unresponsive form of sGC, which is formed under oxidative stress. The first generation of sGC activators like cinaciguat or ataciguat exhibited limitations and were discontinued. We overcame limitations of first-generation sGC activators and identified a new chemical class via high-throughput screening. The investigation of the structure-activity relationship allowed to improve potency and multiple solubility, permeability, metabolism, and drug-drug interactions parameters. This program resulted in the discovery of the oral sGC activator runcaciguat (compound 45 , BAY 1101042). Runcaciguat is currently investigated in clinical phase 2 studies for the treatment of patients with chronic kidney disease and nonproliferative diabetic retinopathy.

Light emitting diodes (LEDs) now enable precise light quality control. Prior to commercialisation however, the plant response to the resultant light quality regime ought to be addressed. The response was examined here in chrysanthemum by evaluating growth, chlorophyll fluorescence (before and following water deficit), as well as stomatal anatomy (density, size, pore dimensions and aperture heterogeneity) and closing ability. Plants were grown under blue (B), red (R), a mixture of R (70%) and B (RB), or white (W; 41% B, 39% intermediate spectrum, 20% R) light LEDs. Although R light promoted growth, it also caused leaf deformation (epinasty) and disturbed the photosynthetic electron transport system. The largest stomatal size was noted following growth under B light, whereas the smallest under R light. The largest stomatal density was observed under W light. Monochromatic R light stimulated both the rate and the degree of stomatal closure in response to desiccation compared with the other light regimes. We conclude that stomatal size is mainly controlled by the B spectrum, whereas a broader spectral range is important for determining stomatal density. Monochromatic R light enhanced stomatal ability to regulate water loss upon desiccation.

Near infrared (NIR) spectroscopy allows rapid estimation of quality traits in fresh fruit. Several portable spectrometers are available in the market as a low-cost solution to perform NIR spectroscopy. However, portable spectrometers, being lower in cost than a benchtop counterpart, do not cover the complete near infrared (NIR) spectral range. Often portable sensors either use silicon-based visible and NIR detector to cover 400-1000 nm, or InGaAs-based short wave infrared (SWIR) detector covering the 900-1700 nm. However, these two spectral regions carry complementary information, since the 400-1000 nm interval captures the color and 3rd overtones of most functional group vibrations, while the 1st and the 2nd overtones of the same transitions fall in the 1000-1700 nm range. To exploit such complementarity, sequential data fusion strategies were used to fuse the data from two portable spectrometers, i.e., Felix F750 (~400-1000 nm) and the DLP NIR Scan Nano (~900-1700 nm). In particular, two different sequential fusion approaches were used, namely sequential orthogonalized partial-least squares (SO-PLS) regression and sequential orthogonalized covariate selection (SO-CovSel). SO-PLS improved the prediction of moisture content (MC) and soluble solids content (SSC) in pear fruit, leading to an accuracy which was not obtainable with models built on any of the two spectral data set individually. Instead, SO-CovSel was used to select the key wavelengths from both the spectral ranges mostly correlated to quality parameters of pear fruit. Sequential fusion of the data from the two portable spectrometers led to an improved model prediction (higher R 2 and lower RMSEP) of MC and SSC in pear fruit: compared to the models built with the DLP NIR Scan Nano (the worst individual block) where SO-PLS showed an increase in R 2 p up to 56% and a corresponding 47% decrease in RMSEP. Differences were less pronounced to the use of Felix data alone, but still the R 2 p was increased by 2.5% and the RMSEP was reduced by 6.5%. Sequential data fusion is not limited to NIR data but it can be considered as a general tool for integrating information from multiple sensors., (Copyright © 2020 The Author(s). Published by Elsevier B.V. All rights reserved.)

The effect of the lighting environment during postharvest storage of ornamentals has largely been neglected in previous research. Anthurium is a cold-sensitive species originating from tropical climates and is widely cultivated all around the world for its colorful spathes. To investigate the effects of light spectrum on the performance of Anthurium cut flowers under cold storage, two cultivars [Calore (red spathe) and Angel (withe spathe)] were placed at low temperature (4°C), either in darkness (D) or under different light spectra [red (R), blue (B), 70:30% red:blue (RB), and white (W)] at an intensity of 125 µmol.m -2 .s -1 . In both cultivars, the longest and shortest vase lives were observed in spathes exposed to the R and B spectra, respectively. In both cultivars, electrolyte leakage (EL) of spathe was highest under the B and W spectra and lowest under the R spectrum. The highest rate of flower water loss from the spathes was observed under the B-containing light spectra, whereas the lowest rate of water loss was observed in D and under the R spectrum. Negative correlations were observed between EL and vase life and between anthocyanin concentration and EL for both Anthurium cultivars. A positive correlation was found between anthocyanin concentration and vase life. For both Anthurium cultivars, spectral light composition with higher percentage of B resulted in higher EL and as a result shorter vase life in cut flowers under cold storage condition. The negative effect of the B light spectrum on vase life of Anthurium can be explained through its effect on water loss and on oxidative stress and membrane integrity. The quality of Anthurium cut flowers should benefit from environments with restricted B light spectrum during postharvest handling., (Copyright © 2020 Aliniaeifard, Falahi, Dianati Daylami, Li and Woltering.)

Improving marketability and extension of vase life of cut flowers has practical significance for the development of the cut flower industry. Although considerable efforts have been made over many years to improve the vase life of cut flowers through controlling the immediate environment and through post-harvest use of floral preservatives, the impact of lighting environment on vase life has been largely overlooked. In the current study, the effect of three LED light spectra [white (400-730 nm), blue (peak at 460 nm), and red (peak at 660 nm)] at 150 μmol m -2 s -1 on vase life and on physiological and biochemical characteristics of carnation cut flowers was investigated. Exposure to blue light (BL) considerably delayed senescence and improved vase life over that of flowers exposed to red light (RL) and white light (WL). H 2 O 2 and malondialdehyde (MDA) contents in petals gradually increased during vase life; the increase was lowest in BL-exposed flowers. As a consequence, BL-exposed flowers maintained a higher membrane stability index (MSI) compared to RL- and WL-exposed flowers. A higher activity of antioxidant enzymes [superoxide dismutase (SOD), peroxidase (POD), catalase (CAT), and ascorbate peroxidase (APX)] was detected in petals of BL-exposed flowers, compared to their activities in RL- and WL-exposed flowers. In BL-exposed flowers, the decline in petal carotenoid contents was delayed in comparison to RL- and WL-exposed flowers. Maximum quantum efficiency of photosystem II (Fv/Fm) and a higher percentage of open stomata were observed in leaves of BL-exposed flowers. Sucrose and glucose contents accumulated in petals during vase life; sugar concentrations were higher in BL-exposed flowers than in RL- and WL-exposed flowers. It is concluded that BL exposure improves the vase life of carnation cut flowers through its effect on the antioxidant defense system in petals and on photosynthetic performance in the leaves., (Copyright © 2020 Aalifar, Aliniaeifard, Arab, Zare Mehrjerdi, Dianati Daylami, Serek, Woltering and Li.)

L-ascorbate (ASC) is essential for human health. Therefore, there is interest in increasing the ASC content of crops like tomato. High irradiance induces accumulation of ASC in green tomato fruits. The D-mannose/L-galactose biosynthetic pathway accounts for the most ASC in plants. The myo-inositol and galacturonate pathways have been proposed to exist but never identified in plants. The D-mannose/L-galactose starts from D-glucose. In a series of experiments, we tested the hypothesis that ASC levels depend on soluble carbohydrate content when tomato fruits ripen under irradiances that stimulate ASC biosynthesis. We show that ASC levels considerably increased when fruits ripened under light, but carbohydrate levels did not show a parallel increase. When carbohydrate levels in fruits were altered by flower pruning, no effects on ASC levels were observed at harvest or after ripening under irradiances that induce ASC accumulation. Artificial feeding of trusses with sucrose increased carbohydrate levels, but did not affect the light-induced ASC levels. We conclude that light-induced accumulation of ASC is independent of the carbohydrate content in tomato fruits. In tomato fruit treated with light, the increase in ASC was preceded by a concomitant increase in myo-inositol.

Background: Midgut neuroendocrine tumors (NETs) are rare malignancies with indolent clinical courses. In general, they are well-differentiated with most tumor cells in the G0 phase of the cell cycle, consistent with the poor response rate of NETs to chemotherapy in vivo. We hypothesize that insults, such as surgery, can drive NET cells from G0 into S phase and that biomarker analysis of individual patient tumors harvested and grown in the lab will provide useful practical guide for future intra and post-operative adjuvant therapy., Methods: 97 well-differentiated midgut NET patients underwent cytoreductive surgery at our institution between May/2012 and October/2012. 148 surgical specimens were collected and submitted to a single commercial lab for processing. Primary tumors, lymph nodes and liver metastases were harvested and cultured. Their ribonucleic acids (RNA) were then extracted to analyze the expressivity, a total of 88 different biomarkers. Based on our patients' specific tumor biomarker expressivity and known correlations between 36 anti-neoplastic agents with their linked biomarkers, recommendations were reported as clinically beneficial or non-beneficial., Results: A total of 148 specimens from 97 patients were tested. In four of the 97 patients, no clinically beneficial chemotherapy agent could be identified. Among the remaining 93 patients, the top three agents that are most likely to be clinically beneficial are: fluorouracil, cisplatin and carboplatin. These were reported to be clinically beneficial in 135/148 (91.2%), 103/148 (69.6%), and 103/148 (69.6%) patients respectively., Conclusions: Midgut NETs are slow growing tumors which are chemotherapeutically inert owing to the fact that most of the tumor cells are in G0 cell cycle. Surgical insult drives NET cells into active synthetic phase where they begin to express biomarkers specific to their tumor cells. Analysis of these biomarkers guides further potential beneficial therapy based on the current known associations among biomarkers and chemotherapy agents. These results must then be compared and confirmed against a direct in-vitro chemo sensitivity assessment conducted simultaneously on the same patients.

Background: We previously reported that midgut neuroendocrine tumors (NETs) often develop alternative lymphatic drainage owing to lymphatic obstructions from extensive mesenteric lymphadenopathy, making intraoperative lymphatic mapping mandatory. We hypothesize that this innovative approach needs a longer term validation., Methods: We updated our results by reviewing 303 patients who underwent cytoreduction from November 2006 to October 2011. Of these patients, 112 had lymphatic mappings and 98 were for midgut NET primaries. Among them, 77 mappings were for the initial cytoreduction and 35 were for reexploration and further cytoreduction. The operative findings, pathology reports, and long-term surgical outcomes were reviewed., Results: Lymphatic mapping changed traditional resection margins in 92% of patients. Of the 35 patients who underwent reexploration without initial mapping, 19 (54%) showed a recurrence at or near the anastomotic sites. In contrast, none of the 112 mapped patients had shown signs of recurrence in a 1- to 5-year follow-up. Additionally, 20 of 45 ileocecal valves (44.4%) were spared in patients whose tumors were at the terminal ileum that, traditionally, would call for a right hemicolectomy., Conclusion: With a longer follow-up, lymphatic mapping has proven to be a safe and effective way to prevent local recurrences and preserve the ileocecal valve for selected patients., (Copyright © 2014 Elsevier Inc. All rights reserved.)