Extracting patient lifestyle characteristics from Dutch clinical text with BERT models.

BACKGROUND: BERT models have seen widespread use on unstructured text within the clinical domain. However, little to no research has been conducted into classifying unstructured clinical notes on the basis of patient lifestyle indicators, especially in Dutch. This article aims to test the feasibility of deep BERT models on the task of patient lifestyle classification, as well as introducing an experimental framework that is easily reproducible in future research. METHODS: This study makes use of unstructured general patient text data from HagaZiekenhuis, a large hospital in The Netherlands. Over 148 000 notes were provided to us, which were each automatically labelled on the basis of the respective patients' smoking, alcohol usage and drug usage statuses. In this paper we test feasibility of automatically assigning labels, and justify it using hand-labelled input. Ultimately, we compare macro F1-scores of string matching, SGD and several BERT models on the task of classifying smoking, alcohol and drug usage. We test Dutch BERT models and English models with translated input. RESULTS: We find that our further pre-trained MedRoBERTa.nl-HAGA model outperformed every other model on smoking (0.93) and drug usage (0.77). Interestingly, our ClinicalBERT model that was merely fine-tuned on translated text performed best on the alcohol task (0.80). In t-SNE visualisations, we show our MedRoBERTa.nl-HAGA model is the best model to differentiate between classes in the embedding space, explaining its superior classification performance. CONCLUSIONS: We suggest MedRoBERTa.nl-HAGA to be used as a baseline in future research on Dutch free text patient lifestyle classification. We furthermore strongly suggest further exploring the application of translation to input text in non-English clinical BERT research, as we only translated a subset of the full set and yet achieved very promising results.

Intercropping on Mars: A promising system to optimise fresh food production in future martian colonies.

Future colonists on Mars will need to produce fresh food locally to acquire key nutrients lost in food dehydration, the primary technique for sending food to space. In this study we aimed to test the viability and prospect of applying an intercropping system as a method for soil-based food production in Martian colonies. This novel approach to Martian agriculture adds valuable insight into how we can optimise resource use and enhance colony self-sustainability, since Martian colonies will operate under very limited space, energy, and Earth supplies. A likely early Martian agricultural setting was simulated using small pots, a controlled greenhouse environment, and species compliant with space mission requirements. Pea (Pisum sativum), carrot (Daucus carota) and tomato (Solanum lycopersicum) were grown in three soil types ("MMS-1" Mars regolith simulant, potting soil and sand), planted either mixed (intercropping) or separate (monocropping). Rhizobia bacteria (Rhizobium leguminosarum) were added as the pea symbiont for Nitrogen-fixing. Plant performance was measured as above-ground biomass (g), yield (g), harvest index (%), and Nitrogen/Phosphorus/Potassium content in yield (g/kg). The overall intercropping system performance was calculated as total relative yield (RYT). Intercropping had clear effects on plant performance in Mars regolith, being beneficial for tomato but mostly detrimental for pea and carrot, ultimately giving an overall yield disadvantage compared to monocropping (RYT = 0.93). This effect likely resulted from the observed absence of Rhizobia nodulation in Mars regolith, negating Nitrogen-fixation and preventing intercropped plants from leveraging their complementarity. Adverse regolith conditions-high pH, elevated compactness and nutrient deficiencies-presumably restricted Rhizobia survival/nodulation. In sand, where more favourable soil conditions promoted effective nodulation, intercropping significantly outperformed monocropping (RYT = 1.32). Given this, we suggest that with simple regolith improvements, enhancing conditions for nodulation, intercropping shows promise as a method for optimising food production in Martian colonies. Specific regolith ameliorations are proposed for future research.

Roles for leakiness and O2 evolution in explaining lower-than-theoretical quantum yields of photosynthesis in the PEP-CK subtype of C4 plants.

Theoretically, the PEP-CK C4 subtype has a higher quantum yield of CO2 assimilation ( Φ CO 2 ) than NADP-ME or NAD-ME subtypes because ATP required for operating the CO2-concentrating mechanism is believed to mostly come from the mitochondrial electron transport chain (mETC). However, reported Φ CO 2 is not higher in PEP-CK than in the other subtypes. We hypothesise, more photorespiration, associated with higher leakiness and O2 evolution in bundle-sheath (BS) cells, cancels out energetic advantages in PEP-CK species. Nine species (two to four species per subtype) were evaluated by gas exchange, chlorophyll fluorescence, and two-photon microscopy to estimate the BS conductance (gbs) and leakiness using a biochemical model. Average gbs estimates were 2.9, 4.8, and 5.0 mmol m-2 s-1 bar-1, and leakiness values were 0.129, 0.179, and 0.180, in NADP-ME, NAD-ME, and PEP-CK species, respectively. The BS CO2 level was somewhat higher, O2 level was marginally lower, and thus, photorespiratory loss was slightly lower, in NADP-ME than in NAD-ME and PEP-CK species. Differences in these parameters existed among species within a subtype, and gbs was co-determined by biochemical decarboxylating sites and anatomical characteristics. Our hypothesis and results partially explain variations in observed Φ CO 2 , but suggest that PEP-CK species probably use less ATP from mETC than classically defined PEP-CK mechanisms.

Triose phosphate utilization in leaves is modulated by whole-plant sink-source ratios and nitrogen budgets in rice.

Triose phosphate utilization (TPU) is a biochemical process indicating carbon sink-source (im)balance within leaves. When TPU limits leaf photosynthesis, photorespiration-associated amino acid exports probably provide an additional carbon outlet and increase leaf CO2 uptake. However, whether TPU is modulated by whole-plant sink-source relations and nitrogen (N) budgets remains unclear. We address this question by model analyses of gas-exchange data measured on leaves at three growth stages of rice plants grown at two N levels. Sink-source ratio was manipulated by panicle pruning, by using yellower-leaf variant genotypes, and by measuring photosynthesis on adaxial and abaxial leaf sides. Across all these treatments, higher leaf N content resulted in the occurrence of TPU limitation at lower intercellular CO2 concentrations. Photorespiration-associated amino acid export was greater in high-N leaves, but was smaller in yellower-leaf genotypes, panicle-pruned plants, and for abaxial measurement. The feedback inhibition of panicle pruning on rates of TPU was not always observed, presumably because panicle pruning blocked N remobilization from leaves to grains and the increased leaf N content masked feedback inhibition. The leaf-level TPU limitation was thus modulated by whole-plant sink-source relations and N budgets during rice grain filling, suggesting a close link between within-leaf and whole-plant sink limitations.

Neglecting acclimation of photosynthesis under drought can cause significant errors in predicting leaf photosynthesis in wheat.

Extreme climatic events, such as heat waves, cold snaps and drought spells, related to global climate change, have become more frequent and intense in recent years. Acclimation of plant physiological processes to changes in environmental conditions is a key component of plant adaptation to climate change. We assessed the temperature response of leaf photosynthetic parameters in wheat grown under contrasting water regimes and growth temperatures (Tgrowth ). Two independent experiments were conducted under controlled conditions. In Experiment 1, two wheat genotypes were subjected to well-watered or drought-stressed treatments; in Experiment 2, the two water regimes combined with high, medium and low Tgrowth were imposed on one genotype. Parameters of a biochemical C3 -photosynthesis model were estimated at six leaf temperatures for each factor combination. Photosynthesis acclimated more to drought than to Tgrowth . Drought affected photosynthesis by lowering its optimum temperature (Topt ) and the values at Topt of light-saturated net photosynthesis, stomatal conductance, mesophyll conductance, the maximum rate of electron transport (Jmax ) and the maximum rate of carboxylation by Rubisco (Vcmax ). Topt for Vcmax was up to 40°C under well-watered conditions but 24-34°C under drought. The decrease in photosynthesis under drought varied among Tgrowth but was similar between genotypes. The temperature response of photosynthetic quantum yield under drought was partly attributed to photorespiration but more to alternative electron transport. All these changes in biochemical parameters could not be fully explained by the changed leaf nitrogen content. Further model analysis showed that both diffusional and biochemical parameters of photosynthesis and their thermal sensitivity acclimate little to Tgrowth , but acclimate considerably to drought and the combination of drought and Tgrowth . The commonly used modelling approaches, which typically consider the response of diffusional parameters, but ignore acclimation responses of biochemical parameters to drought and Tgrowth , strongly overestimate leaf photosynthesis under variable temperature and drought.

Drought exerts a greater influence than growth temperature on the temperature response of leaf day respiration in wheat (Triticum aestivum).

We assessed how the temperature response of leaf day respiration (Rd ) in wheat responded to contrasting water regimes and growth temperatures. In Experiment 1, well-watered and drought-stressed conditions were imposed on two genotypes; in Experiment 2, the two water regimes combined with high (HT), medium (MT) and low (LT) growth temperatures were imposed on one of the genotypes. Rd was estimated from simultaneous gas exchange and chlorophyll fluorescence measurements at six leaf temperatures (Tleaf ) for each treatment, using the Yin method for nonphotorespiratory conditions and the nonrectangular hyperbolic fitting method for photorespiratory conditions. The two genotypes responded similarly to growth and measurement conditions. Estimates of Rd for nonphotorespiratory conditions were generally higher than those for photorespiratory conditions, but their responses to Tleaf were similar. Under well-watered conditions, Rd and its sensitivity to Tleaf slightly acclimated to LT, but did not acclimate to HT. Temperature sensitivities of Rd were considerably suppressed by drought, and the suppression varied among growth temperatures. Thus, it is necessary to quantify interactions between drought and growth temperature for reliably modelling Rd under climate change. Our study also demonstrated that the Kok method, one of the currently popular methods for estimating Rd , underestimated Rd significantly.

Machine learning algorithms trained with pre-hospital acquired history-taking data can accurately differentiate diagnoses in patients with hip complaints.

Background and purpose - Machine learning (ML) techniques are a form of artificial intelligence able to analyze big data. Analyzing the outcome of (digital) questionnaires, ML might recognize different patterns in answers that might relate to different types of pathology. With this study, we investigated the proof-of-principle of ML-based diagnosis in patients with hip complaints using a digital questionnaire and the Kellgren and Lawrence (KL) osteoarthritis score.Patients and methods - 548 patients (> 55 years old) scheduled for consultation of hip complaints were asked to participate in this study and fill in an online questionnaire. Our questionnaire consists of 27 questions related to general history-taking and validated patient-related outcome measures (Oxford Hip Score and a Numeric Rating Scale for pain). 336 fully completed questionnaires were related to their classified diagnosis (either hip osteoarthritis, bursitis or tendinitis, or other pathology). Different AI techniques were used to relate questionnaire outcome and hip diagnoses. Resulting area under the curve (AUC) and classification accuracy (CA) are reported to identify the best scoring AI model. The accuracy of different ML models was compared using questionnaire outcome with and without radiologic KL scores for degree of osteoarthritis.Results - The most accurate ML model for diagnosis of patients with hip complaints was the Random Forest model (AUC 82%, 95% CI 0.78-0.86; CA 69%, CI 0.64-0.74) and most accurate analysis with addition of KL scores was with a Support Vector Machine model (AUC 89%, CI 0.86-0.92; CA 83%, CI 0.79-0.87).Interpretation - Analysis of self-reported online questionnaires related to hip complaints can differentiate between basic hip pathologies. The addition of radiological scores for osteoarthritis further improves these outcomes.

The Kok effect revisited.

The Kok effect refers to the abrupt decrease around the light compensation point in the slope of net photosynthetic rate vs irradiance. Arguably, this switch arises from light inhibition of respiration, allowing the Kok method to estimate day respiration (Rd ). Recent analysis suggests that increasing proportions of photorespiration (quantified as Γ*/Cc , the ratio of CO2 compensation point Γ* to chloroplast CO2 concentration, Cc ) with irradiance explain much of the Kok effect. Also, the Kok method has been modified to account for the decrease in PSII photochemical efficiency (Φ2 ) with irradiance. Using a model that illustrates how varying Rd , Γ*/Cc , Φ2 and proportions of alternative electron transport could engender the Kok effect, we quantified the contribution of these parameters to the Kok effect measured in sunflower across various O2 and CO2 concentrations and various temperatures. Overall, the decreasing Φ2 with irradiance explained c. 12%, and the varying Γ*/Cc explained c. 25%, of the Kok effect. Maximum real light inhibition of Rd was much lower than the inhibition derived from the Kok method, but still increased with photorespiration. Photorespiration had a dual contribution to the Kok effect, one via the varying Γ*/Cc and the other via its participation in light inhibition of Rd .

Using photorespiratory oxygen response to analyse leaf mesophyll resistance.

Classical approaches to estimate mesophyll conductance ignore differences in resistance components for CO2 from intercellular air spaces (IAS) and CO2 from photorespiration (F) and respiration (Rd). Consequently, mesophyll conductance apparently becomes sensitive to (photo)respiration relative to net photosynthesis, (F + Rd)/A. This sensitivity depends on several hard-to-measure anatomical properties of mesophyll cells. We developed a method to estimate the parameter m (0 ≤ m ≤ 1) that lumps these anatomical properties, using gas exchange and chlorophyll fluorescence measurements where (F + Rd)/A ratios vary. This method was applied to tomato and rice leaves measured at five O2 levels. The estimated m was 0.3 for tomato but 0.0 for rice, suggesting that classical approaches implying m = 0 work well for rice. The mesophyll conductance taking the m factor into account still responded to irradiance, CO2, and O2 levels, similar to response patterns of stomatal conductance to these variables. Largely due to different m values, the fraction of (photo)respired CO2 being refixed within mesophyll cells was lower in tomato than in rice. But that was compensated for by the higher fraction via IAS, making the total re-fixation similar for both species. These results, agreeing with CO2 compensation point estimates, support our method of effectively analysing mesophyll resistance.

Intercropping with wheat lowers nutrient uptake and biomass accumulation of maize, but increases photosynthetic rate of the ear leaf.

Intercropping is an ancient agricultural practice that provides a possible pathway for sustainable increases in crop yields. Here, we determine how competition with wheat affects nutrient uptake (nitrogen and phosphorus) and leaf traits, such as photosynthetic rate, in maize. In a field experiment, maize was planted as a sole crop, in three different intercrop configurations with wheat (a replacement intercrop and two add-row intercrops), and as a skip-row system with one out of each three maize rows omitted. Nitrogen and phosphorus uptake were determined at flowering and maturity. Specific leaf area, leaf nitrogen concentration, chlorophyll content and photosynthetic rate of the ear leaf were determined at flowering. Nitrogen and phosphorus concentrations were significantly lower in intercropped maize than in sole maize and skip-row maize at flowering, but these differences were smaller at maturity. At flowering, specific leaf area was significantly greater in intercrops than in skip-row maize. Leaf nitrogen concentration was significantly lower in add-row intercrops than in sole maize, skip-row maize or maize in the replacement intercrop. Leaf chlorophyll content was highest in sole and skip-row maize, intermediate in maize in the replacement intercrop and lowest in maize grown in add-row intercrops. On the contrary, photosynthetic rate was significantly higher in the replacement intercrop than in sole maize, skip-row maize and the intercrop with an additional maize row. The findings indicate that competition with intercropped wheat severely constrained nutrient uptake in maize, while photosynthetic rate of the ear leaf was not negatively affected. Possible mechanisms for higher photosynthesis rate at lower leaf nitrogen content in intercropped maize are discussed.

Calibration matters: On the procedure of using the chlorophyll fluorescence method to estimate mesophyll conductance.

Estimates of mesophyll conductance (gm), when calculated from chlorophyll fluorescence, are uncertain, especially when the photosystem II (PSII) operating efficiency is measured from the traditional single saturation pulse methodology. The multiphase flash method has recently been recommended to replace the single saturation pulse method, allowing a more reliable estimation of gm. Also, many researchers still directly use the PSII operating efficiency to derive linear electron transport rate J (that is required to estimate gm), without appropriate calibration using measurements under non-photorespiratory conditions. Here we demonstrate for tomato and rice that (i) using the multiphase flash method did not yield realistic estimates of gm if no calibration was conducted; and (ii) using the single saturation pulse method still gave reasonable estimates of gm when calibration based on the non-photorespiratory measurements was properly conducted. Therefore, conducting calibration based on data under non-photorespiratory conditions was indispensable for a reliable estimation of gm, regardless whether the multiphase flash or the single saturation pulse method was used for measuring the PSII operating efficiency. Other issues related to the procedure of using the chlorophyll fluorescence method to estimate gm were discussed.

Impact of anatomical traits of maize (Zea mays L.) leaf as affected by nitrogen supply and leaf age on bundle sheath conductance.

The mechanism of photosynthesis in C4 crops depends on the archetypal Kranz-anatomy. To examine how the leaf anatomy, as altered by nitrogen supply and leaf age, affects the bundle sheath conductance (gbs), maize (Zea mays L.) plants were grown under three contrasting nitrogen levels. Combined gas exchange and chlorophyll fluorescence measurements were done on fully grown leaves at two leaf ages. The measured data were analysed using a biochemical model of C4 photosynthesis to estimate gbs. The leaf microstructure and ultrastructure were quantified using images obtained from micro-computed tomography and microscopy. There was a strong positive correlation between gbs and leaf nitrogen content (LNC) while old leaves had lower gbs than young leaves. Leaf thickness, bundle sheath cell wall thickness and surface area of bundle sheath cells per unit leaf area (Sb) correlated well with gbs although they were not significantly affected by LNC. As a result, the increase of gbs with LNC was little explained by the alteration of leaf anatomy. In contrast, the combined effect of LNC and leaf age on Sb was responsible for differences in gbs between young leaves and old leaves. Future investigations should consider changes at the level of plasmodesmata and membranes along the CO2 leakage pathway to unravel LNC and age effects further.

Temperature response of bundle-sheath conductance in maize leaves.

A small bundle-sheath conductance (g bs) is essential for the C4 CO2-concentrating mechanism to suppress photorespiration effectively. To predict the productivity of C4 crops accurately under global warming, it is necessary to examine whether and how g bs responds to temperature. We investigated the temperature response of g bs in maize by fitting a C4 photosynthesis model to combined gas exchange and chlorophyll fluorescence measurements of irradiance and CO2 response curves at 21% and 2% O2 within the range of 13.5-39 °C. The analysis was based on reported kinetic constants of C4 Rubisco and phosphoenolpyruvate carboxylase and temperature responses of C3 mesophyll conductance (g m). The estimates of g bs varied greatly with leaf temperature. The temperature response of g bs was well described by the peaked Arrhenius equation, with the optimum temperature being ~34 °C. The assumed temperature responses of g m had only a slight impact on the temperature response of g bs In contrast, using extreme values of some enzyme kinetic constants changed the shape of the response, from the peaked optimum response to the non-peaked Arrhenius pattern. Further studies are needed to confirm such an Arrhenius response pattern from independent measurement techniques and to assess whether it is common across C4 species.

Modelling the relationship between CO2 assimilation and leaf anatomical properties in tomato leaves.

The CO2 concentration near Rubisco and, therefore, the rate of CO2 assimilation, is influenced by both leaf anatomical factors and biochemical processes. Leaf anatomical structures act as physical barriers for CO2 transport. Biochemical processes add or remove CO2 along its diffusion pathway through mesophyll. We combined a model that quantifies the diffusive resistance for CO2 using anatomical properties, a model that partitions this resistance and an extended version of the Farquhar-von Caemmerer-Berry model. We parametrized the model by gas exchange, chlorophyll fluorescence and leaf anatomical measurements from three tomato cultivars. There was generally a good agreement between the predicted and measured light and CO2 response curves. We did a sensitivity analysis to assess how the rate of CO2 assimilation responds to changes in various leaf anatomical properties. Next, we conducted a similar analysis for assumed diffusive properties and curvature factors. Some variables (diffusion pathway length in stroma, diffusion coefficient of the stroma, curvature factors) substantially affected the predicted CO2 assimilation. We recommend more research on the measurements of these variables and on the development of 2-D and 3-D gas diffusion models, since these do not require the diffusion pathway length in the stroma as predefined parameter.

Accounting for the decrease of photosystem photochemical efficiency with increasing irradiance to estimate quantum yield of leaf photosynthesis.

Maximum quantum yield for leaf CO2 assimilation under limiting light conditions (Φ CO2LL) is commonly estimated as the slope of the linear regression of net photosynthetic rate against absorbed irradiance over a range of low-irradiance conditions. Methodological errors associated with this estimation have often been attributed either to light absorptance by non-photosynthetic pigments or to some data points being beyond the linear range of the irradiance response, both causing an underestimation of Φ CO2LL. We demonstrate here that a decrease in photosystem (PS) photochemical efficiency with increasing irradiance, even at very low levels, is another source of error that causes a systematic underestimation of Φ CO2LL. A model method accounting for this error was developed, and was used to estimate Φ CO2LL from simultaneous measurements of gas exchange and chlorophyll fluorescence on leaves using various combinations of species, CO2, O2, or leaf temperature levels. The conventional linear regression method under-estimated Φ CO2LL by ca. 10-15%. Differences in the estimated Φ CO2LL among measurement conditions were generally accounted for by different levels of photorespiration as described by the Farquhar-von Caemmerer-Berry model. However, our data revealed that the temperature dependence of PSII photochemical efficiency under low light was an additional factor that should be accounted for in the model.

Zinc allocation and re-allocation in rice.

AIMS: Agronomy and breeding actively search for options to enhance cereal grain Zn density. Quantifying internal (re-)allocation of Zn as affected by soil and crop management or genotype is crucial. We present experiments supporting the development of a conceptual model of whole plant Zn allocation and re-allocation in rice. METHODS: Two solution culture experiments using (70)Zn applications at different times during crop development and an experiment on within-grain distribution of Zn are reported. In addition, results from two earlier published experiments are re-analyzed and re-interpreted. RESULTS: A budget analysis showed that plant zinc accumulation during grain filling was larger than zinc allocation to the grains. Isotope data showed that zinc taken up during grain filling was only partly transported directly to the grains and partly allocated to the leaves. Zinc taken up during grain filling and allocated to the leaves replaced zinc re-allocated from leaves to grains. Within the grains, no major transport barrier was observed between vascular tissue and endosperm. At low tissue Zn concentrations, rice plants maintained concentrations of about 20 mg Zn kg(-1) dry matter in leaf blades and reproductive tissues, but let Zn concentrations in stems, sheath, and roots drop below this level. When plant zinc concentrations increased, Zn levels in leaf blades and reproductive tissues only showed a moderate increase while Zn levels in stems, roots, and sheaths increased much more and in that order. CONCLUSIONS: In rice, the major barrier to enhanced zinc allocation towards grains is between stem and reproductive tissues. Enhancing root to shoot transfer will not contribute proportionally to grain zinc enhancement.

Early competition shapes maize whole-plant development in mixed stands.

Mixed cropping is practised widely in developing countries and is gaining increasing interest for sustainable agriculture in developed countries. Plants in intercrops grow differently from plants in single crops, due to interspecific plant interactions, but adaptive plant morphological responses to competition in mixed stands have not been studied in detail. Here the maize (Zea mays) response to mixed cultivation with wheat (Triticum aestivum) is described. Evidence is provided that early responses of maize to the modified light environment in mixed stands propagate throughout maize development, resulting in different phenotypes compared with pure stands. Photosynthetically active radiation (PAR), red:far-red ratio (R:FR), leaf development, and final organ sizes of maize grown in three cultivation systems were compared: pure maize, an intercrop with a small distance (25cm) between maize and wheat plants, and an intercop with a large distance (44cm) between the maize and the wheat. Compared with maize in pure stands, maize in the mixed stands had lower leaf and collar appearance rates, increased blade and sheath lengths at low ranks and smaller sizes at high ranks, increased blade elongation duration, and decreased R:FR and PAR at the plant base during early development. Effects were strongest in the treatment with a short distance between wheat and maize strips. The data suggest a feedback between leaf initiation and leaf emergence at the plant level and coordination between blade and sheath growth at the phytomer level. A conceptual model, based on coordination rules, is proposed to explain the development of the maize plant in pure and mixed stands.

Using a biochemical C4 photosynthesis model and combined gas exchange and chlorophyll fluorescence measurements to estimate bundle-sheath conductance of maize leaves differing in age and nitrogen content.

Bundle-sheath conductance (g(bs) ) affects CO(2) leakiness, and, therefore, the efficiency of the CO(2) -concentrating mechanism (CCM) in C(4) photosynthesis. Whether and how g(bs) varies with leaf age and nitrogen status is virtually unknown. We used a C(4) -photosynthesis model to estimate g(bs) , based on combined measurements of gas exchange and chlorophyll fluorescence on fully expanded leaves of three different ages of maize (Zea mays L.) plants grown under two contrasting nitrogen levels. Nitrogen was replenished weekly to maintain leaf nitrogen content (LNC) at a similar level across the three leaf ages. The estimated g(bs) values on leaf-area basis ranged from 1.4 to 10.3 mmol m(-2) s(-1) and were affected more by LNC than by leaf age, although g(bs) tended to decrease as leaves became older. When converted to resistance (r(bs) = 1/g(bs)), r(bs) decreased monotonically with LNC. The correlation was presumably associated with nitrogen effects on leaf anatomy such as on wall thickness of bundle-sheath cells. Despite higher g(bs), meaning less efficient CCM, the calculated loss due to photorespiration was still low for high-nitrogen leaves. Under the condition of ambient CO(2) and saturating irradiance, photorespiratory loss accounted for 3-5% of fixed carbon for the high-nitrogen, versus 1-2% for the low-nitrogen, leaves.

Using combined measurements of gas exchange and chlorophyll fluorescence to estimate parameters of a biochemical C photosynthesis model: a critical appraisal and a new integrated approach applied to leaves in a wheat (Triticum aestivum) canopy.

We appraised the literature and described an approach to estimate the parameters of the Farquhar, von Caemmerer and Berry model using measured CO(2) assimilation rate (A) and photosystem II (PSII) electron transport efficiency (Phi(2)). The approach uses curve fitting to data of A and Phi(2) at various levels of incident irradiance (I(inc)), intercellular CO(2) (C(i)) and O(2). Estimated parameters include day respiration (R(d)), conversion efficiency of I(inc) into linear electron transport of PSII under limiting light [kappa(2(LL))], electron transport capacity (J(max)), curvature factor (theta) for the non-rectangular hyperbolic response of electron flux to I(inc), ribulose 1.5-bisphosphate carboxylase/oxygenase (Rubisco) CO(2)/O(2) specificity (S(c/o)), Rubisco carboxylation capacity (V(cmax)), rate of triose phosphate utilization (T(p)) and mesophyll conductance (g(m)). The method is used to analyse combined gas exchange and chlorophyll fluorescence measurements on leaves of various ages and positions in wheat plants grown at two nitrogen levels. Estimated S(c/o) (25 degrees C) was 3.13 mbar microbar(-1); R(d) was lower than respiration in the dark; J(max) was lower and theta was higher at 2% than at 21% O(2); kappa(2(LL)), V(cmax), J(max) and T(p) correlated to leaf nitrogen content; and g(m) decreased with increasing C(i) and with decreasing I(inc). Based on the parameter estimates, we surmised that there was some alternative electron transport.