A single-probe heat pulse method for estimating sap velocity in trees.

Available sap flow methods are still far from being simple, cheap and reliable enough to be used beyond very specific research purposes. This study presents and tests a new single-probe heat pulse (SPHP) method for monitoring sap velocity in trees using a single-probe sensor, rather than the multi-probe arrangements used up to now. Based on the fundamental conduction-convection principles of heat transport in sapwood, convective velocity (Vh ) is estimated from the temperature increase in the heater after the application of a heat pulse (ΔT). The method was validated against measurements performed with the compensation heat pulse (CHP) technique in field trees of six different species. To do so, a dedicated three-probe sensor capable of simultaneously applying both methods was produced and used. Experimental measurements in the six species showed an excellent agreement between SPHP and CHP outputs for moderate to high flow rates, confirming the applicability of the method. In relation to other sap flow methods, SPHP presents several significant advantages: it requires low power inputs, it uses technically simpler and potentially cheaper instrumentation, the physical damage to the tree is minimal and artefacts caused by incorrect probe spacing and alignment are removed.

Using machine learning for crop yield prediction in the past or the future.

The use of ML in agronomy has been increasing exponentially since the start of the century, including data-driven predictions of crop yields from farm-level information on soil, climate and management. However, little is known about the effect of data partitioning schemes on the actual performance of the models, in special when they are built for yield forecast. In this study, we explore the effect of the choice of predictive algorithm, amount of data, and data partitioning strategies on predictive performance, using synthetic datasets from biophysical crop models. We simulated sunflower and wheat data using OilcropSun and Ceres-Wheat from DSSAT for the period 2001-2020 in 5 areas of Spain. Simulations were performed in farms differing in soil depth and management. The data set of farm simulated yields was analyzed with different algorithms (regularized linear models, random forest, artificial neural networks) as a function of seasonal weather, management, and soil. The analysis was performed with Keras for neural networks and R packages for all other algorithms. Data partitioning for training and testing was performed with ordered data (i.e., older data for training, newest data for testing) in order to compare the different algorithms in their ability to predict yields in the future by extrapolating from past data. The Random Forest algorithm had a better performance (Root Mean Square Error 35-38%) than artificial neural networks (37-141%) and regularized linear models (64-65%) and was easier to execute. However, even the best models showed a limited advantage over the predictions of a sensible baseline (average yield of the farm in the training set) which showed RMSE of 42%. Errors in seasonal weather forecasting were not taken into account, so real-world performance is expected to be even closer to the baseline. Application of AI algorithms for yield prediction should always include a comparison with the best guess to evaluate if the additional cost of data required for the model compensates for the increase in predictive power. Random partitioning of data for training and validation should be avoided in models for yield forecasting. Crop models validated for the region and cultivars of interest may be used before actual data collection to establish the potential advantage as illustrated in this study.

Is olive crop modelling ready to assess the impacts of global change?

Olive trees, alongside grapevines, dominate the Mediterranean tree crop landscape. However, as climate change intensifies, the Mediterranean region, which encompasses 95% of the global olive cultivation area, faces significant challenges. Rising carbon dioxide (CO2) levels, increasing temperatures, and declining precipitation pose substantial threats to olive tree performance. Photosynthesis, respiration, phenology, water use and ultimately yield are possibly the main factors affected. To address this future scenario, it is crucial to develop adaptation and mitigation strategies. Nevertheless, breeding programs and field management practice testing for tree crops are time-consuming endeavors. Fortunately, models can accelerate the evaluation of tailored solutions. In this review, we critically examine the current state of olive tree modeling and highlight key areas requiring improvement. Given the expected impact of climate change, prioritizing research on phenology, particularly regarding bloom and pollination, is essential. Simulations of biomass should incorporate approaches that account for the interactive effects of CO2 and temperature on photosynthesis and respiration. Furthermore, accurately simulating the influence of water stress on yield necessitates the development of models that integrate canopy behavior with root performance under conditions of water scarcity. By addressing these critical aspects, olive tree models can enhance our understanding of climate change impacts and inform sustainable agricultural practices.

The lipopolysaccharide biosynthesis core of the Mexican pathogenic strain Serratia entomophila is associated with toxicity to larvae of Phyllophaga blanchardi.

The Mexican bacteria Serratia entomophila strain Mor4.1 (Enterobacteriaceae) is pathogenic to coleopteran species of the Phyllophaga genus, which are considered important soil-dwelling pests. Mor4.1 causes anti-feeding activity and mortality to larvae after oral and injection bio-assay either, by bacteria or by cell free culture broth inoculation. The pathogenic determinants of Mor4.1 have not been elucidated. We hypothesize that Mor4.1 produces several toxins and other virulence factors, some acting at the level of the insect gut and others at the hemocoel. To identify and characterize virulence factors, a fosmid library of S. entomophila Mor4.1 was made in Escherichia coli. Five different insecticidal clones were isolated by injecting individual clones into Phyllophaga blanchardi larvae. The complete 40 kb DNA sequence and gene organization of clone G8 was determined. By comparative genomics, 21 genes were associated with virulence. By transposon (Tn5) insertion mutagenesis of G8 and further bio-assays we show that a dUTPase, a flavoprotein and a heptosyltransferase III, are key factors for G8 toxic activity. The heptosyltransferase III, is part of the lipopolysaccharide (LPS) biosynthesis core. We demonstrated that purified LPS from G8 and Mor4.1 are toxic to P. blanchardi larvae by injection bio-assay.

Spatial sap flow and xylem anatomical characteristics in olive trees under different irrigation regimes.

The compensation heat pulse (CHP) method is widely used to estimate sap flow and transpiration in conducting organs of woody plants. Previous studies have reported a natural azimuthal variability in sap flow, which could have practical implications in locating the CHP probes and integrating their output. Sap flow of several olive trees (Olea europaea L. cv. 'Arbequina') previously grown under different irrigation treatments were monitored by the CHP method, and their xylem anatomical characteristics were analyzed from wood samples taken at the same location in which the probes were installed. A significant azimuthal variability in the sap flow was found in a well-irrigated olive tree monitored by eight CHP probes. The azimuthal variability was well related to crown architecture, but poorly to azimuthal differences in the xylem anatomical characteristics. Well-irrigated and deficit-irrigated olive trees showed similar xylem anatomical characteristics, but they differed in xylem growth and in the ratio of nocturnal-to-diurnal sap flow (N/D index). The results of this work indicate that transpiration cannot be accurately estimated by the CHP method in olive trees if a small number of sensors are employed and that the N/D index could be used as a sensitive water status indicator.

Identification of a putative Mexican strain of Serratia entomophila pathogenic against root-damaging larvae of Scarabaeidae (Coleoptera).

The larvae of scarab beetles, known as "white grubs" and belonging to the genera Phyllophaga and Anomala (Coleoptera: Scarabaeidae), are regarded as soil-dwelling pests in Mexico. During a survey conducted to find pathogenic bacteria with the potential to control scarab larvae, a native Serratia sp. (strain Mor4.1) was isolated from a dead third-instar Phyllophaga blanchardi larva collected from a cornfield in Tres Marías, Morelos, Mexico. Oral bioassays using healthy P. blanchardi larvae fed with the Mor4.1 isolate showed that this strain was able to cause an antifeeding effect and a significant loss of weight. Mortality was observed for P. blanchardi, P. trichodes, and P. obsoleta in a multidose experiment. The Mor4.1 isolate also caused 100% mortality 24 h after intracoelomic inoculation of the larvae of P. blanchardi, P. ravida, Anomala donovani and the lepidopteran insect Manduca sexta. Oral and injection bioassays were performed with concentrated culture broths of the Mor4.1 isolate to search for disease symptoms and mortality caused by extracellular proteins. The results have shown that Mor4.1 broths produce significant antifeeding effects and mortality. Mor4.1 broths treated with proteinase K lost the ability to cause disease symptoms and mortality, in both the oral and the injection bioassays, suggesting the involvement of toxic proteins in the disease. The Mor4.1 isolate was identified as a putative Serratia entomophila Mor4.1 strain based on numerical taxonomy and phylogenetic analyses done with the 16S rRNA gene sequence. The potential of S. entomophila Mor4.1 and its toxins to be used in an integrated pest management program is discussed.

Stomatal oscillations in olive trees: analysis and methodological implications.

Stomatal oscillations have long been disregarded in the literature despite the fact that the phenomenon has been described for a variety of plant species. This study aims to characterize the occurrence of oscillations in olive trees (Olea europaea L.) under different growing conditions and its methodological implications. Three experiments with young potted olives and one with large field-grown trees were performed. Sap flow measurements were always used to monitor the occurrence of oscillations, with additional determinations of trunk diameter variations and leaf-level stomatal conductance, photosynthesis and water potential also conducted in some cases. Strong oscillations with periods of 30-60 min were generally observed for young trees, while large field trees rarely showed significant oscillations. Severe water stress led to the disappearance of oscillations, but moderate water deficits occasionally promoted them. Simultaneous oscillations were also found for leaf stomatal conductance, leaf photosynthesis and trunk diameter, with the former presenting the highest amplitudes. The strong oscillations found in young potted olive trees preclude the use of infrequent measurements of stomatal conductance and related variables to characterize differences between trees of different cultivars or subjected to different experimental treatments. Under these circumstances, our results suggest that reliable estimates could be obtained using measurement intervals below 15 min.

OliveCan: A Process-Based Model of Development, Growth and Yield of Olive Orchards.

Several simulation models of the olive crop have been formulated so far, but none of them is capable of analyzing the impact of environmental conditions and management practices on water relations, growth and productivity under both well-irrigated and water-limiting irrigation strategies. This paper presents and tests OliveCan, a process-oriented model conceived for those purposes. In short, OliveCan is composed of three main model components simulating the principal elements of the water and carbon balances of olive orchards and the impacts of some management operations. To assess its predictive power, OliveCan was tested against independent data collected in two 3-year field experiments conducted in Córdoba, Spain, each of them applying different irrigation treatments. An acceptable level of agreement was found between measured and simulated values of seasonal evapotranspiration (ET, range 393 to 1016 mm year-1; RMSE of 89 mm year-1), daily transpiration (Ep, range 0.14-3.63 mm d-1; RMSE of 0.32 mm d-1) and oil yield (Yoil, range 13-357 g m-2; RMSE of 63 g m-2). Finally, knowledge gaps identified during the formulation of the model and further testing needs are discussed, highlighting that there is additional room for improving its robustness. It is concluded that OliveCan has a strong potential as a simulation platform for a variety of research applications.

Effect of soil temperature on root resistance: implications for different trees under Mediterranean conditions.

The effect of temperature on radial root hydraulic specific resistance (Rp) is a known phenomenon; however, the impact ofRpvariations expected from soil temperature changes over the tree root system is unknown. The present article analyses the relations hip ofRpwith temperature in olive 'Picual' and a hybrid rootstock, GF677, at five different temperatures, showing that a variation of 3- and 4.5-folds exists for olive 'Picual' and GF677 in the range from 10 to 20 °C. The functions obtained were scaled up to show the theoretical changes of total radial root system resistance in a common tree orchard in a Mediterranean climate at a daily and seasonal scale, using recorded soil temperature values: a difference between summer and winter of 3.5-fold for olive 'Picual' and 9-fold for GF677 was observed. Nevertheless,Rpchanges are not only related to temperature, as cavitation or circadian rhythms in aquaporin expression may also play a role. The results obtained from an experiment with the two cultivars submitted to constant pressure and temperature during several hours exhibited a variation inRp, but this was of lower magnitude than that observed due to temperature changes. Finally, a comparison ofRpat 25 °C between GF677 and GN15 (another rootstock obtained from the same parental as GF677) showed significant differences. According to our results, diurnal and seasonal changes inRpdue to temperature variations are of significant importance, and it would therefore be advisable to assess them explicitly into soil-plant-atmosphere continuum models.

Biochemical characterization and immunolocalization studies of a Capsicum chinense Jacq. protein fraction containing DING proteins and anti-microbial activity.

The DING protein family consists of proteins of great biological importance due to their ability to inhibit carcinogenic cell growth. A DING peptide with Mr ∼7.57 kDa and pI ∼5.06 was detected in G10P1.7.57, a protein fraction from Capsicum chinense Jacq. seeds. Amino acid sequencing of the peptide produced three smaller peptides showing identity to the DING protein family. G10P1.7.57 displayed a phosphatase activity capable of dephosphorylating different phosphorylated substrates and inhibited the growth of Saccharomyces cerevisiae cells. Western immunoblotting with a custom-made polyclonal antibody raised against a sequence (ITYMSPDYAAPTLAGLDDATK), derived from the ∼7.57 kDa polypeptide, immunodetected an âˆ¼ 39 kDa polypeptide in G10P1.7.57. Purification by electroelution followed by amino acid sequencing of the ∼39 kDa polypeptide yielded seven new peptide sequences and an additional one identical to that of the initially identified peptide. Western immunoblotting of soluble proteins from C. chinense seeds and leaves revealed the presence of the ∼39 kDa polypeptide at all developmental stages, with increased accumulation when the organs reached maturity. Immunolocalization using Dabsyl chloride- or Alexa fluor 488-conjugated antibodies revealed a specific fluorescent signal in the cell cytoplasm at all developmental stages, giving support to the idea that the ∼39 kDa polypeptide is a soluble DING protein. Thus, we have identified and characterized a protein fraction with a DING protein from C. chinense.

Pathogenicity of Isolates of Serratia Marcescens towards Larvae of the Scarab Phyllophaga Blanchardi (Coleoptera).

Serratia marcescens is a Gram negative bacterium (Enterobacteriaceae) often associated with infection of insects. In order to find pathogenic bacteria with the potential to control scarab larvae, several bacterial strains were isolated from the hemocoel of diseased Phyllophaga spp (Coleoptera:Scarabaeidae) larvae collected from cornfields in Mexico. Five isolates were identified as Serratia marcescens by 16S rRNA gene sequencing and biochemical tests. Oral and injection bioassays using healthy Phyllophaga blanchardi larvae fed with the S. marcescens isolates showed different degrees of antifeeding effect and mortality. No insecticidal activity was observed for Spodoptera frugiperda larvae (Lepidoptera: Noctuidae) by oral inoculation. S. marcescens (Sm81) cell-free culture supernatant caused significant antifeeding effect and mortality to P. blanchardi larvae by oral bioassay and also mortality by injection bioassay. Heat treated culture broths lost the ability to cause disease symptoms, suggesting the involvement of proteins in the toxic activity. A protein of 50.2 kDa was purified from the cell-free broth and showed insecticidal activity by injection bioassay towards P. blanchardi. Analysis of the insecticidal protein by tandem- mass spectrometry (LC-MS/MS) showed similarity to a Serralysin-like protein from S. marcescens spp. This insecticidal protein could have applications in agricultural biotechnology.

Balancing crop yield and water productivity tradeoffs in herbaceous and woody crops.

The links between water and crop yield are well known. In agricultural systems, maximum yield and maximum water productivity (WP; yield divided by water use) are not always compatible goals. In water-limited situations, optimal solutions must be reached by finding a compromise between the levels of crop production and WP. The tradeoffs between production and WP are reviewed here and the dominant effects of the environment on WP are examined. Genetic improvement for WP generally has yield tradeoffs, whereas management measures devised to improve WP also enhance yield. It is shown that partial closure of the stomata in response to environmental stimuli has a variable impact on canopy transpiration, depending on the degree of coupling between the canopy and the atmosphere. In contrast to the behaviour of the major herbaceous crops, WP increases in some woody crops in response to water stress, suggesting that biomass and transpiration are not linearly related, and that deficit irrigation should be successful in these species. Avoiding high evaporative demand periods (e.g. through tolerance to low temperatures) is an important option that aims to increase production and WP. A case study is presented for improving sunflower (Helianthus annuus L.) yield and WP in temperate environments.

Using the compensated heat pulse method to monitor trends in stem water content in standing trees.

Studying the dynamics of stem water content (θ) in living trees has an outstanding physiological interest but all the available techniques to measure θ exhibit major drawbacks. In this work, we present a new methodology to estimate variations in θ along with sap velocity using the compensated heat pulse (CHP) technique. One lab experiment was performed on several wooden blocks obtained from three different tree species. Samples were slowly dried and their moisture loss was monitored by both gravimetric approaches and time-domain reflectometry (TDR) or CHP probes in order to contrast the validity of our methodology (volumetric specific heat (VSH)-CHP) over a range of water contents. In addition, a field experiment was conducted to monitor θ fluctuations in standing olive trees (Olea europaea L. cv. 'Arbequina') growing under three different irrigation regimes. In the lab test, the actual θ values deduced gravimetrically differed from the estimates yielded by the VSH-CHP method. However, it could successfully track relative changes in the water stored for the range of θ expected in living wood. Furthermore, the field experiment showed a seasonal change in θ, which was similar in shape and magnitude to those reported in the literature for olive and other Mediterranean tree species. On the other hand, differences in the seasonal patterns of θ between irrigation treatments strongly corresponded with those of sap flow and some leaf water potential measurements. The results of this work suggest that the CHP technique could be employed to monitor the dynamics of both θ and sap flow simultaneously in standing trees and evidence that seasonal changes in θ might be used as a long-term water status indicator.

A model of daily mean canopy conductance for calculating transpiration of olive canopies.

We tested the hypothesis that the transpiration (λEp) of high-coupled canopies, such as olive groves, may be calculated on a daily basis with sufficient precision by the Penman-Monteith 'big leaf' equation, by a model of bulk daily canopy conductance (gc) capable of scaling for canopy dimension. Given the limited data required, such a model could replace the standard approach (ET0 × Kc) for calculating olive water requirements, enhancing the precision of estimates. We developed a specific model of daily gc for unstressed olive canopies that was calibrated by transpiration measurements obtained by water balance from a 2-year experiment in a mature orchard with λEp ranging from 0.6 (February 1993) to 11.5 (July 1994) MJ m-2 day-1 and where leaf area index (L) changed from 1.25 to 2.5. The model uses the intercepted fraction of daily PAR and a linear function of average daytime temperature. The model was validated with λEp data collected by eddy covariance in a 3-year experiment conducted in a growing orchard that differed in L and cultivar from the one used in the calibration. The gc model, when used in the Penman-Monteith equation, gave very good daily λEp predictions for all seasons during 3 years, ranging from 0.5 (November 1998) to 5.5 (June 2000) MJ m-2 day-1, indicating that the goals of dealing with the dependence of olive gc on L and of simulating the seasonal variations in gc were achieved. A comparison with the Jarvis gc model, calibrated with 2 months of measured gc hourly data, showed that the gc model developed here performed better than the Jarvis model for the 3-year dataset. The exception to this was the period in which the Jarvis model was calibrated. This indicates that (1) the Jarvis model did not account for the seasonal variations in gc of the olive trees; and (2) the spatial and temporal scale assumptions required in the calibration of gc generate seasonal errors in the simulated bulk daily λEp for this crop. The applicability of this bulk gc model is restricted to well watered olive canopies and to the one-layer approach of calculating λEp but it could be adapted to rain-fed canopies in the future.