Use of soil and vegetation spectroradiometry to investigate crop water use efficiency of a drip irrigated tomato

An agronomic research was conducted in Tuscany (Central Italy) to evaluate the effects of an advanced irrigation system on the water use efficiency (WUE) of a tomato crop and to investigate the ability of soil and vegetation spectroradiometry to detect and map WUE. Irrigation was applied following an innovative approach based on CropSense system. Soil water content was monitored at four soil depths (10, 20, 30 and 50 cm) by a probe. Rainfall during the crop cycle reached 162 mm and irrigation water applied with a drip system amounted to 207 mm, distributed with 16 irrigation events. Tomato yield varied from 7.10 to 14.4 kg m⁻², with a WUE ranging from 19.1 to 38.9 kg m⁻³. The irrigation system allowed a high yield levels and a low depth of water applied, as compared to seasonal ET crop estimated with Hargraves’ formula and with the literature data on irrigated tomato. Measurements were carried out on geo-referenced points to gather information on crop (crop yield, eighteen Vegetation indices, leaf area index) and on soil (spectroradiometric and traditional analysis). Eight VIs, out of nineteen ones analyzed, showed a significant relationship with georeferenced yield data; PVI maps seemed able to return the best response, before harvesting, to improve the knowledge of the area of cultivation and irrigation system. CropSense irrigation system reduced seasonal irrigation volumes. Some vegetation indexes were significantly correlated to tomato yield and well identify, a posteriori, crop area with low WUE; spectroradiometry can be a valuable tool to improve irrigated tomato field management.     

Response of giant reed (Arundo donax L.) to nitrogen fertilization and soil water availability in semi-arid Mediterranean environment

The aim of the present work was to evaluate the effect of soil water availability and nitrogen fertilization on yield, water use efficiency and agronomic nitrogen use efficiency of giant reed (Arundo donax L.) over four-year field experiment.After the year of establishment, three levels for each factor were studied in the following three years: I₀ (irrigation only during the year of establishment), I₁ (50% ETm restitution) and I₂ (100% ETm restitution); N₀ (0 kg N ha⁻¹), N₁ (60 kg N ha⁻¹) and N₂ (120 kg N ha⁻¹).Irrigation and nitrogen effects resulted significant for stem height and leaf area index (LAI) before senescence, while no differences were observed for stem density and LAI at harvest.Aboveground biomass dry matter (DM) yield increased following the year of establishment in all irrigation and N fertilization treatments. It was always the highest in I₂N₂ (18.3, 28.8 and 28.9 t DM ha⁻¹ at second, third and fourth year growing season, respectively). The lowest values were observed in I₀N₀ (11.0, 13.4 and 12.9 t DM ha⁻¹, respectively).Water use efficiency (WUE) was significantly higher in the most stressed irrigation treatment (I₀), decreasing in the intermediate (I₁) and further in the highest irrigation treatment (I₂). N fertilization lead to greater values of WUE in all irrigation treatment.The effect of N fertilization on agronomic nitrogen use efficiency (NUE) was significant only at the first and second growing season.Giant reed was able to uptake water at 160–180 cm soil depth when irrigation was applied, while up to 140–160 cm under water stress condition.Giant reed appeared to be particularly suited to semi-arid Mediterranean environments, showing high yields even in absence of agro-input supply.     

Modelling crop growth and biomass partitioning to shoots and roots in relation to nitrogen and water availability, using a maximization principle. II. Simulation of crop nitrogen balance

This study analysed of the ability of a crop model to simulate crop nitrogen (N) balance. The model was originally developed to serve as a foundation to develop a decision-making tool to analyse the impact of water management and nitrogen fertilization on crop yield. The model included a dynamic parameter for allocation of dry matter between root and shoot allowing root to shoot ratio to vary according to differing environmental conditions. The new allocation parameter was introduced in order to make the model more applicable under water and nitrogen limited growing conditions. Two wheat (Triticum aestivum L.) data sets were used to test the model simulations. Generally, the model simulations agreed well with the recorded data on crop N uptake. The relationship between the actual and simulated amount of N taken up by the crop was close in the calibration treatments of a greenhouse experiment. The coefficient of determination (r²) of the regression line (simulated value = independent variable, measured value = dependent variable) was 0.90. The r² was 0.83 for the validation data. In the field experiments, the r² values were 0.91 for the calibration data and 0.82 for the validation data. In field data, the model underestimated in some cases the crop N uptake during the period when actual shoot dry weight increased exponentially in spring. Therefore, methods used in computation of nitrogen uptake have to be analysed further. Plant organ N content was simulated satisfactorily for both greenhouse and field data. However, the range over which the simulated values varied was larger than in the actual data.

The results from the study indicate that our model is capable of simulating the crop N balance and we suggest that the model could be used when developing an N application decision tool for field crops. However, the availability of N and soil water were provided as inputs in the present study. Thus, the model should be integrated with models simulating below ground processes in the future. Moreover, the model should be further validated with actual field data.     

Integrated “omics” approaches to sustain global productivity of major grain legumes under heat stress

Grain legumes serve as key sources of dietary protein to the global human population. Consequence of high‐temperature (HT) stress is increasingly evident as drastically lost production of different crops including grain legumes worldwide, thus putting the global food security under great threat. In a changing climate scenario, cool season‐adapted grain legumes frequently encounter heat stress (HS) during their reproductive phase, thus witnessing serious yield losses. To combat the emerging challenges of HT stress, an integrated approach demanding collaborative efforts from various disciplines of plant science should be in place. This review summarizes major impacts of HT stress on grain legume, and captures the relevance of crop genetic resources to HS tolerance in these crops. Measurement of physiological traits assumes key place in view of ever‐increasing precision of next‐generation phenotyping assays. We also discuss the significance of genetic inheritance and QTL discovery and evolving “omics” science for developing HS tolerance grain legume crops.     

Active label-based packaging to extend the shelf-life of “Calanda” peach fruit: Changes in fruit quality and enzymatic activity

Nectarine fruit after cold storage soften normally, but become dry instead of juicy and can develop flesh browning, bleeding and a gel-like or glassy formation of the flesh near the pit. An experiment was conducted to see if time-resolved reflectance spectroscopy could distinguish these internal disorders non-destructively. The optical parameters of absorption coefficient (μ_a) and reduced scattering coefficient (μ′_s) were measured at 670 nm and 780 nm, on nectarine (Prunus persica cv. Morsiani 90) fruit held at 20 °C after harvest or after 30 d of storage at 0 °C or 4 °C. Each day for 5 d 30 fruit were examined both non-destructively and destructively. Other measurements were firmness with a penetrometer, peel colour on the blush and non-blush side, expressible juice, weight loss, and visual rating of internal browning, bleeding, and gel. The fruit had been sorted at harvest according to the value of μ_a670 so that each batch had a similar spread of fruit maturity. More mature fruit (lower μ_a670 values) developed internal browning and bleeding with more severe symptoms compared to less mature ones (higher μ_a670 values). It was found that μ_a780 could distinguish healthy fruits from the chilling injured ones. Canonical discriminant analysis indicated that fruit without cold storage had low μ_a780, less water loss, low firmness, but high μ_a670 and high expressible juice compared with cool stored fruit. Fruit cool stored at 4 °C had high μ_a780 and less expressible juice, lower water loss and lower firmness compared with fruit cool stored at 0 °C. It was concluded that time resolved reflectance spectroscopy could detect internal woolliness and internal browning in nectarines after storage.