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The spatial heterogeneity in hydrologic simulations is a key difference between lumped and distributed models. Not all distributed models benefit from pedo-transfer functions based on the soil properties and crop-vegetation dynamics. Mostly coarse-scale meteorological forcing is used to estimate only the water balance at the catchment outlet. The mesoscale Hydrologic Model (mHM) is one of the rare models that incorporate remote sensing data, i.e., leaf area index (LAI) and aspect, to improve the actual evapotranspiration (AET) simulations and water balance together. The user can select either LAI or aspect to scale PET. However, herein we introduce a new weight parameter, "alphax", that allows the user to incorporate both LAI and aspect together for potential evapotranspiration (PET) scaling. With the mHM code enhancement, the modeler also has the option of using raw PET with no scaling. In this study, streamflow and AET are simulated using the mHM in The Main Basin (Germany) for the period of 2002–2014. The additional value of PET scaling with LAI and aspect for model performance is investigated using Moderate Resolution Imaging Spectroradiometer (MODIS) AET and LAI products. From 69 mHM parameters, 26 parameters are selected for calibration using the Optimization Software Toolkit (OSTRICH). For calibration and evaluation, the KGE metric is used for water balance, and the SPAEF metric is used for evaluating spatial patterns of AET. Our results show that the AET performance of the mHM is highest when using both LAI and aspect indicating that LAI and aspect contain valuable spatial heterogeneity information from topography and canopy (e.g., forests, grasslands, and croplands) that should be preserved during modeling. This is key for agronomic studies like crop yield estimations and irrigation water use. The additional "alphax" parameter makes the model physically more flexible and robust as the model can decide the weights according to the study domain. [ABSTRACT FROM AUTHOR]

The production of onions bulbs (Allium cepa L.) requires a high amount of nitrogen. According to the demand of sustainable agriculture, the information-development and communication technologies allow for improving the efficiency of nitrogen fertilization. In the south of the province of Buenos Aires, Argentina, between 8000 and 10,000 hectares per year−1 are cultivated in the districts of Villarino and Patagones. This work aimed to analyze the relationship of biophysical variables: leaf area index (LAI), canopy chlorophyll content (CCC), and canopy cover factor (fCOVER), with the nitrogen fertilization of an intermediate cycle onion crop and its effects on yield. A field trial study with different doses of granulated urea and granulated urea was carried out, where biophysical characteristics were evaluated in the field and in Sentinel-2 satellite observations. Field data correlated well with satellite data, with an R2 of 0.91, 0.96, and 0.85 for LAI, fCOVER, and CCC, respectively. The application of nitrogen in all its doses produced significantly higher yields than the control. The LAI and CCC variables had a positive correlation with yield in the months of November and December. A significant difference was observed between U250 (62 Mg ha−1) and the other treatments. The U500 dose led to a yield increase of 27% compared to U250, while the difference between U750 and U500 was 6%. [ABSTRACT FROM AUTHOR]

The Leaf Area Index (LAI) strongly influences crop biomass production and yields. The variation characteristic of LAI and the development of crop growth models can provide a theoretical basis for predicting crops' water consumption, fruit quality and yields. This paper analyzes the relationship between measurements of aboveground grape biomass and trends in LAI and dry biomass production in grapes grown in the Turpan area. The LAI changes in grapes were estimated using the modified logistic model, the modified Gaussian model, the log-normal model, the cubic polynomial model, and the Gaussian model. Universal models of LAI were established in which the applied irrigation quota was applied to calculate the maximum LAI. The relationship between the irrigation quota and biomass production, yields, and the harvest index was investigated. The developed models could accurately predict the LAI of grapevines grown in an extremely arid area. However, the Gaussian and cubic polynomial models produced less accurate results than the other models tested. The Michaelis–Menten model analyzed the relationship between biomass and LAI, providing a numerical method for predicting dynamic changes in grapevine LAI. Moreover, the crop biomass increased linearly with the irrigation quota for quotas between 6375 and 13,200 m3/hm. This made it possible to describe the grape yield and harvest index with a quadratic polynomial function, which increases during the early stages of the growing season and then decreases. The analyses of the relationship between yield and harvest index provide important theoretical insights that can be used to improve water use efficiency in grape cultivation and to identify optimal irrigation quotas. [ABSTRACT FROM AUTHOR]

The spatial heterogeneity in hydrologic simulations is a key difference between lumped and distributed models. Not all distributed models benefit from pedo-transfer functions based on the soil properties and crop-vegetation dynamics. Mostly coarse-scale meteorological forcing is used to estimate only the water balance at the catchment outlet. The mesoscale Hydrologic Model (mHM) is one of the rare models that incorporate remote sensing data, i.e., leaf area index (LAI) and aspect, to improve the actual evapotranspiration (AET) simulations and water balance together. The user can select either LAI or aspect to scale PET. However, herein we introduce a new weight parameter, “alphax”, that allows the user to incorporate both LAI and aspect together for potential evapotranspiration (PET) scaling. With the mHM code enhancement, the modeler also has the option of using raw PET with no scaling. In this study, streamflow and AET are simulated using the mHM in The Main Basin (Germany) for the period of 2002–2014. The additional value of PET scaling with LAI and aspect for model performance is investigated using Moderate Resolution Imaging Spectroradiometer (MODIS) AET and LAI products. From 69 mHM parameters, 26 parameters are selected for calibration using the Optimization Software Toolkit (OSTRICH). For calibration and evaluation, the KGE metric is used for water balance, and the SPAEF metric is used for evaluating spatial patterns of AET. Our results show that the AET performance of the mHM is highest when using both LAI and aspect indicating that LAI and aspect contain valuable spatial heterogeneity information from topography and canopy (e.g., forests, grasslands, and croplands) that should be preserved during modeling. This is key for agronomic studies like crop yield estimations and irrigation water use. The additional “alphax” parameter makes the model physically more flexible and robust as the model can decide the weights according to the study domain.

Near-real-time, high-spatial-resolution leaf area index (LAI) maps would enable producers to monitor crop health and growth status, improving agricultural practices such as fertiliser and water management. LAI retrieval methods are numerous and can be divided into statistical and physically based methods. While statistical methods are generally subject to high site-specificity but possess high ease of implementation and use, physically based methods are more transferable, albeit more complex to use in operational settings. In addition, statistical methods need a large amount of data for calibration and subsequent validation, and this is only seldom feasible. Techniques based on predictive equations (PEphysical) represent a viable alternative, allowing the partial combination of statistical and physical methods merits while minimising their shortcomings. In this paper, predictive equation-based techniques were compared with four other methods: two radiative transfer model (RTM) inversion methods, one based on neural network (NNET) and one based on a look-up table (LUT), and two empirical methods (one using empirical models based on vegetation indices and in situ data and one based on empirical models found in the scientific literature). The methods were chosen based on common use. To evaluate the performance of the studied methods, the coefficient of determination (R2), root mean square error (RMSE), and normalised root mean square error (nRMSE, %) between the estimates and in situ LAI measurements were reported. The best PEphysical results, achieved by the OSAVI index (RMSE = 0.84 m2 m−2), provided better performance for LAI recovery than the NNET-based RTM inversions (0.86 m2 m−2) or the estimates made by LUT (0.94 m2 m−2). Furthermore, the best PEphysical produced accuracies comparable to the best empirical model (RMSE = 0.71 m2 m−2), calibrated through in situ data, and similar to the best literature model (RMSE = 0.76 m2 m−2). These results indicated that PEphysical can be used to recover LAI with transferability comparable to literature models.

The production of onions bulbs (Allium cepa L.) requires a high amount of nitrogen. According to the demand of sustainable agriculture, the information-development and communication technologies allow for improving the efficiency of nitrogen fertilization. In the south of the province of Buenos Aires, Argentina, between 8000 and 10,000 hectares per year−1 are cultivated in the districts of Villarino and Patagones. This work aimed to analyze the relationship of biophysical variables: leaf area index (LAI), canopy chlorophyll content (CCC), and canopy cover factor (fCOVER), with the nitrogen fertilization of an intermediate cycle onion crop and its effects on yield. A field trial study with different doses of granulated urea and granulated urea was carried out, where biophysical characteristics were evaluated in the field and in Sentinel-2 satellite observations. Field data correlated well with satellite data, with an R2 of 0.91, 0.96, and 0.85 for LAI, fCOVER, and CCC, respectively. The application of nitrogen in all its doses produced significantly higher yields than the control. The LAI and CCC variables had a positive correlation with yield in the months of November and December. A significant difference was observed between U250 (62 Mg ha−1) and the other treatments. The U500 dose led to a yield increase of 27% compared to U250, while the difference between U750 and U500 was 6%.

The Leaf Area Index (LAI) strongly influences crop biomass production and yields. The variation characteristic of LAI and the development of crop growth models can provide a theoretical basis for predicting crops’ water consumption, fruit quality and yields. This paper analyzes the relationship between measurements of aboveground grape biomass and trends in LAI and dry biomass production in grapes grown in the Turpan area. The LAI changes in grapes were estimated using the modified logistic model, the modified Gaussian model, the log-normal model, the cubic polynomial model, and the Gaussian model. Universal models of LAI were established in which the applied irrigation quota was applied to calculate the maximum LAI. The relationship between the irrigation quota and biomass production, yields, and the harvest index was investigated. The developed models could accurately predict the LAI of grapevines grown in an extremely arid area. However, the Gaussian and cubic polynomial models produced less accurate results than the other models tested. The Michaelis–Menten model analyzed the relationship between biomass and LAI, providing a numerical method for predicting dynamic changes in grapevine LAI. Moreover, the crop biomass increased linearly with the irrigation quota for quotas between 6375 and 13,200 m3/hm. This made it possible to describe the grape yield and harvest index with a quadratic polynomial function, which increases during the early stages of the growing season and then decreases. The analyses of the relationship between yield and harvest index provide important theoretical insights that can be used to improve water use efficiency in grape cultivation and to identify optimal irrigation quotas.

Camelina (Camelina sativa (L.) Crantz) is an oil plant that can increase farmland biodiversity in many parts of the world. In addition to food importance, it is a good alternative in biofuel production. The aim of the experiment was to evaluate the response of camelina, the variety Śmiłowska (spring form), to various foliar fertilization. The combined application of three fertilizers had the most positive effect on the tested features and economic result: urea (46% N), magnesium sulfate (16% MgO + 32% SO3), and Plonvit R (multi-component fertilizer). The obtained increase in seed yield after the application of the above variant was 0.54 t ha−1, i.e., 37.5% compared to the control. The remaining fertilization combinations did not have a significant effect on seed yield, which amounted on average to 1.66 t ha−1. The yield of fat and protein amounted to 0.68 t·ha−1 and 0.42 t ha−1, respectively, and was strongly correlated with seed yield. The yielding of the variety Śmiłowska was stable over the years of the study. The combined use of three foliar fertilizers (variant H) increased the SPAD (soil plant analysis development) and LAI (leaf area index) values compared to the control. The application of urea alone reduced crude fat content in the seeds.

Super-high density (SHD) is the latest innovation in almond growing. This new cropping system needs to be studied in different climates, soils, latitudes and cultivars in order to promote more efficient and sustainable orchard management. This study shows the effects of two row orientations and different canopy positions on leaf area index (LAI), photosynthetically active radiation (PAR) and biological, phenological and agronomical parameters of a SHD almond orchard. Total bud number and flower bud number were higher for N-S row orientation and more wood buds were detected in top layers. LAI was strongly influenced by layer, but not by row orientation. Row orientation did not affect blooming or ripening phenology. Fruit number per layer was higher for North–South (N-S) row orientation and in middle layers; fruit set showed the opposite trend to flower bud and fruit numbers, achieving higher values for East–West (E-W) row orientation. Hulled fruit yield was not affected by row orientation but by canopy height. N-S oriented rows showed a greater number of empty nuts than E-W, but no differences were found between layers. We concluded that in SHD almond orchards, row orientation is determinant for sustainable crop management.

The decrease in the rate of inflow and outflow of water—and thereby the uptake of plant nutrients as the result of Huanglongbing (HLB or citrus greening)—leads to a decline in overall tree growth and the development of nutrient deficiencies in HLB-affected citrus trees. This study was conducted at the University of Florida, Southwest Florida Research and Education Center (SWFREC) near Immokalee, FL from January 2017 through December 2019. The objective of the study was to determine the effect of rootstocks, nutrient type, rate, and frequency of applications on leaf area index (LAI), water relations (stomatal conductance [gs], stem water potential [Ψw], and sap flow), soil nutrient accumulation, and dynamics under HLB-affected citrus trees. The experiment was arranged in a split-split plot design that consisted of two types of rootstocks, three nitrogen (N) rates, three soil-applied secondary macronutrients, and an untreated control replicated four times. LAI significantly increased in response to the secondary macronutrients compared with uncontrolled trees. A significantly greater gs, and thus a decline in Ψw, was a manifestation of higher sap flow per unit LA (leaf area) and moisture stress for trees budded on Swingle (Swc) than Cleopatra (Cleo) rootstocks, respectively. The hourly sap flow showed significantly less water consumption per unit LA for trees that received a full dose of Ca or Mg nutrition than Ca + Mg treated and untreated control trees. The soil nutrient concentrations were consistently higher in the topmost soil depth (0–15 cm) than the two lower soil depths (15–30 cm, 30–45 cm). Mobile nutrients: soil nitrate–nitrogen (NO3-N) and Mg2+ Mg2+, Mn2+, Zn2+, and B leached to the lower soil (15–30 cm) depth during the summer season. However, the multiple split applications of N as Best Management Practices (BMPs) and optimum irrigation scheduling based on reference evapotranspiration (ETo) maintained soil available N (ammonium nitrogen [NH4-N] and NO3-N) below 4.0 mg kg−1, which was a magnitude 2.0–4.0× less than the conventional N applications. Soil NH4-N and NO3-N leached to the two lower soil depths during the rainy summer season only when trees received the highest N rate (280 kg ha−1), suggesting a lower citrus N requirement. Therefore, 224 kg ha−1 N coupled with a full Ca or Mg dose could be the recommended rate for HLB-affected citrus trees.

In 2019–2020, a study was conducted to evaluate the suitability of willow composts as a substrate or substrate component in tomato transplant cultivation. In 2019, 4-year-old chopped willow biomass (mostly chips <2 cm long) was formed into four compost prisms: S0—willow compost without additives; SN—willow compost with the addition of nitrogen; SF—willow compost with the addition of wood-decaying mycelium; and SFN—willow compost with the addition of wood-decaying mycelium and nitrogen. Willow compost was rated as a homogeneous substrate (S0, SN, SF, and SFN) and as a substrate component with peat (P), mixed in willow:peat ratios such as 25:75, 50:50, and 75:25, in the variants S0:P, SN:P, SF:P, and SFN:P. For reference, deacidified peat was used as a homogeneous substrate. The study showed that willow compost could be used as a renewable plant material replacing peat. The best parameters (plant height, leaf span, number of leaves, and especially the highest weight) were found in tomato transplants grown in the SF:P and SFN:P substrates and at a 25:75 ratio. It was found that the addition of nitrogen to the compost, in order to obtain a wide C:N ratio, negatively affected the initial growth of tomato plants. [ABSTRACT FROM AUTHOR]

Super-high density (SHD) is the latest innovation in almond growing. This new cropping system needs to be studied in different climates, soils, latitudes and cultivars in order to promote more efficient and sustainable orchard management. This study shows the effects of two row orientations and different canopy positions on leaf area index (LAI), photosynthetically active radiation (PAR) and biological, phenological and agronomical parameters of a SHD almond orchard. Total bud number and flower bud number were higher for N-S row orientation and more wood buds were detected in top layers. LAI was strongly influenced by layer, but not by row orientation. Row orientation did not affect blooming or ripening phenology. Fruit number per layer was higher for North–South (N-S) row orientation and in middle layers; fruit set showed the opposite trend to flower bud and fruit numbers, achieving higher values for East–West (E-W) row orientation. Hulled fruit yield was not affected by row orientation but by canopy height. N-S oriented rows showed a greater number of empty nuts than E-W, but no differences were found between layers. We concluded that in SHD almond orchards, row orientation is determinant for sustainable crop management. [ABSTRACT FROM AUTHOR]

Camelina (Camelina sativa (L.) Crantz) is an oil plant that can increase farmland biodiversity in many parts of the world. In addition to food importance, it is a good alternative in biofuel production. The aim of the experiment was to evaluate the response of camelina, the variety Śmiłowska (spring form), to various foliar fertilization. The combined application of three fertilizers had the most positive effect on the tested features and economic result: urea (46% N), magnesium sulfate (16% MgO + 32% SO3), and Plonvit R (multi-component fertilizer). The obtained increase in seed yield after the application of the above variant was 0.54 t ha−1, i.e., 37.5% compared to the control. The remaining fertilization combinations did not have a significant effect on seed yield, which amounted on average to 1.66 t ha−1. The yield of fat and protein amounted to 0.68 t·ha−1 and 0.42 t ha−1, respectively, and was strongly correlated with seed yield. The yielding of the variety Śmiłowska was stable over the years of the study. The combined use of three foliar fertilizers (variant H) increased the SPAD (soil plant analysis development) and LAI (leaf area index) values compared to the control. The application of urea alone reduced crude fat content in the seeds. [ABSTRACT FROM AUTHOR]

The decrease in the rate of inflow and outflow of water—and thereby the uptake of plant nutrients as the result of Huanglongbing (HLB or citrus greening)—leads to a decline in overall tree growth and the development of nutrient deficiencies in HLB-affected citrus trees. This study was conducted at the University of Florida, Southwest Florida Research and Education Center (SWFREC) near Immokalee, FL from January 2017 through December 2019. The objective of the study was to determine the effect of rootstocks, nutrient type, rate, and frequency of applications on leaf area index (LAI), water relations (stomatal conductance [gs], stem water potential [Ψw], and sap flow), soil nutrient accumulation, and dynamics under HLB-affected citrus trees. The experiment was arranged in a split-split plot design that consisted of two types of rootstocks, three nitrogen (N) rates, three soil-applied secondary macronutrients, and an untreated control replicated four times. LAI significantly increased in response to the secondary macronutrients compared with uncontrolled trees. A significantly greater gs, and thus a decline in Ψw, was a manifestation of higher sap flow per unit LA (leaf area) and moisture stress for trees budded on Swingle (Swc) than Cleopatra (Cleo) rootstocks, respectively. The hourly sap flow showed significantly less water consumption per unit LA for trees that received a full dose of Ca or Mg nutrition than Ca + Mg treated and untreated control trees. The soil nutrient concentrations were consistently higher in the topmost soil depth (0–15 cm) than the two lower soil depths (15–30 cm, 30–45 cm). Mobile nutrients: soil nitrate–nitrogen (NO3-N) and Mg2+ Mg2+, Mn2+, Zn2+, and B leached to the lower soil (15–30 cm) depth during the summer season. However, the multiple split applications of N as Best Management Practices (BMPs) and optimum irrigation scheduling based on reference evapotranspiration (ETo) maintained soil available N (ammonium nitrogen [NH4-N] and NO3-N) below 4.0 mg kg−1, which was a magnitude 2.0–4.0× less than the conventional N applications. Soil NH4-N and NO3-N leached to the two lower soil depths during the rainy summer season only when trees received the highest N rate (280 kg ha−1), suggesting a lower citrus N requirement. Therefore, 224 kg ha−1 N coupled with a full Ca or Mg dose could be the recommended rate for HLB-affected citrus trees. [ABSTRACT FROM AUTHOR]

Leaf Area Index (LAI) is an important plant parameter for both farmers and plant scientists to monitor and/or model the growth and the well-being of plants. Since direct LAI measurement techniques are relatively laborious and time-consuming, various indirect methods have been developed and widely used since the early 1990s. The LP-80 ceptometer uses a linear array of PAR (photosynthetically active radiation) sensors for non-destructive LAI measurements that is backed by 15 years of research. Despite this, considerable discrepancy can be found between the expert opinions regarding the optimal illumination conditions recommended for the measurement. The sensitivity of ceptometer-based LAI values to PAR was investigated, and a simple method was devised to correct raw ceptometer data collected under non-ideal light conditions. Inadequate light conditions (PAR < 1700 µmol m−2 s−1) could cause an underestimation of LAI. Using the corrected LAI values, the ceptometer data showed a significantly better fit (higher R2, smaller mean average error and closer to zero mean signed error values) to the destructive LAI data for both wheat and maize. With the help of the correction equations, the use of the LP-80 ceptometer could be extended to days when light conditions are not ideal. [ABSTRACT FROM AUTHOR]