Response of yam varieties to soil moisture regime in Southwestern Nigeria

A field experiment was conducted on varietal response of white yam to moisture regime in Abeokuta. The experiment comprised three varieties of yam (Efuru, Ise-osi and Oniyere), three mulching options (grass, polythene and unmulched), and two planting dates (early and late). Treatments were replicated three times using RCBD lay-out. Model for selecting planting date involved relating potential evapotranspiration (PE) to precipitation (P) in the form of 0.1PE<P < 0.5PE, partitioned for attaining optimal planting date into early {T1= Σ(P-0.1PE) ≤ 0} and late {T2 = Σ(P-0.5PE) ≤ 0}, respectively. For humid period defined by P> PE, the physiological parameters and moisture agro-climatic indices measured during phenological stages of yam grown were analyzed with respect to treatments. Result showed that T1 defined as Σ(P-0.1PE) ≤ 10 mm appeared as the best model that significantly (P < 0.05) influenced emergence rate, phenological growth and tuber yield. All yam varieties evaluated were suitable for planting with respect to yield. Efuru and Ise-osi synchronized perfectly with Actual Water Availability and produced good vegetative growth with LAI of 1.08 and 0.91 leading to higher tuber yield of 12 and 11.64 tonnes ha-1, respectively. Grass mulch had tuber yield, 4-6 tonnes ha-1greater than the polythene and unmulched plots in all varieties. Mulching significantly (P< 0.05) increased tuber yield, 6-8 tonnes ha-1than the unmulched. Conclusively, early planting with grass mulch increased tuber yield.

Yield and qualitative and biochemical characteristics of saffron (Crocus sativus L.) cultivated in different soil, water, and climate conditions

Saffron is highly valued for its unique aroma, taste, color, and medicinal properties. Iran is one of the most important saffron-producing countries. The present study aimed to investigate the effect of climatic and environmental characteristics of six sites (Shirvan, Faruj, Zavareh, Torbat-e Heydarieh, Ghayen, and Birjand) on the yield and qualitative, and biochemical characteristics of saffron. The studied sites were considered as treatments. The obtained data were analyzed based on a nested design, where the village within the site was considered an experimental error, and the farm within the village within each site was considered a sampling error. The Torbat-e Heydarieh treatment with altitudes of ~1323.3 m produced the maximum saffron flower yield (0.83 g m2), stigma yield (0.098 g m2), safranal content (15.8%), picrocrocin content (30.6%), and crocins content (69.3%). Evidently that the low maximum summer temperature in the area is one of the reasons for its superiority. The correlation analysis between traits shows that the maximum summer temperature had a significant negative correlation with saffron flower yield, stigma yield, and picrocrocin and crocin content. Results showed the highest total flavonoid and phenol content and DPPH activity related to Shirvan and Faruj. Although the results showed that selenium could increase the quantitative and qualitative yield of saffron, this requires further studies to confirm it. Based on the findings, it is concluded that I) qualitative and quantitative characteristics of saffron are strongly controlled by the environmental and climatic conditions and II) Razavi Khorasan province had a significant advantage in terms of flower and stigma yield and safranal, picrocrocin and crocin content of saffron and North Khorasan province in terms of biochemical characteristics.

Testing of Drought Exceedance Probability Index (DEPI) for Turkey using PERSIANN data for 2000-2021 period

Drought is a climatic event that threatens the environment and human life with an ambiguity of location and time. Recently, droughts can be analyzed for different periods with the help of different mathematical methods and developing technology. This study aims to perform a drought analysis in 126 designated study points of Turkey. The analyzed data includes monthly total precipitation values between March 2000 and February 2021, obtained from PERSIANN system (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks). Monthly precipitation totals of these designated points were used as input parameters in the Drought Exceedance Probability Index (DEPI) which is a new drought analysis method. The analysis was conducted separately for the whole of Turkey from January to December. Moreover, the findings were compared with the Standardized Precipitation Index (SPI), a globally accepted and commonly used drought index, to measure the drought detection performance of DEPI. SPI was calculated for periods of 6, 12 and 24 months. Pearson correlation coefficients between drought values of SPI-6, SPI-12 and SPI-24 and DEPI results were calculated. The second part of the study includes possible trend of drought determined by the Mann-Kendall trend analysis method. Both DEPI and SPI results and trend analysis results were mapped and visualized with the help of ArcGIS package program. The highest correlation is between DEPI and SPI-12 with 0.75, while the lowest correlation is between DEPI and SPI-24 with a value of 0.62. SPI monthly drought maps indicated the wettest months were January and February, while the driest months were March and July. Besides the DEPI monthly drought maps, the wettest months were October and November, while the driest months were May and June. The Mann-Kendall trend maps showed a significant increase in drought for summer.

Assessment of deficit irrigation impact on agronomic parameters and water use efficiency of six chickpea (Cicer Arietinum L.) cultivars under Mediterranean semi-arid climate

Six kabuli chickpea genotypes (Cicer Arietinum L.) were evaluated under three water levelss at the open field during February -June 2018. This study was conducted to evaluate the chickpea water stress, on soil water dynamic, agromorphological traits, and water use efficiency to estimate variability levels between varieties and to identify the varieties of chickpea adaptable on semi-arid bioclimatic stage. For this purpose, a trial was conducted at the Higher Agronomic Institute of Chott Mariem (Tunisia). There is no effect of the treatment on the height, biological yield, and branching number. The seeds weigh, PCG, seed yield, harvest index, and water use efficiency relative to seed have the highest value in T1 (100% of ETc) when water use efficiency relative to biological yield, number of pods and of seeds recorded the highest values in T3 (50% of ETc). Univariate analysis showed highly significant differences between genotypes for many traits. Principal Component Analysis was performed for all traits and allowed to define two axes. The first one explains 49.30% of the variability of the total trait and was formed by genotypes ‘Beja’, ‘Nayer’ and’ ‘Rebha’. Genotypes forming this axe are closely related to each other according to their common morphological characters like height (r=0.88), biological yield (r=0.93), bringing the number (r=0.53), seed yield (r=0.81), WUE relative to seed (r=0.75), harvest index (r=0.65) and WUE relative to biological yield (r=0.94). The second clustered genotypes ‘Bochra’ and ‘Nour’. This second axe (27.99%) is represented by pods number (r=0.87), seed number (r=0.87) and PCG (r=0.78).

Efficacy of benzyladenine for compensating the reduction in soybean productivity under low water supply

Undoubtedly, drought is a negative consequence of climate change. Farmers have to deal with this issue and may be forced to irrigate their crops with less water than required, however reduction in productivity is anticipated. Thus, two–year field trials were conducted to assess the impact of irrigation regimes (60, 80 and 100% of crop evapotranspiration, denoted ET60, ET80, and ET100, respectively) and benzyladenine rates (0, 50, 100, 150 and 200 mg L−1, symbolized as BA0, BA50, BA100, BA150, BA200, respectively) on soybean. Findings clarified that the maximum increases in plant height and net assimilation rate were obtained with the interactions of ET100 or ET80 x BA200 or BA150 in both seasons. ET80 x BA200 (in both seasons) and ET100 x BA150 (in the first season) were as similar as ET100 x BA200 for enhancing pods number plant−1. Irrigation water use efficiency progressively increased with decreasing irrigation water amount and increasing benzyladenine rate. In conclusion, the reduction in seed yield due to lowering water supply up to 80% of crop evapotranspiration (with saving 20% of irrigation water) could be compensated using benzyladenine, 150 mg L−1, thus it should be involved in soybean irrigation programs.

Predicting symptoms of downy mildew, powdery mildew, and gray mold diseases of grapevine through machine learning

Downy mildew, powdery mildew, and gray mold are major diseases of grapevine with a strong negative impact on fruit yield and fruit quality. These diseases are controlled by the application of chemicals, which may cause undesirable effects on the environment and on human health. Thus, monitoring and forecasting crop disease is essential to support integrated pest management (IPM) measures. In this study, two tree-based machine learning (ML) algorithms, random forest and C5.0, were compared to test their capability to predict the appearance of symptoms of grapevine diseases, considering meteorological conditions, spatial indices, the number of crop protection treatments and the frequency of monitoring days in which symptoms were recorded in the previous year. Data collected in Tuscany region (Italy), on the presence of symptoms on grapevine, from 2006 to 2017 were divided with an 80/20 proportion in training and test set, data collected in 2018 and 2019 were tested as independent years for downy mildew and powdery mildew. The frequency of symptoms in the previous year and the cumulative precipitation from April to seven days before the monitoring day were the most important variables among those considered in the analysis for predicting the occurrence of disease symptoms. The best performance in predicting the presence of symptoms of the three diseases was obtained with the algorithm C5.0 by applying (i) a technique to deal with imbalanced dataset (i.e., symptoms were detected in the minority of observations) and (ii) an optimized cut-off for predictions. The balanced accuracy achieved in the test set was 0.8 for downy mildew, 0.7 for powdery mildew and 0.9 for gray mold. The application of the models for downy mildew and powdery mildew in the two independent years (2018 and 2019) achieved a lower balanced accuracy, around 0.7 for both the diseases. Machine learning models were able to select the best predictors and to unravel the complex relationships among geographic indices, bioclimatic indices, protection treatments and the frequency of symptoms in the previous year.

Micrometeorological modeling and water consumption of tabasco pepper cultivated under greenhouse conditions

Micrometeorological variables of tabasco pepper cultivated under greenhouse and drip irrigated conditions have not been presented to date in literature, especially the water consumption of these plants, in terms of crop evapotranspiration (ETc) and crop coefficient (Kc). The determination of these variables is extremely important for the application of the correct amount of water to irrigated crops in these environments because PM FAO (56) standard methodology was idealized for outdoor environments. The objective of this work was to develop models of estimation of micrometeorological variables in greenhouse conditions and to determine the water demand, in terms of evapotranspiration (ET) and Kc, of the pepper (Capsicum frutescens L.), cv. Tabasco McIlhenny, drip irrigated using drainage lysimeters. The research was carried out in an experimental area located at the University of Sao Paulo (USP) in Piracicaba, SP, Brazil. The following micrometeorological variables were monitored: air temperature, air relative humidity (digital thermohygrometer) and evaporation (mini-pan) (EMT). Drainage lysimeters were used to obtain the ETc and the reference evapotranspiration (ETo) was estimated outside the greenhouse by the Penman Monteith (EToPM), Hargreaves and Samani (EToHS) methods and the class “A” pan method (ECA). It was concluded that the total value of mini-pan evaporation (EMT) inside the greenhouse was practically equal to EToPM, 5% lower than EToHS and 31% higher than ECA in the outdoor environment. ET values ranged from 0.28 to 2.42 mm day-1 and total crop ET was 446.43 mm. The Kc values for the first pepper production cycle were: 0.17 in the initial phase, 0.76 in the flowering and fruiting phase and 0.39 in the harvest phase, for the second production cycle, the value of Kc was 0.50 at the harvest phase.

Estimation of measured evapotranspiration using data-driven methods with limited meteorological variables

Determination of surface energy balance depends on the energy exchange between land and atmosphere. Thus, crop, soil and meteorological factors are crucial, particularly in agricultural fields. Evapotranspiration is derived from latent heat component of surface energy balance and is a key factor to clarify the energy transfer mechanism. Development of the methods and technologies for the aim of determining and measuring of evapotranspiration have been one of the main focus points for researchers. However, the direct measurement systems are not common because of economic reasons. This situation causes that different methods are used to estimate evapotranspiration, particularly in locations where no measurements are made. Thus, in this study, non-linear techniques were applied to make accurate estimations of evapotranspiration over the winter wheat canopy located in the field of Atatürk Soil Water and Agricultural Meteorology Research Institute Directorate, Kırklareli, Turkey. This is the first attempt in the literature which consist of the comparison of different machine learning methods in the evapotranspiration values obtained by the Bowen Ratio Energy Balance system. In order to accomplish this aim, support-vector machine, Adaptive neuro fuzzy inference system and Artificial neural network models have been evaluated for different input combinations. The results revealed that even with only global solar radiation data taken as an input, a high prediction accuracy can be achieved. These results are particularly advantageous in cases where the measurement of meteorological variables is limited. With the results of this study, progress can be made in the efficient use and management of water resources based on the input parameters of evapotranspiration especially for regions with limited data.

The influence of extreme weather events on farm economic performance – a case study from Serbia

Western Balkan region, particularly Serbia, is faced with an increased frequency of extreme weather events, as a consequence of global climate change. However, there is still no enough research on how the effects of extreme weather events could be measured on the farm level. More importantly, there is no standard international methodology that is used regularly to address the issue. Therefore, the aim of this research was to evaluate the effects of extreme weather events on business performances of two the most common farm types in Serbia. To achieve this goal, the authors performed a financial loss assessment on a farm level. Panel models and R software environment were used to perform a multiple regression analysis allowing to indicate determinants of financial loss indicator depending on the farm’s production type. The results indicated that performance of both farm types is more influenced by drought than by floods. The regression analysis revealed that for both farm types financial stress is the most important independent variable.

Meteorological and Salix species (S. acutifolia, S. smithiana, S. viminalis) phenological trends in central Italy

Plant phenology, through opportune observing and interpreting techniques can be useful to interpret the eventual plant vegetative and reproductive adaptation to climate changes. Some plants of Salix acutifolia Willd., S. smithiana Willd. and S. viminalis L. were considered in a phenological garden in central Italy for analysing their phenological growth stages according to the International gardens network indications during a 10-year period (2008-2017) which allowed us to realize some preliminary trend analyses. The 3 Salix species showed different behaviours in the same cultivation area. S. acutifolia manifested no trend for spring and autumnal phases, S. viminalis presented low significant trends while S. Smithiana was that with the more evident tendencies for all the considered vegetative phases during the study period. The reproductive phase (BBCH 65) showed no significant trend for any Salix species during the study period not being influenced by the different meteorological variables and suggesting that photoperiod in this case may play an important role. The more evident phenological trends were represented for 2 Salix species by the advance of the leaf development during spring and by the progressive delay of the senescence during the last part of the summer, with the fallen leaves phase that was recorded averagely 2 weeks later during the last years of the study period.